Monitoring Colonias Development along the 

United States–Mexico Border: A Process 

Application using GIS and Remote Sensing in 

Douglas, Arizona, and Agua Prieta, Sonora 

By Laura M. Norman1

, Angela J. Donelson2, Edwin L. Pfeifer1, Alven H. Lam3, and Kenneth J. 

Osborn4

Open-File Report 2004-1212 

2004 

U.S. DEPARTMENT OF THE INTERIOR 

U.S. GEOLOGICAL SURVEY

 

1

 U.S. Geological Survey, 520 N. Park Ave. #355, Tucson, AZ 85719 2

 U.S. Department of Housing and Urban Development, 160 N. Stone Ave. Tucson, AZ 85701 3

 U.S. Department of Housing and Urban Development, 451 7th Street, SW, Rm. 8118, Washington, DC

20410 

4

 U.S. Geological Survey, 3020 State University Drive East, Suite 4003, Sacramento, CA 95826, deceased 

i
Abstract

The U.S. Department of Housing and Urban Development (HUD) and the U.S. Geological 

Survey (USGS) have developed a joint project to create Internet-enabled geographic information 

systems (GIS) that will help cities along the United States–Mexico border deal with issues related 

to colonias. HUD defines colonias as rural neighborhoods in the United States–Mexico border 

region that lack adequate infrastructure or housing and other basic services. They typically have 

high poverty rates that make it difficult for residents to pay for roads, sanitary water and sewer 

systems, decent housing, street lighting, and other services through assessment. Many Federal 

agencies recognize colonias designations and provide funding assistance. 

It is the intention of this project to empower Arizona–Sonora borderland neighborhoods 

and community members by recognizing them as colonias. This recognition will result in eligibility 

for available economic subsidies and accessibility to geospatial tools and information for urban 

planning. The steps to achieve this goal include delineation of colonia-like neighborhoods, 

identification of their urbanization over time, development of geospatial databases describing their 

infrastructure, and establishment of a framework for distributing Web-based GIS decision support 

systems. A combination of imagery and infrastructure information was used to help delineate 

colonia boundaries. A land-use change analysis, focused on urbanization in the cities over a 30-

year timeframe, was implemented. The results of this project are being served over the Internet, 

providing data to the public as well as to participating agencies. 

One of the initial study areas for this project was the City of Douglas, Ariz., and its 

Mexican sister-city Agua Prieta, Sonora, which are described herein. Because of its location on 

the border, this twin-cities area is especially well suited to international manufacturing and 

commerce, which has, in turn, led to an uncontrolled spread of colonias. The USGS worked with 

local organizations in developing the Web-based GIS database. Community involvement 

ensured that the database and map server would meet the current and long-term needs of the 

communities and end users. Partners include Federal agencies, State agencies, county officials, 

town representatives, universities, and youth organizations, as well as interested local advocacy 

groups and individuals. A significant component of this project was development of relationships 

and partnerships in the border towns for facilitating binational approaches to land management. 

 

ii
TABLE OF CONTENTS 

ABSTRACT...................................................................................................................................... II

ACKNOWLEDGMENTS.................................................................................................................VI

STUDY AREA: DOUGLAS, ARIZ., AND AGUA PRIETA, SONORA.............................................. 1

LOCATION........................................................................................................................... 1 

HISTORY (ECONOMY)........................................................................................................... 2 

POPULATION....................................................................................................................... 4 

TOPOGRAPHY ..................................................................................................................... 4 

CLIMATE ............................................................................................................................ 4 

HYDROLOGY ....................................................................................................................... 4 

GIS DATABASE DEVELOPMENT AND COLONIAS GEOGRAPHY ............................................. 7

INTRODUCTION.................................................................................................................... 7 

USER NEEDS ASSESSMENT................................................................................................... 7 

INFRASTRUCTURE................................................................................................................ 8 

COMMUNITY RESOURCES ................................................................................................... 10 

Youth Advocates................................................................................................................... 10

COLONIAS DELINEATION ..................................................................................................... 13 

Procedure ............................................................................................................................. 14

CENSUS........................................................................................................................... 17 

REMOTE SENSING APPLICATIONS AND LAND USE CHANGE .............................................. 21

INTRODUCTION.................................................................................................................. 21 

DATA ACQUISITION ............................................................................................................ 24 

DATA PROCESSING ............................................................................................................ 24 

Registration........................................................................................................................... 24

NORMALIZED DIFFERENCE VEGETATION INDEX (NDVI) PROCESSING......................................... 26 

URBAN EXTENT ................................................................................................................. 27 

Unsupervised Classification.................................................................................................. 27

Assessment .......................................................................................................................... 29

ANALYSIS ......................................................................................................................... 30 

RESULTS ...................................................................................................................................... 35

COLONIAS ........................................................................................................................ 35 

Development......................................................................................................................... 35

Descriptions .......................................................................................................................... 38

WEB-BASED INTERFACE DEVELOPMENT................................................................................ 38 

DELIVERY OF PRODUCT/TRAINING ........................................................................................ 39 

CONCLUSIONS ............................................................................................................................ 40

REFERENCES .............................................................................................................................. 41 

APPENDIX A: LOCAL ORGANIZATIONS REGULARLY CONTACTED..................................... 43 

APPENDIX B: PHOTOGRAPHS OF COLONIAS ......................................................................... 44

iii
APPENDIX C: METADATA GENERATED ACCORDING TO THE FEDERAL GEOGRAPHIC 

DATA COMMITTEE (FGDC) STANDARDS FOR ALL NEW COVERAGES................................ 50

1973 ............................................................................................................................... 50 

1985 ............................................................................................................................... 55 

1995 ............................................................................................................................... 60 

2000 ............................................................................................................................... 65 

COLONIAS IN AGUA PRIETA, SONORA ................................................................................... 70 

WATERLINES IN AGUA PRIETA, SONORA................................................................................ 75 

FLOODZONES IN AGUA PRIETA, SONORA............................................................................... 80 

SEWERLINES IN AGUA PRIETA, SONORA................................................................................ 84 

WELLS IN AGUA PRIETA, SONORA ........................................................................................ 88 

COLONIAS IN DOUGLAS, ARIZ. ............................................................................................. 92 

SEWERLINES- DOUGLAS, ARIZ............................................................................................. 97 

WATERLINES- DOUGLAS, ARIZ........................................................................................... 102 

ATTRACTIONS IN DOUGLAS, ARIZ. ...................................................................................... 107 

LIST OF FIGURES 

FIGURE 1: MAP OF THE STATES OF ARIZONA AND SONORA SHOWING CITIES, MAJOR HIGHWAYS, AND 

RIVER SYSTEMS IN THE VICINITY OF THE CITIES OF DOUGLAS, ARIZ., AND AGUA PRIETA, SONORA. 1 

FIGURE 2: USGS DIGITAL RASTER GRAPHIC (DRG) OF DOWNTOWN DOUGLAS, ARIZ., AND AGUA

PRIETA, SONORA (SCALE 1:100,000). ....................................................................................... 2 

FIGURE 3: COCHISE COUNTY EMPLOYMENT BY SECTOR, 1960 AND 1990 (U.S. BUREAU OF THE 

CENSUS, 1960 AND 1990). ....................................................................................................... 3 

FIGURE 4: LANDSAT SATELLITE IMAGE OVERLAIN WITH TOPOGRAPHIC CONTOURS, STREAMS, AND THE 

INTERNATIONAL BOUNDARY........................................................................................................ 5 

FIGURE 5: VIEW OF THE STREET 5 LOOKING EAST FROM AV. 14 (COCEF/BECC, 1998). .................... 6 

FIGURE 6: FLOOD ZONES LOCATED WITHIN AGUA PRIETA (DERIVED FROM COCEF/BECC, 1998)......... 7 

FIGURE 7: SEWER LINES FROM HOUSES EXTENDING INTO A NEARBY ARROYO (PHOTO BY SILVIA 

VILLALOBOS DE ZUÑIGA)............................................................................................................ 8 

FIGURE 8: WATER TANK IN AGUA PRIETA (PHOTO BY SILVIA VILLALOBOS DE ZUÑIGA). .......................... 9 

FIGURE 9: DIGITIZED INFRASTRUCTURE FOR THE TWIN CITY AREA....................................................... 10 

FIGURE 10: CARLOS DE LA TORRE, DIRECTOR OF PUBLIC WORKS, CITY OF DOUGLAS, PRESENTED 

DEMONSTRATION OF GLOBAL POSITIONING SYSTEM. ................................................................ 12 

FIGURE 11: ARCIMS APPLICATION PORTRAYING ATTRACTION DATABASE CREATED BY YOUTH 

ADVOCATES! AND EXAMPLE OF ACCOMPANYING PHOTOGRAPH. ................................................. 13 

FIGURE 12: DESIGNATED COLONIAS LOCATIONS WITHIN THE COCHISE COUNTY BOUNDARY, IDENTIFIED 

BY USDA RURAL DEVELOPMENT.............................................................................................. 14 

FIGURE 13: DEL CABARGA, COORDINATOR FOR TAKE TO THE HILLS, A NON-PROFIT ORGANIZATION, 

DREW BOUNDARIES OF COLONIAS ON HARD-COPY MAPS. ........................................................... 15 

FIGURE 14: NEWLY DIGITIZED ROADS, SEWER LINES, AND WATER LINES USED TO IDENTIFY COLONIA 

BOUNDARIES. .......................................................................................................................... 16 

FIGURE 15: U.S. CENSUS BLOCKS WITHIN THE NEWLY DELINEATED CITY COLONIAS BOUNDARIES. ....... 17 

FIGURE 16: RENTER-OCCUPIED HOUSING IN COLONIAS...................................................................... 20 

FIGURE 17: PERCENT OF HISPANIC POPULATION IN COLONIAS............................................................ 20 

FIGURE 18: A FLOOR BED SHARED BY 13 BROTHERS AND SISTERS IN ONE FAMILY’S HOUSE IN AGUA

PRIETA (PHOTO BY SILVIA VILLALOBOS DE ZUÑIGA)................................................................... 21 

FIGURE 19: AERIAL PHOTOGRAPH SHOWING DOUGLAS, ARIZ., IN NORTHERN (UPPER) HALF AND AGUA

PRIETA, SONORA, IN THE SOUTHERN (LOWER) HALF, DIVIDED BY THE INTERNATIONAL BORDER. 

PHOTO (1970) DEPICTS SMOKESTACK AND SMOKE TRAILING TO THE NORTH FROM A NOWABANDONED SMELTER. ............................................................................................................ 22 

FIGURE 20: SATELLITE IMAGE TAKEN IN 2001, SHOWING DOUGLAS, ARIZ., IN THE NORTHERN (UPPER) 

HALF AND AGUA PRIETA, SONORA, IN THE SOUTHERN (LOWER) HALF, DIVIDED BY THE 

INTERNATIONAL BORDER.......................................................................................................... 23 

iv
FIGURE 21: LANDSAT DATASETS, REGISTERED AND CLIPPED TO DESCRIBE THE DOUGLAS AND AGUA

PRIETA STUDY AREA (1973, 1985, 1995, AND 2000). THE IMAGES SHOW DOUGLAS, ARIZ., 

(NORTHERN HALF) AND AGUA PRIETA, SONORA, (SOUTHERN HALF); DIVIDED BY THE UNITED 

STATES–MEXICO BORDER. ...................................................................................................... 25 

FIGURE 22: THE ERDAS MODELMAKER WAS EMPLOYED TO ADD THE NUMBER 1 TO ALL VALUES AND THEN 

MULTIPLY BY 100 TO DISPLAY THE PRODUCT OF THE NDVI IN 200 GRAY LEVELS, VIEWABLE BY AN 

8-BIT SYSTEM.......................................................................................................................... 26 

FIGURE 23: VEGETATION LAYER (GREEN) DERIVED FROM CALCULATIONS OF THE NDVI 2000 LANDSAT 

DATASET, OVERLAIN ON DOQQ WITH STREET LINES AND CITY PARKS. ....................................... 27 

FIGURE 24: 1973 ISODATA SET AND REGISTERED ORIGINAL TRUE COLOR WITH URBAN AREA DEFINED IN 

RED. ....................................................................................................................................... 28 

FIGURE 25: 1985 ISODATA SET AND REGISTERED ORIGINAL TRUE COLOR WITH URBAN AREA DEFINED IN 

ORANGE.................................................................................................................................. 28 

FIGURE 26: 1995 ISODATA SET AND REGISTERED ORIGINAL TRUE COLOR WITH URBAN AREA DEFINED IN 

LIGHT GREEN........................................................................................................................... 28 

FIGURE 27: 2000 ISODATA SET AND REGISTERED ORIGINAL TRUE COLOR WITH URBAN AREA DEFINED IN 

BLUE....................................................................................................................................... 29 

FIGURE 28: THE 1995-DERIVED URBAN DATA WERE SUPERIMPOSED ON THE 1996 DOQQ TO ENSURE AN 

ACCURATE PORTRAYAL OF THE BOUNDARY. .............................................................................. 30 

FIGURE 29: THE NLCD PORTRAYING CONDITIONS CIRCA 1992 WAS COMPARED TO THE NEWLY DERIVED 

URBAN BOUNDARY IN 1995. ..................................................................................................... 30 

FIGURE 30: URBAN GROWTH DEPICTED FROM LANDSAT IMAGERY FROM THE YEARS 1973, 1985, 1995, 

AND 2000. .............................................................................................................................. 31 

FIGURE 31: URBAN GROWTH OF THE DOUGLAS/AGUA PRIETA AREA THROUGH THE YEARS PLOTTED ONTO

HILL-SHADED DIGITAL ELEVATION MODELS (DEMS), EXAGGERATED 7 TIMES............................... 32 

FIGURE 32: THE ENTIRE STUDY AREA OF DOUGLAS AND AGUA PRIETA IS INCREASING IN SIZE THROUGH 

TIME. ...................................................................................................................................... 33 

FIGURE 33: URBAN GROWTH BAR CHART DEPICTING ACREAGE IN DOUGLAS, ARIZ., AND AGUA PRIETA, 

SONORA. ................................................................................................................................ 34 

FIGURE 34: X-Y SCATTER PLOT AND LINEAR REGRESSIONS DISPLAYING URBAN GROWTH IN THE AREA OF

DOUGLAS, ARIZ., AND AGUA PRIETA, SONORA, INCLUDING A 10–YEAR FORECAST..................... 35 

FIGURE 35: PIE CHART ILLUSTRATING GROWTH IN THE STUDY AREA. .................................................. 36 

FIGURE 36: URBAN EXTENT INFORMATION WITH COLONIAS, SEWER, AND WATER LINE INFORMATION 

OVERLAIN................................................................................................................................ 37 

FIGURE 37: ARCIMS COLONIAS MAPPING WEBSITE PORTRAYING DATASETS IN DOUGLAS AND AGUA

PRIETA (HTTP://CODD.ART.SRNR.ARIZONA.EDU/COLONIAS)........................................................ 39 

FIGURE 38: COCHISE COMMUNITY COLLEGE, DOUGLAS CAMPUS, “USGS-HUD & GIS TRAINING” SIGN.

.............................................................................................................................................. 40

FIGURE 39: COLONIA DWELLING IN DOUGLAS (PHOTO BY ANGELA J. DONELSON). .............................. 44 

FIGURE 40: THE PIRTLEVILLE COLONIA, OUTSIDE OF DOUGLAS (PHOTO BY ANGELA J. DONELSON). .... 44 

FIGURE 41: TRAILERS COMPRISE SOME COLONIAS IN DOUGLAS (PHOTO BY ANGELA J. DONELSON)..... 45 

FIGURE 42: HOUSES ARE MADE OF VARIOUS MATERIALS IN COLONIA EMPACADORA, AGUA PRIETA 

(PHOTO BY SILVIA VILLALOBOS DE ZUÑIGA). ............................................................................. 45 

FIGURE 43: ONE WOMAN LIVING IN COLONIA EMPACADORA, AGUA PRIETA (PHOTOS BY SILVIA 

VILLALOBOS DE ZUÑIGA).......................................................................................................... 46 

FIGURE 44: HOUSE IN COLONIA SOUTHERN, AGUA PRIETA (PHOTO BY SILVIA VILLALOBOS DE ZUÑIGA).46

FIGURE 45: THIS FAMILY IN COLONIA BACHICUY, AGUA PRIETA IS NOT ENTITLED TO GOVERNMENT 

SUBSIDIES DUE TO OWNERSHIP OF AUTOMOBILE (A LUXURY) (PHOTO BY SILVIA VILLALOBOS DE 

ZUÑIGA).................................................................................................................................. 47 

FIGURE 46: HOUSE WITH WATER TANK IN COLONIA BACHICUY, AGUA PRIETA (PHOTO BY SILVIA 

VILLALOBOS DE ZUÑIGA).......................................................................................................... 47 

FIGURE 47: COLONIA LADRILLERA, AGUA PRIETA (PHOTO BY SILVIA VILLALOBOS DE ZUÑIGA)............. 48 

FIGURE 48: MATERIALS FOR HOUSES IN COLONIA PUEBLO NUEVO, AGUA PRIETA ARE MAKESHIFT (PHOTO 

BY SILVIA VILLALOBOS DE ZUÑIGA)........................................................................................... 48 

FIGURE 49: CARDBOARD ROOFING TYPICAL IN COLONIA OF AGUA PRIETA (PHOTO BY SILVIA VILLALOBOS 

DE ZUÑIGA)............................................................................................................................. 49 

v
LIST OF TABLES

TABLE 1: IMPORTANT ATTRACTIONS IDENTIFIED BY YOUTH ADVOCATES! ............................................ 11 

TABLE 2: ALL U.S. CENSUS DATA SUMMARIZED BY COLONIA BOUNDARY............................................ 18 

TABLE 3: ZONAL STATISTICS OF URBAN GROWTH THROUGH TIME........................................................ 32 

TABLE 4: ZONAL STATISTICS OF THE URBAN EXTENT CALCULATED BY INDIVIDUAL LOCATION................. 34 

 

Acknowledgments

The authors wish to thank William Acevedo, Karen Bolm, Jean Parcher, and Sean Stone 

of the U.S. Geological Survey, for their extremely helpful reviews of this material. 

vi
Study Area: Douglas, Ariz., and Agua Prieta, Sonora

Location 

The City of Douglas is located in Cochise County, Ariz., on the United States–Mexico 

border (fig.1). 

Figure 1: Map of the States of Arizona and Sonora showing cities, major highways, and river 

systems in the vicinity of the Cities of Douglas, Ariz., and Agua Prieta, Sonora.

1
The City of Douglas is located 118 miles southeast of Tucson, 74 miles from Interstate 10 

via Highway 191 (or 80). The unincorporated community of Pirtleville is located just northwest of 

Douglas. Because of its location on the Mexican border, Douglas is especially well suited to 

international manufacture and commerce; businesses based in Douglas benefit from the 

maquiladora (twin-plant) concept by utilizing the labor force of its Mexican companion city, Agua 

Prieta (fig. 2). 

Figure 2: USGS Digital Raster Graphic (DRG) of downtown Douglas, Ariz., and Agua Prieta, 

Sonora (Scale 1:100,000).

History (Economy)

To understand the Douglas–Agua Prieta border history, long-established patterns of rural 

economic underdevelopment must be examined. With the arrival of the Southern Pacific Railroad 

in the 1880s, Arizona, in the minds of many east-coast financiers, acquired a “civilized” mode of 

transportation (Trennert, 1988). The construction and financing of the railroad was a bi-national 

United States and Mexican effort, which largely sought to extract and transport copper and 

mineral deposits in the Arizona–Sonora region (Myrick, 1967). Transportation of copper became 

financially feasible with the completion of the railroad. 

The founding of the City of Agua Prieta dates to 1899, two years before the construction 

of the highway “Douglas Arizona - Mineral of Nacozari of Garcia,” which was built to connect the 

mines in Mexico with the United States markets. Douglas was founded in 1900 as a coppersmelting center. Shortly thereafter, in 1901, two large mining interests—Phelps Dodge and the 

Calumet and Arizona—built smelters in Douglas. By 1903, Douglas was served daily by 19 

freight and 12 passenger trains (Martynec and others, 1994). Agua Prieta served as a point of 

crossing at the border and as a transit stop for transporting mining products. The area where the 

Agua Prieta is currently located used to be an Indian ranch known as Bachicul. Over time, the 

2
Mexican population moved to the border area, and concentrated in several blocks around the 

railroad. In the following decades, Agua Prieta grew in a reticular fashion, its boundaries 

reaching the United States border in the north and the Agua Prieta River in the west. On August 

28, 1916, the area was designated a village and on November 11, 1942, it was made a city 

(INEGI, 1995). 

Between 1880-1890, ranchers increased cattle operations from 400,000 head to nearly 

one million head (Seltzer, 1959). By the 1920s, farming was well established in the border region, 

assisted by federally subsidized irrigation technology (Kearney, 1995). The Arizona cattle industry 

similarly enjoyed a period of expansion. In Arizona, range cattle became especially important to 

the Cochise County economy and by the 1950s, beef cattle were the second most important 

agricultural industry in the state, after cotton (Kent, 1983). Arizona agriculture both served and 

expanded the economic base developed by the mining industry and the railroads. Agriculture in 

the Arizona border region depended largely on Mexican low-cost labor (Weaver, 2001). 

The late 1950s and early 1960s marked a profound change in the economic base of the 

entire Arizona economy. In southern Arizona, employment in mining and agriculture declined 

significantly and was succeeded by a service economy. The Bracero program that had previously 

brought millions of Mexican farm laborers to work the agricultural fields of America was 

terminated. Mechanization of agriculture eliminated the need for many of the workers required in 

the past and the end of the Bracero program stopped importation of low-cost Mexican labor. In an 

effort to offset some of the massive unemployment, the Mexican government launched the 

Programa Nacional Fronterizo (or PRONAF, the National Border Program) in 1961 to promote 

tourism and, soon after, the Border Industrialization Program (BIP) in 1965. The BIP especially 

helped spur much larger-scale development on the Mexican side of the border through incentives 

for establishing twin plant manufacturing operations, or maquiladoras. The ability to send parts 

and raw materials to Mexico, and obtain finished goods duty-free, prompted maquiladora

operators to set up small-scale United States operations on the Arizona side of the border, with 

larger Mexican assembly operations on the Sonoran side. 

Because of the copper industry and agriculture, the economy of this nonmetropolitan 

area continued to grow in the early 1900s. Yet, a decline in the southern Arizona mining industry 

manifested itself fully in the 1970s. Today the entire region is transitioning from the copper and 

cattle industries of the past to modern manufacturing in bonded assembly plants, as well as to 

tourism. The increase in manufacturing and tourism has generated increased migration of 

Mexican citizens from other regions of Sonora. Population growth of the twin city area has 

created a new workforce in public administration and service industries (fig. 3) to accommodate 

these people. 

0.0%

5.0%

10.0%

15.0%

20.0%

percent of workforce

1960 9.0% 11.5% 8.7% 12.7% 9.4%

1990 3.9% 1.0% 6.6% 17.1% 18.1%

agriculture mining manufact. pub admin service

Figure 3: Cochise County employment by sector, 1960 and 1990 (U.S. Bureau of the Census, 

1960 and 1990).

Beginning in the 1960s, with the implementation of the North American Free Trade 

Agreement (NAFTA), the maquiladora industry has focused much attention on the border and is 

3
most renown for the big boom in the 1980s. In 2001, however, this industry suffered a serious 

decline in employment. While there is continued investment in manufacturing, particularly in the 

border areas (Cañas and Coronado, 2002), the decline in employment can be attributed to the

recent interest in other foreign markets, such as China. This suggests that the border economy 

will once again need to re-invent itself to accommodate future economic directions. 

Population 

The City of Douglas is predominantly comprised of Hispanic families who have resided in 

the United States for generations. The average family size is 20 percent higher than the United 

States average and the median age is 28 years. The population of Douglas in 2001 was 21,336 

people, comprising 6,117 households (http://www.infods.com/freedata). Median household 

income in Douglas is $26,490, versus the nationwide average of $41,369 

(http://www.infods.com/freedata/), and the poverty rate, according to census information, is 55 

percent (http://www.ezec.gov/ezec/Ariz./border.html). 

The population for the City of Agua Prieta and its suburbs has been calculated in many 

different ways by INEGI, the National Counsel of Population (CONAPO), and the General 

Censuses of Population and Dwelling carried out by the federal government in Mexico. 

Depending on the urban growth rate used, current population estimates range from 112,000 to 

132,000 within the city limits to 173,000 to 185,000 including the suburbs (COCEF/BECC, 1998). 

Topography

Douglas and Agua Prieta are located within the Whitewater International Watershed. The 

elevation of the cities is about 3,990 feet or approximately 1,200 meters (fig. 4). The Mule 

Mountains are located to the west, the Swisshelm and Perilla Ranges are to the east, and the 

Chiricahuas are north. 

Climate 

The high desert climate of the twin city area provides 320 sunny days a year and an 

annual total rainfall of 13.05 inches, with the majority of the rain falling during the "monsoon" 

season in July and August. The average daily high temperature is 79.2oF and the average low is 

44.4oF. 

Hydrology 

The name “Douglas” is from the Gaelic meaning “Dark River” or “Blood River”. Prior to 

the first settlement, the name “Agua Prieta” was used by cattlemen and Indians to describe the 

cloudy water of the river. The Agua Prieta headwaters lie in the United States, at an altitude of 

2,450 m., in the Chiricahua Mountains, 50 km north of Douglas and Agua Prieta. At its upper 

end, it is named Ash Creek and drains generally west, changing course to the south and 

southeast, where the name changes to Whitewater Draw. At the border, the name changes 

again to Agua Prieta (fig. 4). Alluvial deposits form the aquifer, which supplies water to the City of 

Agua Prieta. The water is primarily used for domestic, farm, commercial, and industrial purposes 

(COCEF/BECC, 1998). 

 

4
Figure 4: Landsat satellite image overlain with topographic contours, streams, and the 

international boundary.

Given the relatively flat terrain, Agua Prieta is prone to flooding in the summer rains (fig. 5). The 

flood zones are located in the southwest, in proximity to the River Agua Prieta, and in the 

southeast (fig. 6), where a residential area is located. 

5
Figure 5: View of the Street 5 looking east from Av. 14 (COCEF/BECC, 1998).

6
Figure 6: Flood zones located within Agua Prieta (derived from COCEF/BECC, 1998).

GIS Database Development and Colonias Geography

Introduction 

The purpose of this project was to make available relevant geospatial datasets, with a 

focus on infrastructure, such as sewer lines, water lines, and housing elements, for ease in 

delineation and further servicing of those colonias in need of funding or support. A robust GIS 

database requires the compilation of many datasets, including transportation, hydrography, 

topography, census data, and urban extents (Crawford and others, 1996). 

User Needs Assessment 

The first task was to meet with HUD representatives to discuss user needs. The second 

task was to establish contacts with local representatives and interested parties to exchange 

information and to collaborate on the desired end product. In-depth field analysis, onsite 

meetings, and discussions with local collaborators were conducted in the design and 

development phase of this bi-national digital dataset. 

7
A list of local organizations was complied for the area (Appendix A) and representatives 

from these organizations were invited to a meeting on December 12, 2002, in Douglas, Ariz. A 

user needs assessment, defining the suggested planning tools that were identified, was 

developed. 

Infrastructure 

Infrastructure data acquired from the City of Douglas Public Works Department were in 

AutoCAD format, and contained the locations of sewer and water lines in relation to streets in 

Douglas, Ariz. These data were digitized through the means of dead reckoning in Arc View 3.3, 

onto Digital Orthophoto Quarter Quadrangles (DOQQs). 

Silvia Villalobos de Zuñiga captured some photographic examples of Agua Prieta’s 

current makeshift infrastructure systems (figs. 7- 8). Infrastructure data gathered by 

COCEF/BECC (1998) for the master plan of Agua Prieta was systematically translated and 

synthesized. AutoCAD drawings describing the area were rectified and digitized within a GIS. 

According to the report submitted by the U.S. Army Corps of Engineers, the potable water 

infrastructure of the City of Douglas consists of tubing ranging from 3 to 18 inches in diameter, 10 

active wells, 4 abandoned wells, 4 storage tanks, and a pressure station (COCEF/BECC, 1998). 

Geographic features describing the sewer and water lines in the twin cities were 

automated into the geospatial database (fig. 9). 

Figure 7: Sewer lines from houses extending into a nearby arroyo (photo by Silvia Villalobos de 

Zuñiga).

8
Figure 8: Water tank in Agua Prieta (photo by Silvia Villalobos de Zuñiga).

9
Figure 9: Digitized infrastructure for the twin city area.

Community Resources 

For reference and potential planning, the location of community attractions was 

considered to be an important dataset for this project. Many citizens and especially local 

businesses expressed a desire to have their city’s featured resources searchable via the Internet. 

Youth Advocates

The Southeast Arizona Health Behavioral Services (SEAHBS) sponsors a group called 

the New Turf/ Youth Advocates, which is comprised of about 20 high-school-aged young adults 

and mentored by Ana Maria Flannigan. A "photo-points" project for the twin cities was designed 

and implemented by the youth group in four phases: 

1. Identification of important attractions in their community. These included a new 

skate park, community pools, and soccer fields (see table 1). 

10
2. Documentation of these sites throughout the city using a digital camera. 

3. Association of the locations of the resources with the photographs using Global 

Positioning System (GPS) readings and map coordinates. Carlos de la Torre, 

Director of Public Works, City of Douglas, instructed the youth group on using a 

Trimble 4700-4800 GPS system (fig. 10). 

4. Incorporation of this information into the GIS database. The data can be viewed 

at the Web site by clicking on a point on a map and opening the corresponding 

photograph taken by the youths (fig. 11). 

Table 1: Important attractions identified by Youth Advocates! 

ID NAME ADDRESS PHONE

1 Grand Theatre 1139 N G Ave 520-364-6144 

2 Douglas Aquatic Center 1551 East 15th St. 520-364-8846 

3 Coronado Courts 1830 Bonita Ave. 520-364-4637 

4 15th Street Park 1200 15th St. 

5 Veteran's Memorial Park 1500 8th Street 

6 Douglas Unified School District 1600 North Louis 520-805-0712 

7 Gadsden Hotel 1046 North G Ave. 520-364-4481 

8 Giggles 1801 East 9th St. 520-364-8397 

9 Huber Middle School 15th and Washing 520-364-2840 

10 

 Immaculate Conception 

Catholic Church 928 C Ave. 520-364-8494 

11 Douglas Library 560 East 10th St. 520-364-3851 

12 LM's Body Builders 1012 North G Ave. 520-364- 3996 

13 McDonald's of Douglas 104 East 5th St. 520-364-8388 

14 Douglas Cinema 520-364-5000 

15 Douglas Police Department 300 East 14th St. 520-364-8422 

16 Post Office 601 East 10th St. 520-364-3621 

17 The Williams House 1001 D Ave. 520-364-7370 

18 Port of Entry 1 N. Pan America 

19 Pachanga's Agua Prieta 

20 Raul Castro Park 10th St. 

21 Skate Park 

22 Health Department 315 E. 7th St. 

23 Walmart 204 W. 5th St. 

24 Safeway 90 5th St. 

25 Four Churches Square 

11
Figure 10: Carlos de la Torre, Director of Public Works, City of Douglas, presented 

demonstration of Global Positioning System.

12
Figure 11: ArcIMS application portraying attraction database created by Youth Advocates! and 

example of accompanying photograph.

Colonias Delineation 

Colonias were defined by the Cranston–Gonzales Act of 1990 as rural communities and 

neighborhoods located within 150 miles of the United States–Mexican border and that lack 

adequate infrastructure (sewer or water lines) and/or housing. Some colonias may be entire 

border communities, while others are comprised of neighborhoods within incorporated 

communities (http://www.hud.gov/groups/frmwrkcoln/whatcol.cfm). 

There was only one known ‘colonias’ geospatial dataset describing the study area, which 

is based on specific U.S. Department of Agriculture (USDA) rural development colonias 

definitions generated for Cochise County, and does not incorporate Douglas proper (fig. 12). The 

City of Douglas declared itself a colonia in 1996 as Resolution No. 96-132, under the State 

Community Development Block Grant Program, pursuant to the Housing and Community 

Development Act of 1974, as amended, Section 916. However, the USDA rural development 

does not recognize this area for colonia funding (USDA: 306C) because its population exceeds 

the stated limit of 10,000 people. So, while it qualifies as an area lacking sewer lines, water lines, 

or adequate housing structures, it does not meet the requirements to receive available colonia 

funding. 

13
Figure 12: Designated colonias locations within the Cochise County boundary, identified by 

USDA rural development.

Many states take advantage of the available colonia funding sources by designating all 

areas fitting the legal description of a colonia. According to studies implemented by the U.S. 

Census Bureau, the State of Texas recognizes 1,821 colonias whose average population is 1,336 

and the State of Arizona recognizes 182, whose average population is 2,871. It is suggested that 

this discrepancy may be explained by the greater resolutions with which the Census Designated 

Places (CDPs) were designated by the officials in Texas (that is, Texas Attorney General’s 

Office), working with Census Bureau staff, prior to Census 2000 (Ratcliffe, 2003). This results in 

many areas of Texas, which lack adequate housing or infrastructure, qualifying for funding 

opportunities made available to recognized colonias. Therefore, for this project, the USGS 

identified smaller, colonia-like neighborhoods within incorporated communities of selected 

Arizona borderlands to be recognized as colonias in the future, thereby competing for some of 

those funds. 

With the help of local officials, citizens, and hard-copy city land-use maps, the 

delineations were approximated, automated, and incorporated into the database. The integration 

of spatial and demographic data from a variety of sources allowed for accurate depictions of 

colonias populations. Geospatial and digital data describing infrastructure (City of Douglas 

Department of Public Works) and census information (U.S. Census Bureau and others) helped to 

delineate neighborhood-style colonias that exist within the city itself. Some of these data were 

available as hard-copy maps or in AutoCAD format and needed to be digitized. All data created 

by the USGS have metadata generated to describe their source, scale, and other pertinent 

information required by the Federal Geographic Data Committee (FGDC) standards (Appendix 

B). 

Procedure

14
Using a suitability–capability analysis (SCA) originally described by McHarg (1969), 

neighborhoods were systematically designated as colonias in this study. The SCA was based on 

community member assessments of the housing suitability and/or infrastructure capability of a 

neighborhood, using the newly digitized sewer and water lines in concert with street maps and 

prior knowledge, to pinpoint known colonia boundaries. For example, an area was deemed a 

colonia if the area’s housing conditions were identified as inadequate (suitability ranking) and/or 

whether or not the area had access to infrastructure (that is, capability to access sewer or water 

lines). Those areas previously recognized by agencies, including the USDA, FONAVIT, and 

FOVISTE, were also delineated and identified as colonias in this study. 

Chuck Ebner (Assistant Director, Department of Public Works, City of Douglas), Rosael 

Torres (Housing Authority, City of Douglas), Carlos de la Torre (Director, Department of Public 

Works, City of Douglas), and Carol Huddleston (head of Turning Point, a non-profit local 

organization) helped to identify the poorest neighborhoods in the City of Douglas to designate as 

colonias for this project. 

In the City of Agua Prieta, Silvia Villalobos de Zuñiga (Director of Agua Prieta's National 

System for the Integral Development of the Family (DIF) and sister to the Mayor of Agua Prieta, 

Irma Villalobos de Terán); Del Cabarga (dual citizen and coordinator for Take to the Hills, a nonprofit organization), and Reverend Jesus Gallegos (minister at Lily of the Valley Presbyterian 

Church in Agua Prieta, Mexican affiliate of the Frontera de Cristo border ministry), identified the 

poorest neighborhoods (barrios pobres) to designate colonias for this project. 

Figure 13: Del Cabarga, Coordinator for Take to the Hills, a non-profit organization, drew 

boundaries of colonias on hard-copy maps.

Approximations were based upon previous knowledge and familiarity with the most 

impoverished and underprivileged areas known to the city at that time. The polygon boundaries 

were then digitized and attributed (fig. 14). 

15
Figure 14: Newly digitized roads, sewer lines, and water lines used to identify colonia boundaries.
Census 

The U.S. Census GIS data were imported (fig. 15) and clipped to the colonia boundaries 

of Douglas, Ariz., to accurately describe the population (see figure 16 and table 2) and housing 

elements (fig. 17) within these polygonal features. 

Figure 15: U.S. Census blocks within the newly delineated city colonias boundaries.

17
Table 2: All U.S. Census data summarized by colonia boundary.

Census data Pirtleville PasatiempoNorthwest Musgrave Fairview

Census

Tract 9 

Bay

Acres Sunnyside

Douglas

Terrace

Count 44 4 12 23 9 205 13 23 11

Population 

2000 969 45 927 474 99 6759 878 510 411

White 534 37 464 343 48 4282 464 350 234

Black or 

african 

american 9 0 5 2 0 45 0 0 1

American 

indian and 

alaska native 10 0 4 0 0 40 3 6 0

Asian 7 0 0 0 0 23 0 2 4

Native

hawaiian and 

other pacific 

islander 0 0 0 5 4 5 0 2 0

Other 385 8 410 111 43 2156 376 145 165

2 or more 

races 24 0 44 13 4 208 35 5 7

Hispanic 920 20 837 415 93 6170 811 401 368

Males 478 24 432 231 53 3133 442 258 194

Females 491 21 495 243 46 3626 436 252 217

Age under 5 72 4 135 26 20 608 86 43 37

Age 5–17 250 13 272 134 22 1631 274 136 109

Age 18–21 69 1 73 26 11 451 62 37 21

Age 22–29 85 0 126 36 11 617 95 50 42

Age 30–39 113 6 116 67 20 724 135 77 47

Age 40–49 116 5 100 69 8 792 98 57 63

Age 50–64 156 10 67 73 4 862 74 64 60

Age 65 & up 108 6 38 43 3 1074 54 46 32

Median age 32 43 20 30 15 30 23 29 27

Median age, 

males 29 35 17 33 16 28 20 28 27

Median age, 

females 35 44 23 29 12 32 25 30 29

Households 296 16 287 149 23 2206 241 162 124

Average 

household 

size 3 3 3 3 3 3 3 3 2

1-person 

household, 

male 18 1 22 15 2 230 22 9 7

1-person 

household, 

female 41 3 27 14 0 292 13 12 8

Marriedcouple w/ 

own children 88 6 93 41 12 508 100 52 46

18
under 18 yrs 

Marriedcouple, no 

own children 

under 18 yrs 74 4 30 36 4 480 43 37 35

Male 

householder,

no wife 

present, w/

own children 

under 18 yrs 7 1 10 8 2 58 14 7 3

Female 

householder,

no husband 

present, w/

own children 

under 18 yrs 19 0 78 17 2 280 26 22 11

Families 232 12 231 118 21 1629 202 137 107

Average 

family size 4 3 3 3 3 3 3 3 3

Housing 

units 349 18 317 171 30 2629 276 208 132

Housing 

units, urban 0 0 0 0 0 0 0 0 0

Housing 

units, rural 0 0 0 0 0 0 0 0 0

Housing 

units, vacant 53 2 30 22 7 423 35 46 8

Housing 

units, owner 

occupied 262 15 123 107 19 1242 170 108 105

Housing 

units, renter 

occupied 34 1 164 42 4 964 71 54 19

Using the derived dataset, it is possible to estimate housing elements. For example, the 

renter-occupied attribute was averaged and plotted to examine the relationship of rented vs. 

owner-occupied units in the colonias (fig. 16). 

19
Figure 16: Renter-occupied housing in colonias.

It is generally assumed that most colonias are predominantly Hispanic (Ratcliffe, 2003), 

yet one of the seven defined in this study (Pasatiempo) is less than 50 percent Hispanic, see 

Figure 17. 

Figure 17: Percent of Hispanic population in colonias.

20
These types of comparisons help to illustrate the changing environment along the United 

States–Mexico border by applying hard analysis to quantify population and characterize the 

colonias. 

Census information in Agua Prieta was not available. The housing conditions were 

defined solely through visual analysis. Photographs by Sylvia Villabolos de Zuniga visually 

describe the conditions of some poor neighborhoods in Agua Prieta (fig. 18). 

Figure 18: A floor bed shared by 13 brothers and sisters in one family’s house in Agua Prieta 

(photo by Silvia Villalobos de Zuñiga).

Remote Sensing Applications and Land Use Change 

Introduction 

Urbanization is monitored to estimate populations, predict and plan direction of urban 

growth for development purposes, and to help monitor adjacent environmentally sensitive or 

riparian areas (Forney and others, 2001; Lee and Marsh, 1995). Many studies aim to depict land 

use change using remote sensing technologies (Shan, 1999; Jensen and others, 1995; Acevedo 

and others, 1999; Eastman and Fulk, 1993; Howarth, 1986; Jensen and Toll, 1982; Haack and 

others, 1987; Kirkland and others, 1994; Mack and others, 1995). Remote sensing and 

photogrammetric technology aid in describing international borders by helping analysts create 

seamless maps of features apparent on the Earth’s surface while disregarding anthropogenic 

boundaries (Brady and others, 2002; Osborn, 1998). 

The City of Douglas provided imagery (figs. 19-20), which shows that the urban extent of 

the twin city area had changed over the years. Temporal image processing and analysis was 

performed to quantify urban growth stemming from human settlement. A time-series change 

analysis from 1973 to 2000 was performed to identify recently developed areas. 

21
Figure 19: Aerial photograph showing Douglas, Ariz., in northern (upper) half and Agua Prieta, 

Sonora, in the southern (lower) half, divided by the international border. Photo (1970) depicts 

smokestack and smoke trailing to the north from a now-abandoned smelter. 

22
Figure 20: Satellite image taken in 2001, showing Douglas, Ariz., in the northern (upper) half 

and Agua Prieta, Sonora, in the southern (lower) half, divided by the international border.

Image interpretation and analysis required acquisition and processing of Landsat 

imagery, their georectification, and classification of urban and residential land use. These data 

were then used to produce maps of the past and current urban extent in the region. Because the 

classification value of urban extent is subject to the analyst’s decision rules during the urban 

mapping process, the numbers listed in this study are approximations. 

Software products used for this study include Erdas Imagine 8.5; ESRI ArcMap, ArcInfo 

8.2 and it’s GRID module, Arc View 3.3 and the extensions Spatial Analyst, 3D Analyst, Grids and 

Graticules, Geoprocessing, Microsoft Word, and Photo Editor. Hardware required a minimum of 

2GB for data storage. Information on the World Wide Web was also accessed. 

Identification of features using remotely sensed data involves use of computer software 

with the ability to identify pixels based upon their spectral reflection properties and to analyze 

pixels for statistical estimates. The Normalized Difference Vegetation Index (NDVI) was 

calculated from each of the data sets to derive estimates of vegetation. Clustering methods, 

23
called unsupervised classification procedures, were applied to determine the location of the 

spectral classes into which the pixels of urban definition are assigned. 

Data Acquisition 

The Arizona Regional Image Archive http://aria.arizona.edu is an online interdisciplinary 

resource system for digital image and map data for the Sonoran desert region, including the 

southwest region of the United States and northern Mexico. This source provides geospatial data 

via an interactive map that can be downloaded over the Internet. 

Datasets were acquired from this website and included USGS products (DOQQs, DRGs, 

and Digital Elevation Models (DEMs), as well as Landsat satellite imagery. Landsat imagery of 

the Douglas, Ariz., and Agua Prieta, Sonora, area (Path 35 Row 38) was acquired for 

06/04/1973, 06/06/1985, 06/18/1995, and 04/05/2000. The acquisition dates of the Landsat data 

were deemed appropriate because the angle of the sun was approximately the same on the four 

dates. 

Although the satellite data were all acquired from Landsat systems, different sensors 

were utilized through the years, which may result in some discrepancy during analysis. The 

Landsat-1 satellite acquired the MSS imagery for 1973 at a 79-m resolution. Landsat-5 TM 

sensor acquired TM data in 1985 and 1995 at a 30-m resolution. And the Landsat-7 Enhanced 

Thematic Mapper Plus (ETM+) data was acquired at 30-m resolution in 2000. 

Data Processing 

Registration

Geometric distortions were corrected by establishing a relationship between the satellite image 

and 1996 USGS DOQQ of the corresponding regions. Once the ground control points (GCPs) 

were established, the image was converted, or rubber sheeted, to the new coordinate system 

through a nearest neighbor resampling regime using a 3rd-order polynomial through a process 

called rectification. The newly registered data were then checked for accuracy through the 

process of overlay analysis. Each image was subset, registered, and clipped to the same 

bounding coordinates (fig. 21). 

24
Figure 21: Landsat datasets, registered and clipped to describe the Douglas and Agua Prieta study area (1973, 1985, 199

images show Douglas, Ariz., (northern half) and Agua Prieta, Sonora, (southern half); divided by the United States–Mexico 
Normalized Difference Vegetation Index (NDVI) Processing 

NDVI was calculated for each of the Landsat data sets. To quantify the density of plant growth, 

NDVI uses the near-infrared radiation (NIR) minus the visible radiation of the red band (RED) 

divided by NIR plus RED. Written mathematically, the formula is: 

NDVI = (NIR — RED)/(NIR + RED) 

As indicated, due to changes in the sensors through the years, band number and width vary and, 

hence, comparison of the resulting datasets can be problematic and requires normalization. 

Calculations of NDVI for a given pixel always result in a number that ranges from minus one (-1) 

to plus one (+1). To display the result of this formula, the Erdas Modelmaker (fig. 22) was 

employed to complete the following stretch: the addition of the number 1 to all pixel values, to 

readjust the scale from (–1 to +1) to (0 to 2) and subsequent multiplication of all pixel values by 

100 to create an 8-bit gray-level image. 

Figure 22: The Erdas Modelmaker was employed to add the number 1 to all values and then 

multiply by 100 to display the product of the NDVI in 200 gray levels, viewable by an 8-bit system.

The NDVI values were divided into three classes using quantile sampling. The lower two 

classes were masked out to create a coverage of high vegetation, compared with the location of 

known city parks and streets in Douglas, and draped over a DOQQ (fig. 23). 

Examination of the NDVI dataset shows evidence that the City of Douglas is much more 

vegetated than the City of Agua Prieta. The vegetation in Douglas is apparent in golf courses, 

city parks, and residential yards. Agua Prieta, on the other hand, is very scarce in vegetation 

throughout the urban area, except for the area just west of the city, where dense vegetation due 

to agriculture is clustered around the river that drains the sewage treatment plant. 

26
Figure 23: Vegetation layer (green) derived from calculations of the NDVI 2000 Landsat dataset, 

overlain on DOQQ with street lines and city parks.

Urban Extent 

Unsupervised Classification

Datasets were systematically run through the Erdas Imagine isodata algorithm, using 6 iterations 

each, creating signature sets and imagery categorized into 20 classes. The isodata-clustering 

algorithm uses the minimum spectral distance formula to form clusters, beginning with arbitrary 

cluster means. Classes correspond to spectral signatures of dominant land use and land cover 

types. Signatures that appeared to be urban areas were isolated for future analysis. 

Using the vegetation layer, isodata classifications, and registered original true-color 

Landsat imagery, the urban areas were identified and manually digitized at a 1:25,000 scale for 

each year of interest (figs. 24-27). 

27
Figure 24: 1973 isodata set and registered original true color with urban area defined in red. 

Figure 25: 1985 isodata set and registered original true color with urban area defined in orange. 

Figure 26: 1995 isodata set and registered original true color with urban area defined in light 

green.

28
Figure 27: 2000 isodata set and registered original true color with urban area defined in blue. 

Assessment

A visual verification was performed on the urban area delineated in 1995 by overlaying the 

polygon on the 1-m-resolution DOQQ captured in 1996 (fig. 28). This determined that an 

accurate depiction of urban extent had been calculated. 

29
Figure 28: The 1995-derived urban data were superimposed on the 1996 DOQQ to ensure an 

accurate portrayal of the boundary.

The National Land Classification Dataset (NLCD) from 1992 was also compared to the 

1995-derived data (fig. 29) as another qualitative comparison. This confirmed that the urban area 

estimated by derivation in this study was accurate. 

City of Douglas, Arizona 

Urban Sprawl Estimates (1995) 

vs. NLCD (Early 1990s)

Figure 29: The NLCD portraying conditions circa 1992 was compared to the newly derived urban 

boundary in 1995.

Analysis 

The results of quantification of the urban extent are presented in geospatial datasets that 

can be compared with other GIS information describing the city. This will provide graphical 

analysis of urban growth over time, in relation to development of infrastructure and colonias. The 

urban boundary vector files were converted to raster grids for statistical operations available in 

GIS software. These GRIDS are displayed under a USGS DRG and indicate rapid urban growth 

in Agua Prieta, Sonora, as well as some growth in Douglas, Ariz. (fig. 30). The DRG helps to 

identify cultural features on the ground. 

30
Figure 30: Urban growth depicted from Landsat imagery from the years 1973, 1985, 1995, and 

2000. 

Land-use change studies historically demonstrate urban growth in a time-series portrayal overlain 

on DEMs (Acevedo and others, 1999). Due to the extremely flat terrain in the study area (fig. 4), 

it was necessary to calculate a vertical exaggeration in the portrayal of the DEM to create a 3-D 

perspective and to examine growth in relationship to topographic features (fig. 31). This 

demonstrates that the topography in the area is not a factor that may hinder further development. 

31
Figure 31: Urban growth of the Douglas/Agua Prieta area through the years plotted onto 

hill-shaded digital elevation models (DEMs), exaggerated 7 times. 

After the conversion of these urban growth boundaries from vector to raster, zonal functions can 

be performed, including calculations of area (table 3), which can be plotted to examine 

relationships (fig. 32). 

Table 3: Zonal statistics of urban growth through time.

Dataset # Pixels Square Meters Acres Hectares Square Miles 

1973 16,381 14,742,900 3,643 1,474 5.69

1985 22,153 19,937,700 4,927 1,994 7.70

1995 28,369 25,532,100 6,309 2,553 9.86

2000 31,952 28,756,800 7,106 2,876 11.10

32
 Urban Area

y = 127.74x - 248484

R2

 = 0.9933

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

8,000

9,000

1970 1975 1980 1985 1990 1995 2000 2005 2010

Year

Acres

Figure 32: The entire study area of Douglas and Agua Prieta is increasing in size through time. 

If growth continues in this steady climb (fig. 32), the estimated urban area in 2010 would 

be about 8,200 acres, which represents a 14 percent increase from 2000. 

Datasets were divided at the international border to compare growth on either side (see 

fig. 33 -34 and table 4). It is apparent that the City of Douglas is growing more slowly than the 

City of Agua Prieta. Figures 33 and 34 suggest that the urban extent of the City of Douglas 

actually declined in size between 1995 and 2000, an unlikely scenario. This apparent decline 

may be explained by changes in interpretation of the area west of the city. Originally this area 

was classified as urban, but as growth continued, the area was subsequently interpreted as a 

factory and not residential. 

33
Table 4: Zonal statistics of the urban extent calculated by individual location.

Douglas Pixels M^2 Acres Hectares

1973 9564 8,607,600 2,126.98 860.76

1985 10629 9,566,100 2,363.83 956.61

1995 12753 11,477,700 2,836.20 1,147.77

2000 12592 11,332,800 2,800.40 1,133.28

Agua Prieta 

1973 6844 6,159,600 1,522.07 615.96

1985 11561 10,404,900 2,571.11 1,040.49

1995 15062 13,555,800 3,349.71 1,355.58

2000 16930 15,237,000 3,765.14 1,523.70

0

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

Acres

1973 2127 1522

1985 2364 2571

1995 2836 3350

2000 2800 3765

Douglas, Arizona Agua Prieta, Sonora 

Figure 33: Urban growth bar chart depicting acreage in Douglas, Ariz., and Agua Prieta, Sonora. 

34
Douglas, Arizona, U.S. & Agua Prieta, Sonora, Mexico 

Urban Growth Comparison & Forecast

y = 27.956x - 53051

R2

 = 0.9345

y = 82.679x - 161585

R2

 = 0.9993

0

1,000

2,000

3,000

4,000

5,000

1965 1975 1985 1995 2005 2015

Year

Acres

Douglas

Agua Prieta

Douglas, Arizona, and Agua Prieta, Sonora, 

Urban Growth and Forecast 

Figure 34: X-Y scatter plot and linear regressions displaying urban growth in the area of Douglas, 

Ariz., and Agua Prieta, Sonora, including a 10–year forecast.

According to the linear regressions (fig. 36), by the year 2010, the Douglas area would increase 

by about 400 acres to a total of 3,150 acres, and Agua Prieta would increase about 1,000 acres 

to a total of 4,600 acres. 

Results

Colonias 

Development

Estimates of urban extent have been quantified and substantiate the hypothesis of an 

exponential increase in Mexican colonias in sister-city urban areas, in congruity with recent 

economic incentives generated by recent international policy. Based on the results from the 

urban growth study, the entire area has nearly doubled in size over 27 years (fig. 35). 

35
Total Area in 2000 

1973

1985

1995

2000

Figure 35: Pie chart illustrating growth in the study area.

The majority of growth has occurred in Agua Prieta, where the city’s urban extent was 60 

percent larger in 2000 than in 1973. The Douglas extent has grown by 25 percent. These 

numbers indicate that Agua Prieta has grown 2.5 times its original size in 27 years. It is not clear 

from this study what has driven this land-use conversion, although it is possible that the 

implementation of international economic policies have dramatically affected urban growth in the 

Mexican portion of the study area. If current trends continue, by 2010, it is expected that Douglas 

will grow by 11 percent and Agua Prieta will grow by 21 percent. 

The SCA overlay analysis of vector datasets on the derived urban extent boundaries 

helped to identify new colonia developments and their spatial relationships, as well as access to 

infrastructure and housing conditions as described by community members (fig. 36). This type of 

combined geospatial, tabular, and remote-sensing analyses allows assumptions to be made 

concerning growth and development along a timeline for each of the newly defined colonias. 

The lack of basic water and sewer infrastructure has been identified as a primary factor 

contributing to the health problems experienced by colonias residents (Ratcliffe, 2003). By 

identifying the areas in need of servicing, they may become designated as colonias to secure 

access to programs and funds that help support them. 

36
Figure 36: Urban extent information with colonias, sewer, and water line information overlain. 

37
Descriptions

United States colonias are predominantly older settlements that have been steadily 

increasing in size. The pre-existing colonias dataset for Cochise County was compared to the 

new city colonias derived dataset. The area described as Pirtleville colonia is consistent with the 

city defined boundary for Pirtleville and the Sulphur Springs Valley colonia, recognized by the 

USDA (fig. 12), holds portions of some newly named and recognized colonias boundaries 

(Fairview, Bay Acres, and Sunnyside) on the outskirts of the City of Douglas. Some new colonias 

do not fall in any previously defined colonia boundary. 

The Pirtleville colonia was established prior to 1973, grew extensively in 1985, and has 

since been growing slowly. It is equipped with both sewer and water lines within its urban extent. 

Fairview colonia seems to be the most recently developed area. While houses existed in the 

Fairview area prior to 2000, it was not previously recognized as urban. This may explain why 

Fairview lacks infrastructure. Development in Bay Acres and Northwest colonias probably 

occurred around 1995, but as of 2000, they have not grown much, although a small urban area 

was identified in 1985 imagery. Bay Acres is equipped with water lines, but not sewers. 

Sunnyside, Musgrave, Douglas Terrace, and Pasatiempo were urban in 1973, and have been 

growing slowly and steadily. Sunnyside has both water and sewer lines, but Pasatiempo and 

Douglas Terrace only have water. The Pasatiempo colonia is different than the other colonias 

because it has the smallest population consisting of predominantly non-Hispanic people living in 

predominantly owner-occupied housing units. It is apparent that the newer colonias—Fairview, 

Bay Acres, Northwest, and Musgrave—have not been equipped with water and sewer lines. 

Delineation of these areas will help to secure funding to implement these systems. 

Mexican colonias appear predominantly in those areas of Agua Prieta where settlement 

is new. In the delineation of these colonias, some sociological details were described by 

community members and documented herein. The oldest is Colonia Empacadora which, 

according to personal interviews with Reverend Jesus Gallegos, is known to be a very dangerous 

area. This area west of the railroads tracks is very poor and completely lacks sewer lines. The 

Colonias Infonavit, Infonavit-grande, and Fovista were established as Federally subsidized 

housing areas for many migrant workers from Oaxaca and southern Mexico, who moved into the 

area to work at the maquillas. According to Sylvia Villabolos de Zuniga, these colonias provide 

well-built track homes, which are extremely small apartment-like dwellings with only one restroom 

facility for all tenants. Many migrant workers, who travel with large families, occupy these units. 

The apartments are described as 20- by 20-foot rooms, holding 6 or more people. The Infonavit 

colonia was built directly around the industrial portion of the city around 1985, and the Infonavitgrande colonia was established at the city limits around 1995. 

Colonia Pueblo Nuevo and colonia Bachicuy, both of which are situated in a flood zone, 

were established around 1995. The lack of sewers in these areas necessitated use of outhouses 

and privy houses, which run out in floods, potentially infecting the drinking water with fecal 

coliform bacteria. According to Reverend Jesus Gallegos, who runs a community center in this 

neighborhood offering medical care, coliform contamination causes stomach infections in many of 

the children. Colonia Ladrillera was primarily inhabited in 2000 and colonia Southern appeared 

sometime after 2000. According to Del Cabarga, these areas were originally part of ajidos and 

sell for about U.S. $600 for an 18- by 20-foot lot. While streets exist throughout Agua Prieta, 

most are unpaved, and those that are paved tend to become covered in dirt because there are no 

street sweepers. This area is growing at a rapid rate and new colonias are being developed as 

growth occurs. 

Web-Based Interface Development 

The resulting geospatial database has been uploaded to a map service for the purpose of 

Web-based distribution. Through a collaborative effort with the University of Arizona's School of 

Renewable Natural Resources, utilizing relationships already established with the USGS, and 

expanding on ideas in congruence with the newly established Center on Impacts of Urban 

38
Development in Southern Arizona’s Desert Environment (CIUDAD), a Web portal was opened to 

support the USGS/HUD efforts at http://codd.art.srnr.arizona.edu/colonias (fig. 37). 

Figure 37: ArcIMS colonias mapping website portraying datasets in Douglas and Agua Prieta 

(http://codd.art.srnr.arizona.edu/colonias).

Delivery of Product/Training 

Development of this database was accomplished in cooperation with many different 

people within the communities of Douglas and Agua Prieta. Hard-copy maps, describing the 

sewer, water, aerial photos, and colonia boundaries, were supplied on request to those interested 

parties. Brochures, describing the project in English and Spanish, were developed and 

distributed to multiple community groups and non-profit organizations, including Focus Future, 

Turning Point, and Take it to the Hills. Associates of the Arizona Department of Environmental 

Quality were contacted via e-mail and telephone. Regular e-mail and newsletters, describing the 

status of the project, were sent to the people on the contact list. The U.S. Census and U.S. 

Border Patrol were contacted in regards to potential partnerships and interest in the current 

project. The project was also presented at the ESRI International User Conference in July 2003. 

On September 17th and 24th, 2003, workshops were held in Douglas, Ariz., to demonstrate utility 

and access to the newly digitized geospatial dataset. The focus of these meetings was to review 

39
the project. The meetings demonstrated the development and application of a bi-national web 

mapping service for Douglas and Agua Prieta. The purpose of this map service was described as 

support for border communities' urban planning and community development activities. Time was 

allocated during the meetings to provide user feedback and to discuss future maintenance of the 

web mapping service. The first meeting was held on September 17, 2003, at the City of Douglas 

Council Chambers and included a presentation of the database, a demonstration of data, 

description of products, a talk about possible applications, and an explanation of Internet system 

requirements. The Youth Advocates also made a presentation describing their work. 

The second meeting was held at Cochise College, Douglas Campus on September 24, 

2003 (fig. 39). This meeting was a hands-on workshop to introduce the dataset to the 

community. No previous GIS experience was necessary, and the first 20 people to register held 

available seats. Josh Pope, a volunteer from The Planning Center, assisted in this GIS workshop 

presentation. A tutorial was designed and presented to describe access to the datasets through 

the Internet. Participants at the computer lab filled out evaluation forms, which suggested a 

positive response. 

Figure 38: Cochise Community College, Douglas Campus, “USGS-HUD & GIS Training” sign. 

Conclusions

Development of new datasets describing urban neighborhoods and the implications of 

urban growth provides accessible and affordable information that can help promote sustainable 

development along the United States–Mexico border by providing local citizens with knowledge of 

their surroundings. The results from this project exemplify a paradigm shift regarding the 

dissemination of public records at the international level. Partnerships with other Federal, State, 

and local organizations, and with community members should improve both the quantity and 

accuracy of the acquired data. The Web-based mapping service consolidates and makes 

available demographic and urban-planning information to local nongovernmental organizations 

that are preparing grant and loan applications to improve the community. Community planners 

only need access to the Internet, which empowers everyone with tools previously available only 

to those who could afford expensive mapping software. 

40
REFERENCES

Acevedo, W., Richards, L.R., and Buchanan, J.T., 1999, Analysis of land use change in urban 

environments: U.S. Geological Survey Fact Sheet 188-99, 4 p. 

Brady, Laura M., Gray, Floyd, Castaneda, Mario, Boltman, Mark, and Bolm, Karen Sue, 2002, 

Preliminary United States–Mexico border watershed analysis, twin cities area of Nogales, 

Arizona, and Nogales, Sonora: U.S. Geological Survey Open-File Report: Open-File Report 

02-112. 

Cañas, Jesus, and Coronado, Roberto, 2002, Maquiladora industry: past, present, and future, in

El Paso Business Frontier, Federal Reserve Bank of Dallas, El Paso Branch, Issue 2.

Comisión De Cooperación Ecológica Fronteriza (COCEF/BECC), 1998, Agua Prieta, Sonora, 

Plan Maestro: Para el Mejoramiento de los Servicios de Agua Potable, Alcantarillado y 

Saneamiento de la Ciudad de Agua Prieta, Sonora, Y Levatamiento de Redes Hidraulicas. 

CONTA 98-02. 

Crawford, J., Acevedo, W., Foresman, T., Buchanan, J., and Prince, W., 1996, Developing a 

temporal database for urban development for the Baltimore–Washington region. American 

Society for Photogrammetry and Remote Sensing Conference, Baltimore, Md., April 20-26, 

1996. 

Eastman, J.R., and Fulk, M., 1993, Long sequence time series evaluation using standardized 

principle components: Photogrammetric Engineering and Remote Sensing, v. 59, no. 6, p. 

991-996. 

Forney, W., Richards, L., Adams, K.D., Minor, T.B., Rowe, T.G., Smith, J.L., and Raumann, C.G., 

2001, Land use change and effects on water quality and ecosystem health in the Lake Tahoe 

Basin, Nevada and California: U.S. Geological Survey Open-File Report 01-418, 29 p. 

Haack, B., Bryant, N., Adams, S., 1987, An assessment of Landsat MSS and TM data for urban 

digital classification: Remote Sensing of Environment, v. 21, p. 201-213. 

Howarth, P.J., 1986, Landsat digital enhancement for change detection in urban environment: 

Remote Sensing of Environment, v. 13, p. 149-160. 

INEGI, 1995, Estadísticas Históricas de México Tomo I, 1994, México. 

Jensen, J.R., and Toll, D.L., 1982, Detecting residential land-use development at the urban 

fringe: Photogrammetric Engineering and Remote Sensing, v. 48, p. 629-643. 

Jensen, J.R., Rutchey, K., Koch, M.S., and Narumalani, S., 1995, Inland wetland change 

detection in everglades water conservation area 2a using a time series of normalized 

remotely sensed data: Photogrammetric Engineering and Remote Sensing, v. 61, no. 2, p. 

199-209. 

Kearney, Milo, 1995, Border Cuates: A history of the U.S.-Mexican Twin Cities: Austin, Eakin 

Press.

Kent, Robert, 1983, Agriculture and ranching, in Borderlands Sourcebook: A Guide to the 

Literature on Northern Mexico and the American Southwest: Norman, University of Oklahoma 

Press, p. 140. 

41
Kirkland, D., Gaydos, L., Clarke, K., DeCola, L., Acevedo, W., and Bell, C., 1994, An analysis of 

human-induced land transformation in the San Francisco Bay/Sacramento area: World 

Resource Review v. 6, no. 2, p. 206-217. 

Lee, C.T., and Marsh, S.E., 1995, The use of archival Landsat MSS and ancillary data in a GIS 

environment to map historical change in an urban riparian habitat: Photogrammetric 

Engineering and Remote Sensing, v. 61, no. 8, p. 999–1,008. 

Mack, C., Marsh, S.E., and Hutchinson, C.F., 1995, Application of aerial photography and GIS 

techniques in the development of an historical perspective of environmental hazards at the 

rural-urban fringe: Photogrammetric Engineering and Remote Sensing, v. 61, no. 8, p. 1,015–

1,020. 

Martynec, S., Peter, D.E., and Hardaker, C., 1994, Cultural Resources Survey and Monitoring of 

the Douglas-Naco Ariz. Sector of the United States–Mexico Border: Plano, Texas: GeoMarine, Inc. 

McHarg, Ian L., 1969, Design with Nature: Garden City, New York, Doubleday/Natural History 

Press.

Myrick, David F., 1967, The railroads of Arizona: an approach to tombstone. Journal of Ariz. 

History, v. 8, no. 3, p. 155-170. [Tucson, Arizona, Historical Society]. 

Osborn, K., 1998. United States–Mexico transboundary aerial photography and mapping 

initiative: Photogrammetric Engineering and Remote Sensing, v. 64, no. 11, p. 1,085–1,088. 

Ratcliffe, Michael R., 2003, Spatial and demographic data for colonias: Proceedings from the 42nd

Annual Meeting of the Western Regional Science Association, February 26–March 1, 2003, 

Rio Rico, Ariz. 

Seltzer, Raymond, 1959, Head of University of Arizona Agricultural Economics Department, Cited 

in Arizona Cattlelog, January 1959, p. 26. 

Shan, Z., 1999, Remote sensing and GIS as a tool in exploring the dynamics of urban spatial 

structure: the case of the Shanghai City: Proceedings of the 20th Asian Conference on 

Remote Sensing, November 22-25, 1999, Hong Kong, China. 

Trennert, Robert A., 1988, A different perspective: victorian travelers in Arizona, 1860-1900. 

Journal of Arizona History, v. 29, no. 4, p. 349-370. [Tucson, Arizona Historical Society]. 

U.S. Bureau of the Census, 1960-1990; 1997: Population, Social and Economic Characteristics. 

Weaver, Thomas, 2001, Time, space and articulation in the economic development of the United 

States–Mexico border region from 1940 to 2000: Human Organization, v. 60, no. 2, p. 105-

120. 

 

42
APPENDIX A: Local organizations regularly contacted

Acosta y Asociados, Agua Prieta, Sonora 

Arizona Department of Environmental Quality (ADEQ), Phoenix and Nogales, AZ 

Arizona Department of Health Services (ADHS), Phoenix, AZ 

Arizona-Mexico Commission, Phoenix, AZ 

Border Environment Cooperation Commission: La Comisión de Cooperación Ecológica 

Fronteriza (BECC/COCEF), El Paso/Juarez, Chichuahua 

City of Bisbee, Bisbee, AZ 

City of Douglas Department of Public Works, Douglas, AZ 

City of Douglas Housing Authority, Douglas, AZ 

City of Douglas, Douglas, AZ 

Cochise College, Douglas, AZ 

Cochise County Housing Authority, Bisbee, AZ 

Cochise County, Bisbee, AZ 

Comisión de Agua Potable y Alcantarillado del Estado de Sonora (COAPAES), Nogales and 

Agua Prieta, Sonora 

Emergency Response Commission, Agua Prieta, Sonora 

Gateway Commmunity College, Phoenix, AZ 

Institute for the Environment and Sustainable Development of Sonora (IMADES), Hermosillo, 

Sonora 

Instituto Nacional de Estadística Geografíae Informática (INEGI), Agua Calientes, Sonora 

Libraries for the Future, Phoenix, AZ 

Municipal de Agua Prieta, Agua Prieta, Sonora 

New Turf/Youth Advocates, Douglas and Sierra Vista, AZ 

Sonoran Desert Institute, Tucson, AZ 

SouthEastern Arizona Behavioral Health Services (SEABHS), Douglas, AZ 

SouthEastern Arizona Governments Organization (SEAGO), Douglas, AZ 

The Planning Center, Tucson, AZ 

The Promotora Institute, Nogales, AZ 

The University of Arizona, Bureau of Applied Research in Anthropology (BARA), Tucson, AZ 

The University of Arizona, College of Architecture, Planning and Landscape Architecture 

(CAPLA), Tucson, AZ 

The University of Arizona, Department of Geography, Tucson, AZ 

The University of Arizona, Latin American Studies, Tucson, AZ 

The University of Arizona, School of Renewable Natural Resources (SRNR), Tucson, AZ 

The University of Arizona, Udall Center for Studies in Public Policy, Tucson, AZ 

The University of Texas, Austin, TX 

Turning Point Non-Profit, Douglas, AZ 

U.S. Border Patrol, Douglas, AZ 

U.S. Census, Washington, DC 

U.S. Department of Health, Cochise County, Bisbee, AZ 

United States–Mexico Border Philanthropy Partnership, Douglas, AZ 

USDA Rural Development, Sierra Vista, AZ 

Youth Advocates!, Douglas, AZ 

43
APPENDIX B: Photographs of Colonias

Mike Ortega, (City Manager of Douglas), took USGS and HUD staff on a tour of colonias, 

where Angela Donelson (Southwest Border, Farmworker and Colonias Initiative, HUD) captured 

the following photographs (figs. 40-42). Silvia Villalobos de Zuñiga also took videotape in June 

2003, describing some of the colonias in the municipal. The videotape was converted to 932 

digital photographs by the USGS in Flagstaff, Arizona, under Edwin Pfeifer. Some photographs 

are included in this report and intended for publication at the interactive mapping Internet site 

(figs. 43-50). 

Figure 39: Colonia dwelling in Douglas (photo by Angela J. Donelson).

Figure 40: The Pirtleville colonia, outside of Douglas (photo by Angela J. Donelson).

44
Figure 41: Trailers comprise some colonias in Douglas (photo by Angela J. Donelson).

 

Figure 42: Houses are made of various materials in colonia Empacadora, Agua Prieta (photo by 

Silvia Villalobos de Zuñiga).

45
Figure 43: One woman living in colonia Empacadora, Agua Prieta (photos by Silvia Villalobos de 

Zuñiga).

Figure 44: House in colonia Southern, Agua Prieta (photo by Silvia Villalobos de Zuñiga).

46
Figure 45: This family in colonia Bachicuy, Agua Prieta is not entitled to government subsidies 

due to ownership of automobile (a luxury) (photo by Silvia Villalobos de Zuñiga).

Figure 46: House with water tank in colonia Bachicuy, Agua Prieta (photo by Silvia Villalobos de 

Zuñiga).

47
Figure 47: Colonia Ladrillera, Agua Prieta (photo by Silvia Villalobos de Zuñiga).

Figure 48: Materials for houses in colonia Pueblo Nuevo, Agua Prieta are makeshift (photo by 

Silvia Villalobos de Zuñiga).

48
Figure 49: Cardboard roofing typical in colonia of Agua Prieta (photo by Silvia Villalobos de 

Zuñiga).

49
APPENDIX C: Metadata generated according to the Federal Geographic Data 

Committee (FGDC) standards for all new coverages.

1973 

Identification_Information: 

 Citation: 

 Citation_Information: 

 Originator: Laura M. Norman 

 Publication_Date: 12/03 

 Title: 1973 Urban Extent of Douglas, Arizona/Agua Prieta, Sonora 

 Edition: 1 

 Geospatial_Data_Presentation_Form: vector digital data 

 Series_Information: 

 Online Linkage: http://codd.art.srnr.arizona.edu/colonias 

 Larger_Work_Citation: 

 Citation_Information: 

 Originator: Norman, Laura M., Donelson, Angela J., Pfeifer, Edwin, Lam, Alven H., and 

Osborn, Kenneth J. 

 Publication_Date: 12/03 

 Title: Analyses of Urban Sprawl and Colonias Development in Douglas, Arizona & Agua 

Prieta, Sonora, on the United States–Mexico Border; A Process Application using GIS and 

Remote Sensing 

 Geospatial_Data_Presentation_Form: vector digital data 

 Series_Information: 

 Series_Name: Open File Report 

 Issue_Identification: OFR 03-XXX 

 Publication_Information: 

 Publication_Place: Menlo Park, CA 

 Publisher: USGS 

 Online_Linkage: http://wgsc.wr.usgs.gov/wrgeog_pubs/ 

 Description: 

 Abstract: Landsat imagery describing the Douglas, AZ and Agua Prieta, Sonora area (Path 35 

Row 38) was acquired for place name Sierra Vista at 06/04/1973 from the Arizona Regional 

Image Archive, (http://aria.arizona.edu), an on-line interdisciplinary resource system for digital 

image and map data for the Sonoran desert region, including the U.S. Southwest and northern 

Mexico. The urban extent of the twin cities are was extracted from the satellite image. 

 Purpose: Image processing and subsequent temporal remote sensing analysis was done to 

quantify urban growth stemming from human settlement. 

 Time_Period_of_Content: 

 Time_Period_Information: 

 Single_Date/Time: 

 Calendar_Date: 06/04/1973 

 Currentness_Reference: 1973 

 Status: 

 Progress: Complete 

 Maintenance_and_Update_Frequency: None planned 

 Spatial_Domain: 

 Bounding_Coordinates: 

 West_Bounding_Coordinate: -109.568835 

 East_Bounding_Coordinate: -109.512347 

 North_Bounding_Coordinate: 31.378782 

 South_Bounding_Coordinate: 31.295863 

 Keywords: 

 Theme: 

50
 Theme_Keyword_Thesaurus: none 

 Theme_Keyword: Land use 

 Theme_Keyword: Urban Sprawl 

 Place: 

 Place_Keyword: Arizona 

 Place_Keyword: Sonora 

 Use_Constraints: This digital database is not meant to be used or displayed at any scale larger 

than 1:24,000 (for example, 1:12,000). Any hardcopies utilizing this dataset shall clearly 

indicate their source. If the user has modified the data in any way, he is obligated to describe the 

types of modifications he has performed on the hardcopy map. User specifically agrees not to 

misrepresent this dataset nor to imply that changes he made were approved by the U.S. 

Geological Survey. 

 Point_of_Contact: 

 Contact_Information: 

 Contact_Person_Primary: 

 Contact_Person: Laura M. Norman 

 Contact_Organization: U.S. Geological Survey 

 Contact_Position: Cartographer, GIS Specialist 

 Contact_Address: 

 Address_Type: mailing address 

 Address: 520 N Park Ave, Ste #355 

 City: Tucson 

 State_or_Province: AZ 

 Postal_Code: 85719 

 Country: U.S.A 

 Contact_Voice_Telephone: 520 670 5510 

 Contact_Facsimile_Telephone: 520 670 5571 

 Contact_Electronic_Mail_Address: lmbrady@usgs.gov 

 Hours_of_Service: 9-5 

 Native_Data_Set_Environment: Microsoft Windows 2000 Version 5.0 (Build 2195) Service Pack 

4; ESRI ArcCatalog 8.2.0.700 

 Cross_Reference: 

 Citation_Information: 

 Publication_Information: 

 Publication_Place: Tucson, Arizona 

 Publisher: U.S. Geological Survey 

 Larger_Work_Citation: 

 Citation_Information: 

 Publication_Information: 

 Publication_Place: USGS 

Data_Quality_Information: 

 Attribute_Accuracy: 

 Attribute_Accuracy_Report: Although the satellite data were all acquired from the Landsat 

system, different sensors were accessed through the years, which may lead to some discrepancy 

in analysis. The Landsat 1 satellite acquired the MSS imagery for the 1973 year at a 79-meter 

resolution. Therefore, we were limited by pixel sixe. Other error that could have been introduced 

includes error due to rubbersheeting algorithm applied to the dataset. 

 Lineage: 

 Source_Information: 

 Source_Citation: 

 Citation_Information: 

 Publication_Date: Unknown 

 Title: Landsat 5 TM 

 Geospatial_Data_Presentation_Form: remote-sensing image 

 Other_Citation_Details: 79 m. resolution 

 Online_Linkage: www.aria.arizona.edu 

51
 Source_Time_Period_of_Content: 

 Time_Period_Information: 

 Single_Date/Time: 

 Calendar_Date: 06/04/73 

 Source_Currentness_Reference: ground condition 

 Process_Step: 

 Process_Description: Geometric distortions were corrected by establishing a relationship 

between the satellite image and a Digital Orthophoto Quarter Quad (DOQQ) of the corresponding 

regions. Once these ground control points (GCP's) were established, the image is then 

converted, or rubbersheeted to the new coordinate system through a nearest neighbor 

resampling regime using a 3rd order polynomial, through a process called rectification. 

Identification of features by remote sensing involves computer software with the ability to identify 

pixels based upon their numerical properties and analyze them for statistical estimates. Using 

clustering methods to assign each pixel in an image to spectral classes, of which it has no 

foreknowledge, is called unsupervised classification. These procedures were applied to 

determine the location of the spectral classes into which the pixels are assigned. The analyst, 

who confirms these classes with information from ground maps, aerial photos, and ground visits, 

then identifies the output classes. Estimates of urban sprawl have been quantified by means of 

digitizing the urban extent area from the processed image. 

 Process_Date: 05/03 

Spatial_Data_Organization_Information: 

 Direct_Spatial_Reference_Method: Vector 

 Point_and_Vector_Object_Information: 

 SDTS_Terms_Description: 

 SDTS_Point_and_Vector_Object_Type: G-polygon 

 Point_and_Vector_Object_Count: 6 

Spatial_Reference_Information: 

 Horizontal_Coordinate_System_Definition: 

 Planar: 

 Grid_Coordinate_System: 

 Grid_Coordinate_System_Name: Universal Transverse Mercator 

 Universal_Transverse_Mercator: 

 UTM_Zone_Number: 12 

 Transverse_Mercator: 

 Scale_Factor_at_Central_Meridian: 0.999600 

 Longitude_of_Central_Meridian: -111.000000 

 Latitude_of_Projection_Origin: 0.000000 

 False_Easting: 500000.000000 

 False_Northing: 0.000000 

 Planar_Coordinate_Information: 

 Planar_Coordinate_Encoding_Method: coordinate pair 

 Coordinate_Representation: 

 Abscissa_Resolution: 0.000016 

 Ordinate_Resolution: 0.000016 

 Planar_Distance_Units: meters 

 Geodetic_Model: 

 Horizontal_Datum_Name: North American Datum of 1983 

 Ellipsoid_Name: Geodetic Reference System 80 

 Semi-major_Axis: 6378137.000000 

 Denominator_of_Flattening_Ratio: 298.257222 

Entity_and_Attribute_Information: 

 Detailed_Description: 

 Entity_Type: 

 Entity_Type_Label: 1973 

 Entity_Type_Definition: Polygon used to portray urban extent in 1973 

 Attribute: 

52
 Attribute_Label: FID 

 Attribute_Definition: Internal feature number. 

 Attribute_Definition_Source: ESRI 

 Attribute_Domain_Values: 

 Unrepresentable_Domain: Sequential unique whole numbers that are automatically 

generated. 

 Attribute: 

 Attribute_Label: Shape 

 Attribute_Definition: Feature geometry. 

 Attribute_Definition_Source: ESRI 

 Attribute_Domain_Values: 

 Unrepresentable_Domain: Coordinates defining the features. 

 Attribute: 

 Attribute_Label: ID 

 Attribute: 

 Attribute_Label: GRIDCODE 

Distribution_Information: 

 Distributor: 

 Contact_Information: 

 Contact_Organization_Primary: 

 Contact_Organization: U.S. Geological Survey 

 Resource_Description: Downloadable Data 

 Distribution_Liability: 

 The U.S. Geological Survey (USGS) provides these geographic data "as is." The USGS 

makes no guarantee or warranty concerning the accuracy of information contained in the 

geographic data. The USGS further makes no warranties, either expressed or implied, as to any 

other matter whatsoever, including, without limitation, the condition of the product or its fitness for 

any particular purpose. The burden for determining fitness for use lies entirely with the user. 

Although these data have been processed successfully on computers at the USGS, no warranty, 

expressed or implied, is made by the USGS regarding the use of these data on any other system, 

nor does the fact of distribution constitute or imply any such warranty. 

 In no event shall the USGS have any liability whatsoever for payment of any consequential, 

incidental, indirect, special, or tort damages of any kind, including, but not limited to, any loss of 

profits arising out of use of or reliance on the geographic data or arising out of the delivery, 

installation, operation, or support by USGS. 

 Standard_Order_Process: 

 Digital_Form: 

 Digital_Transfer_Information: 

 Transfer_Size: 0.018 

Metadata_Reference_Information: 

 Metadata_Date: 20031205 

 Metadata_Review_Date: 20031204 

 Metadata_Contact: 

 Contact_Information: 

 Contact_Person_Primary: 

 Contact_Person: Laura M. Norman 

 Contact_Organization: U.S. Geological Survey 

 Contact_Position: Cartographer, GIS Specialist 

 Contact_Address: 

 Address_Type: mailing address 

 Address: 520 N Park Ave, Ste #355 

 City: Tucson 

 State_or_Province: AZ 

 Postal_Code: 85719 

 Country: U.S.A 

53
 Contact_Voice_Telephone: 520 670 5510 

 Contact_Facsimile_Telephone: 520 670 5571 

 Contact_Electronic_Mail_Address: lmbrady@usgs.gov 

 Hours_of_Service: 9-5 

 Metadata_Standard_Name: FGDC Content Standards for Digital Geospatial Metadata 

 Metadata_Standard_Version: FGDC-STD-001-1998 

 Metadata_Time_Convention: local time 

 Metadata_Access_Constraints: none 

 Metadata_Use_Constraints: none 

 Metadata_Extensions: 

 Online_Linkage: http://www.esri.com/metadata/esriprof80.html 

 Profile_Name: ESRI Metadata Profile 

54
1985 

Identification_Information: 

 Citation: 

 Citation_Information: 

 Originator: Laura M. Norman 

 Publication_Date: 12/03 

 Title: 1985 Urban Extent of Douglas, Arizona/Agua Prieta, Sonora 

 Edition: 1 

 Geospatial_Data_Presentation_Form: vector digital data 

 Online Linkage: http://codd.art.srnr.arizona.edu/colonias 

 Larger_Work_Citation: 

 Citation_Information: 

 Originator: Norman, Laura M., Donelson, Angela J., Pfeifer, Edwin, Lam, Alven H., and 

Osborn, Kenneth J. 

 Publication_Date: 12/03 

 Title: Analyses of Urban Sprawl and Colonias Development in Douglas, Arizona & Agua 

Prieta, Sonora on the United States–Mexico Border; A Process Application using GIS and 

Remote Sensing 

 Geospatial_Data_Presentation_Form: vector digital data 

 Series_Information: 

 Series_Name: Open File Report 

 Issue_Identification: OFR-03-XXX 

 Publication_Information: 

 Publication_Place: Menlo Park, CA 

 Publisher: USGS 

 Online_Linkage: <http://wgsc.wr.usgs.gov/wrgeog_pubs/> 

 Description: 

 Abstract: Landsat imagery describing the Douglas, AZ and Agua Prieta, Sonora area (Path 35 

Row 38) was acquired for place name Sierra Vista at 06/06/1985 from the Arizona Regional 

Image Archive, (http://aria.arizona.edu), an on-line interdisciplinary resource system for digital 

image and map data for the Sonoran desert region, including the U.S. Southwest and northern 

Mexico. The urban extent of the twin cities are was extracted from the satellite image. 

 Purpose: Image processing and subsequent temporal remote sensing analysis was done to 

quantify urban growth stemming from human settlement at this time period. 

 Time_Period_of_Content: 

 Time_Period_Information: 

 Single_Date/Time: 

 Calendar_Date: 06/06/1985 

 Currentness_Reference: 1985 

 Status: 

 Progress: Complete 

 Maintenance_and_Update_Frequency: None planned 

 Spatial_Domain: 

 Bounding_Coordinates: 

 West_Bounding_Coordinate: -109.568835 

 East_Bounding_Coordinate: -109.512347 

 North_Bounding_Coordinate: 31.378782 

 South_Bounding_Coordinate: 31.295863 

 Keywords: 

 Theme: 

 Theme_Keyword_Thesaurus: none 

 Theme_Keyword: Land use 

 Theme_Keyword: Urban Sprawl 

55
 Place: 

 Place_Keyword_Thesaurus: none 

 Place_Keyword: Arizona 

 Place_Keyword: Sonora 

 Place_Keyword: Douglas, AZ 

 Place_Keyword: Agua Prieta, Son. 

 Use_Constraints: This digital database is not meant to be used or displayed at any scale larger 

than 1:24,000 (for example, 1:12,000). Any hardcopies utilizing this dataset shall clearly 

indicate their source. If the user has modified the data in any way, he is obligated to describe the 

types of modifications he has performed on the hardcopy map. User specifically agrees not to 

misrepresent this dataset nor to imply that changes he made were approved by the U.S. 

Geological Survey. 

 Point_of_Contact: 

 Contact_Information: 

 Contact_Person_Primary: 

 Contact_Person: Laura M. Norman 

 Contact_Organization: U.S. Geological Survey 

 Contact_Position: Cartographer, GIS Specialist 

 Contact_Address: 

 Address_Type: mailing address 

 Address: 520 N Park Ave, Ste #355 

 City: Tucson 

 State_or_Province: AZ 

 Postal_Code: 85745 

 Country: U.S.A 

 Contact_Voice_Telephone: 520 670 5510 

 Contact_Facsimile_Telephone: 520 670 5571 

 Contact_Electronic_Mail_Address: lmbrady@usgs.gov 

 Hours_of_Service: 9-5 

 Native_Data_Set_Environment: Microsoft Windows 2000 Version 5.0 (Build 2195) Service Pack 

4; ESRI ArcCatalog 8.2.0.700 

 Cross_Reference: 

 Citation_Information: 

 Publication_Information: 

 Larger_Work_Citation: 

 Citation_Information: 

 Publication_Information: 

 Publication_Place: USGS 

Data_Quality_Information: 

 Attribute_Accuracy: 

 Attribute_Accuracy_Report: Although the satellite data were all acquired from the Landsat 

system, different sensors were accessed through the years, which may lead to some discrepancy 

in analysis. Landsat 5 TM sensor acquired that MSS data in 1985 at a 30-m resolution. Therefore, 

we were limited by pixel size. Other error that could have been introduced includes error due to 

rubbersheeting algorithm applied to the dataset. 

 Lineage: 

 Source_Information: 

 Source_Citation: 

 Citation_Information: 

 Publication_Date: Unknown 

 Title: Landsat 5 TM 

 Geospatial_Data_Presentation_Form: remote-sensing image 

 Other_Citation_Details: 30 m. resolution 

 Online_Linkage: www.aria.arizona.edu 

 Source_Time_Period_of_Content: 

 Time_Period_Information: 

56
 Single_Date/Time: 

 Calendar_Date: 06/06/1985 

 Source_Currentness_Reference: ground condition 

 Process_Step: 

 Process_Description: Geometric distortions were corrected by establishing a relationship 

between the satellite image and a Digital Orthophoto Quarter Quad (DOQQ) of the corresponding 

regions. Once these ground control points (GCP's) were established, the image is then 

converted, or rubbersheeted to the new coordinate system through a nearest neighbor 

resampling regime using a 3rd order polynomial, through a process called rectification. 

Identification of features by remote sensing involves computer software with the ability to identify 

pixels based upon their numerical properties and analyze them for statistical estimates. Using 

clustering methods to assign each pixel in an image to spectral classes, of which it has no 

foreknowledge, is called unsupervised classification. These procedures were applied to 

determine the location of the spectral classes into which the pixels are assigned. The analyst, 

who confirms these classes with information from ground maps, aerial photos, and ground visits, 

then identifies the output classes. Estimates of urban sprawl have been quantified by means of 

digitizing the urban extent area from the processed image. 

 Process_Date: 05/03 

Spatial_Data_Organization_Information: 

 Direct_Spatial_Reference_Method: Vector 

 Point_and_Vector_Object_Information: 

 SDTS_Terms_Description: 

 SDTS_Point_and_Vector_Object_Type: G-polygon 

 Point_and_Vector_Object_Count: 15 

Spatial_Reference_Information: 

 Horizontal_Coordinate_System_Definition: 

 Planar: 

 Grid_Coordinate_System: 

 Grid_Coordinate_System_Name: Universal Transverse Mercator 

 Universal_Transverse_Mercator: 

 UTM_Zone_Number: 12 

 Transverse_Mercator: 

 Scale_Factor_at_Central_Meridian: 0.999600 

 Longitude_of_Central_Meridian: -111.000000 

 Latitude_of_Projection_Origin: 0.000000 

 False_Easting: 500000.000000 

 False_Northing: 0.000000 

 Planar_Coordinate_Information: 

 Planar_Coordinate_Encoding_Method: coordinate pair 

 Coordinate_Representation: 

 Abscissa_Resolution: 0.000016 

 Ordinate_Resolution: 0.000016 

 Planar_Distance_Units: meters 

 Geodetic_Model: 

 Horizontal_Datum_Name: North American Datum of 1983 

 Ellipsoid_Name: Geodetic Reference System 80 

 Semi-major_Axis: 6378137.000000 

 Denominator_of_Flattening_Ratio: 298.257222 

Entity_and_Attribute_Information: 

 Detailed_Description: 

 Entity_Type: 

 Entity_Type_Label: 1985 

 Entity_Type_Definition: Polygon used to portray urban extent in 1985 

 Attribute: 

 Attribute_Label: FID 

 Attribute_Definition: Internal feature number. 

57
 Attribute_Definition_Source: ESRI 

 Attribute_Domain_Values: 

 Unrepresentable_Domain: Sequential unique whole numbers that are automatically 

generated. 

 Attribute: 

 Attribute_Label: Shape 

 Attribute_Definition: Feature geometry. 

 Attribute_Definition_Source: ESRI 

 Attribute_Domain_Values: 

 Unrepresentable_Domain: Coordinates defining the features. 

 Attribute: 

 Attribute_Label: ID 

 Attribute: 

 Attribute_Label: GRIDCODE 

Distribution_Information: 

 Distributor: 

 Contact_Information: 

 Contact_Organization_Primary: 

 Contact_Organization: U.S. Geological Survey 

 Resource_Description: Downloadable Data 

 Distribution_Liability: 

 The U.S. Geological Survey (USGS) provides these geographic data "as is." The USGS 

makes no guarantee or warranty concerning the accuracy of information contained in the 

geographic data. The USGS further makes no warranties, either expressed or implied, as to any 

other matter whatsoever, including, without limitation, the condition of the product or its fitness for 

any particular purpose. The burden for determining fitness for use lies entirely with the user. 

Although these data have been processed successfully on computers at the USGS, no warranty, 

expressed or implied, is made by the USGS regarding the use of these data on any other system, 

nor does the fact of distribution constitute or imply any such warranty. 

 In no event shall the USGS have any liability whatsoever for payment of any consequential, 

incidental, indirect, special, or tort damages of any kind, including, but not limited to, any loss of 

profits arising out of use of or reliance on the geographic data or arising out of the delivery, 

installation, operation, or support by USGS. 

 Standard_Order_Process: 

 Digital_Form: 

 Digital_Transfer_Information: 

 Transfer_Size: 0.016 

Metadata_Reference_Information: 

 Metadata_Date: 20031205 

 Metadata_Contact: 

 Contact_Information: 

 Contact_Person_Primary: 

 Contact_Person: Laura M. Norman 

 Contact_Organization: U.S. Geological Survey 

 Contact_Position: Cartographer, GIS Specialist 

 Contact_Address: 

 Address_Type: mailing address 

 Address: 520 N Park Ave, Ste #355 

 City: Tucson 

 State_or_Province: AZ 

 Postal_Code: 85719 

 Country: U.S.A 

 Contact_Voice_Telephone: 520 670 5510 

 Contact_Facsimile_Telephone: 520 670 5571 

 Contact_Electronic_Mail_Address: lmbrady@usgs.gov 

58
 Hours_of_Service: 9-5 

 Metadata_Standard_Name: FGDC Content Standards for Digital Geospatial Metadata 

 Metadata_Standard_Version: FGDC-STD-001-1998 

 Metadata_Time_Convention: local time 

 Metadata_Access_Constraints: none 

 Metadata_Use_Constraints: none 

 Metadata_Extensions: 

 Online_Linkage: http://www.esri.com/metadata/esriprof80.html 

 Profile_Name: ESRI Metadata Profile 

 Metadata_Extensions: 

 Online_Linkage: http://www.esri.com/metadata/esriprof80.html 

 Profile_Name: ESRI Metadata Profile 

59
1995 

Identification_Information: 

 Citation: 

 Citation_Information: 

 Originator: Laura M. Norman 

 Publication_Date: 12/03 

 Publication_Time: Unknown 

 Title: 1995 Urban Extent of Douglas, Arizona/Agua Prieta, Sonora 

 Edition: 1 

 Geospatial_Data_Presentation_Form: vector digital data 

 Online Linkage: http://codd.art.srnr.arizona.edu/colonias 

 Larger_Work_Citation: 

 Citation_Information: 

 Originator: Norman, Laura M., Donelson, Angela J., Pfeifer, Edwin, Lam, Alven H., and 

Osborn, Kenneth J. 

 Publication_Date: Unknown 

 Title: Analyses of Urban Sprawl and Colonias Development in Douglas, Arizona & Agua 

Prieta, Sonora on the United States–Mexico Border; A Process Application using GIS and 

Remote Sensing 

 Edition: Open File Report 

 Geospatial_Data_Presentation_Form: vector digital data 

 Series_Information: 

 Series_Name: Open File Report 

 Issue_Identification: OFR-03-XXX 

 Publication_Information: 

 Publication_Place: Menlo Park, CA 

 Publisher: USGS 

 Online_Linkage: <http://wgsc.wr.usgs.gov/wrgeog_pubs/> 

 Description: 

 Abstract: Landsat imagery describing the Douglas, AZ and Agua Prieta, Sonora area (Path 35 

Row 38) was acquired for place name Sierra Vista at 06/18/1995 from the Arizona Regional 

Image Archive, (http://aria.arizona.edu), an on-line interdisciplinary resource system for digital 

image and map data for the Sonoran desert region, including the U.S. Southwest and northern 

Mexico. The urban extent of the twin cities are was extracted from the satellite image. 

 Purpose: Image processing and subsequent temporal remote sensing analysis was done to 

quantify urban growth stemming from human settlement. 

 Time_Period_of_Content: 

 Time_Period_Information: 

 Single_Date/Time: 

 Calendar_Date: 06/18/1995 

 Currentness_Reference: 1995 

 Status: 

 Progress: Complete 

 Maintenance_and_Update_Frequency: None planned 

 Spatial_Domain: 

 Bounding_Coordinates: 

 West_Bounding_Coordinate: -109.568835 

 East_Bounding_Coordinate: -109.512347 

 North_Bounding_Coordinate: 31.378782 

 South_Bounding_Coordinate: 31.295863 

 Keywords: 

 Theme: 

 Theme_Keyword: Land use 

 Theme_Keyword: Urban Sprawl 

60
 Place: 

 Place_Keyword: Arizona 

 Place_Keyword: Sonora 

 Place_Keyword: Douglas, AZ 

 Place_Keyword: Agua Prieta, Son. 

 Access_Constraints:

 The U.S. Geological Survey (USGS) provides these geographic data "as is." The USGS 

makes no guarantee or warranty concerning the accuracy of information contained in the 

geographic data. The USGS further makes no warranties, either expressed or implied, as to any 

other matter whatsoever, including, without limitation, the condition of the product or its fitness for 

any particular purpose. The burden for determining fitness for use lies entirely with the user. 

Although these data have been processed successfully on computers at the USGS, no warranty, 

expressed or implied, is made by the USGS regarding the use of these data on any other system, 

nor does the fact of distribution constitute or imply any such warranty. 

 In no event shall the USGS have any liability whatsoever for payment of any consequential, 

incidental, indirect, special, or tort damages of any kind, including, but not limited to, any loss of 

profits arising out of use of or reliance on the geographic data or arising out of the delivery, 

installation, operation, or support by USGS. 

 Use_Constraints: This digital database is not meant to be used or displayed at any scale larger 

than 1:24,000 (for example, 1:12,000). Any hardcopies utilizing this dataset shall clearly 

indicate their source. If the user has modified the data in any way, he is obligated to describe the 

types of modifications he has performed on the hardcopy map. User specifically agrees not to 

misrepresent this dataset nor to imply that changes he made were approved by the U.S. 

Geological Survey. 

 Point_of_Contact: 

 Contact_Information: 

 Contact_Person_Primary: 

 Contact_Person: Laura M. Norman 

 Contact_Organization: U.S. Geological Survey 

 Contact_Position: Cartographer, GIS Specialist 

 Contact_Voice_Telephone: 520 670 5510 

 Contact_Facsimile_Telephone: 520 670 5571 

 Contact_Electronic_Mail_Address: lmbrady@usgs.gov 

 Hours_of_Service: 9-5 

 Native_Data_Set_Environment: Microsoft Windows 2000 Version 5.0 (Build 2195) Service Pack 

4; ESRI ArcCatalog 8.2.0.700 

 Cross_Reference: 

 Citation_Information: 

 Publication_Information: 

 Larger_Work_Citation: 

 Citation_Information: 

 Publication_Information: 

 Publication_Place: USGS 

Data_Quality_Information: 

 Attribute_Accuracy: 

 Attribute_Accuracy_Report: Although the satellite data were all acquired from the Landsat 

system, different sensors were accessed through the years, which may lead to some discrepancy 

in analysis. Landsat 5 TM sensor acquired that MSS data in 1995 at a 30-m resolution. Therefore, 

we were limited by pixel sixe. Other error that could have been introduced includes error due to 

rubbersheeting algorithm applied to the dataset. 

 Lineage: 

 Source_Information: 

 Source_Citation: 

 Citation_Information: 

 Publication_Date: Unknown 

61
 Title: Landsat 5 TM 

 Geospatial_Data_Presentation_Form: remote-sensing image 

 Other_Citation_Details: 30 m. resolution 

 Online_Linkage: www.aria.arizona.edu 

 Source_Time_Period_of_Content: 

 Time_Period_Information: 

 Single_Date/Time: 

 Calendar_Date: 06/06/1985 

 Source_Currentness_Reference: ground condition 

 Process_Step: 

 Process_Description: Geometric distortions were corrected by establishing a relationship 

between the satellite image and a Digital Orthophoto Quarter Quad (DOQQ) of the corresponding 

regions. Once these ground control points (GCP's) were established, the image is then 

converted, or rubbersheeted to the new coordinate system through a nearest neighbor 

resampling regime using a 3rd order polynomial, through a process called rectification. 

Identification of features by remote sensing involves computer software with the ability to identify 

pixels based upon their numerical properties and analyze them for statistical estimates. Using 

clustering methods to assign each pixel in an image to spectral classes, of which it has no 

foreknowledge, is called unsupervised classification. These procedures were applied to 

determine the location of the spectral classes into which the pixels are assigned. The analyst, 

who confirms these classes with information from ground maps, aerial photos, and ground visits, 

then identifies the output classes. Estimates of urban sprawl have been quantified by means of 

digitizing the urban extent area from the processed image. 

 Process_Date: 05/03 

Spatial_Data_Organization_Information: 

 Direct_Spatial_Reference_Method: Vector 

 Point_and_Vector_Object_Information: 

 SDTS_Terms_Description: 

 SDTS_Point_and_Vector_Object_Type: G-polygon 

 Point_and_Vector_Object_Count: 14 

Spatial_Reference_Information: 

 Horizontal_Coordinate_System_Definition: 

 Planar: 

 Grid_Coordinate_System: 

 Grid_Coordinate_System_Name: Universal Transverse Mercator 

 Universal_Transverse_Mercator: 

 UTM_Zone_Number: 12 

 Transverse_Mercator: 

 Scale_Factor_at_Central_Meridian: 0.999600 

 Longitude_of_Central_Meridian: -111.000000 

 Latitude_of_Projection_Origin: 0.000000 

 False_Easting: 500000.000000 

 False_Northing: 0.000000 

 Planar_Coordinate_Information: 

 Planar_Coordinate_Encoding_Method: coordinate pair 

 Coordinate_Representation: 

 Abscissa_Resolution: 0.000016 

 Ordinate_Resolution: 0.000016 

 Planar_Distance_Units: meters 

 Geodetic_Model: 

 Horizontal_Datum_Name: North American Datum of 1983 

 Ellipsoid_Name: Geodetic Reference System 80 

 Semi-major_Axis: 6378137.000000 

 Denominator_of_Flattening_Ratio: 298.257222 

Entity_and_Attribute_Information: 

 Detailed_Description: 

62
 Entity_Type: 

 Entity_Type_Label: 1995 

 Entity_Type_Definition: Polygon used to portray urban extent in 1995 

 Attribute: 

 Attribute_Label: FID 

 Attribute_Definition: Internal feature number. 

 Attribute_Definition_Source: ESRI 

 Attribute_Domain_Values: 

 Unrepresentable_Domain: Sequential unique whole numbers that are automatically 

generated. 

 Attribute: 

 Attribute_Label: Shape 

 Attribute_Definition: Feature geometry. 

 Attribute_Definition_Source: ESRI 

 Attribute_Domain_Values: 

 Unrepresentable_Domain: Coordinates defining the features. 

 Attribute: 

 Attribute_Label: ID 

 Attribute: 

 Attribute_Label: GRIDCODE 

Distribution_Information: 

 Distributor: 

 Contact_Information: 

 Contact_Organization_Primary: 

 Contact_Organization: U.S. Geological Survey 

 Resource_Description: Downloadable Data 

 Standard_Order_Process: 

 Digital_Form: 

 Digital_Transfer_Information: 

 Transfer_Size: 0.016 

Metadata_Reference_Information: 

 Metadata_Date: 20031204 

 Metadata_Contact: 

 Contact_Information: 

 Contact_Person_Primary: 

 Contact_Person: Laura M. Norman 

 Contact_Organization: U.S. Geological Survey 

 Contact_Position: Cartographer, GIS Specialist 

 Contact_Address: 

 Address_Type: mailing address 

 Address: 520 N Park Ave, Ste #355 

 City: Tucson 

 State_or_Province: AZ 

 Postal_Code: 85719 

 Country: U.S.A 

 Contact_Voice_Telephone: 520 670 5510 

 Contact_Facsimile_Telephone: 520 670 5571 

 Contact_Electronic_Mail_Address: lmbrady@usgs.gov 

 Hours_of_Service: 9-5 

 Metadata_Standard_Name: FGDC Content Standards for Digital Geospatial Metadata 

 Metadata_Standard_Version: FGDC-STD-001-1998 

 Metadata_Time_Convention: local time 

 Metadata_Access_Constraints: none 

 Metadata_Use_Constraints: none 

 Metadata_Extensions: 

 Online_Linkage: http://www.esri.com/metadata/esriprof80.html 

63
 Profile_Name: ESRI Metadata Profile 

64
2000 

Identification_Information: 

 Citation: 

 Citation_Information: 

 Originator: Laura M. Norman 

 Publication_Date: 12/03 

 Title: 2000 Urban Extent of Douglas, AZ/Agua Prieta, Sonora 

 Geospatial_Data_Presentation_Form: vector digital data 

 Online Linkage: http://codd.art.srnr.arizona.edu/colonias 

 Larger_Work_Citation: 

 Citation_Information: 

 Originator: Norman, Laura M., Donelson, Angela J., Pfeifer, Edwin, Lam, Alven H., and 

Osborn, Kenneth J. 

 Publication_Date: 12/03 

 Title: Analyses of Urban Sprawl and Colonias Development in Douglas, Arizona & Agua 

Prieta, Sonora on the United States–Mexico Border; A Process Application using GIS and 

Remote Sensing 

 Geospatial_Data_Presentation_Form: vector digital data 

 Series_Information: 

 Series_Name: Open File Report 

 Issue_Identification: OFR-03-XXX 

 Publication_Information: 

 Publication_Place: Menlo Park, CA 

 Publisher: USGS 

 Online_Linkage: <http://wgsc.wr.usgs.gov/wrgeog_pubs/> 

 Description: 

 Abstract: Landsat imagery describing the Douglas, AZ and Agua Prieta, Sonora area (Path 35 

Row 38) was acquired for place name Sierra Vista at 04/05/2000 from the Arizona Regional 

Image Archive, (http://aria.arizona.edu), an on-line interdisciplinary resource system for digital 

image and map data for the Sonoran desert region, including the U.S. Southwest and northern 

Mexico. The urban extent of the twin cities are was extracted from the satellite image. 

 Purpose: Image processing and subsequent temporal remote sensing analysis was done to 

quantify urban growth stemming from human settlement. 

 Time_Period_of_Content: 

 Time_Period_Information: 

 Single_Date/Time: 

 Calendar_Date: 04/05/2000 

 Currentness_Reference: 2000 

 Status: 

 Progress: Complete 

 Maintenance_and_Update_Frequency: None planned 

 Spatial_Domain: 

 Bounding_Coordinates: 

 West_Bounding_Coordinate: -109.568835 

 East_Bounding_Coordinate: -109.512347 

 North_Bounding_Coordinate: 31.378782 

 South_Bounding_Coordinate: 31.295863 

 Keywords: 

 Theme: 

 Theme_Keyword_Thesaurus: none 

 Theme_Keyword: Land use 

 Theme_Keyword: Urban Sprawl 

65
 Place: 

 Place_Keyword: Arizona 

 Place_Keyword: Sonora 

 Place_Keyword: Douglas, AZ 

 Place_Keyword: Agua Prieta, Sonora 

 Use_Constraints: This digital database is not meant to be used or displayed at any scale larger 

than 1:24,000 (for example, 1:12,000). Any hardcopies utilizing this dataset shall clearly 

indicate their source. If the user has modified the data in any way, he is obligated to describe the 

types of modifications he has performed on the hardcopy map. User specifically agrees not to 

misrepresent this dataset nor to imply that changes he made were approved by the U.S. 

Geological Survey. 

 Point_of_Contact: 

 Contact_Information: 

 Contact_Person_Primary: 

 Contact_Person: Laura M. Norman 

 Contact_Organization: U.S. Geological Survey 

 Contact_Position: Cartographer, GIS Specialist 

 Contact_Address: 

 Address_Type: mailing address 

 Address: 520 N Park Ave, Ste #355 

 City: Tucson 

 State_or_Province: AZ 

 Postal_Code: 85719 

 Country: U.S.A 

 Contact_Voice_Telephone: 520 670 5510 

 Contact_Facsimile_Telephone: 520 670 5571 

 Contact_Electronic_Mail_Address: lmbrady@usgs.gov 

 Hours_of_Service: 9-5 

 Native_Data_Set_Environment: Microsoft Windows 2000 Version 5.0 (Build 2195) Service Pack 

4; ESRI ArcCatalog 8.2.0.700 

 Cross_Reference: 

 Citation_Information: 

 Publication_Information: 

 Larger_Work_Citation: 

 Citation_Information: 

 Publication_Information: 

 Publication_Place: USGS 

Data_Quality_Information: 

 Attribute_Accuracy: 

 Attribute_Accuracy_Report: Although the satellite data were all acquired from the Landsat 

system, different sensors were accessed through the years, which may lead to some discrepancy 

in analysis. The Landsat 7 Enhanced Thematic Mapper Plus (ETM+) MRLC data was acquired at 

30 m resolution in year 2000. Therefore, we were limited by pixel sixe. Other error that could have 

been introduced includes error due to rubbersheeting algorithm applied to the dataset. 

 Lineage: 

 Source_Information: 

 Source_Citation: 

 Citation_Information: 

 Publication_Date: Unknown 

 Title: Landsat 7 ETM + 

 Geospatial_Data_Presentation_Form: remote-sensing image 

 Other_Citation_Details: 30 m. resolution 

 Online_Linkage: www.aria.arizona.edu 

 Source_Time_Period_of_Content: 

 Time_Period_Information: 

 Single_Date/Time: 

66
 Calendar_Date: 06/06/1985 

 Source_Currentness_Reference: ground condition 

 Process_Step: 

 Process_Description: Geometric distortions were corrected by establishing a relationship 

between the satellite image and a Digital Orthophoto Quarter Quad (DOQQ) of the corresponding 

regions. Once these ground control points (GCP's) were established, the image is then 

converted, or rubbersheeted to the new coordinate system through a nearest neighbor 

resampling regime using a 3rd order polynomial, through a process called rectification. 

Identification of features by remote sensing involves computer software with the ability to identify 

pixels based upon their numerical properties and analyze them for statistical estimates. Using 

clustering methods to assign each pixel in an image to spectral classes, of which it has no 

foreknowledge, is called unsupervised classification. These procedures were applied to 

determine the location of the spectral classes into which the pixels are assigned. The analyst, 

who confirms these classes with information from ground maps, aerial photos, and ground visits, 

then identifies the output classes. Estimates of urban sprawl have been quantified by means of 

digitizing the urban extent area from the processed image. 

 Process_Date: 05/03 

Spatial_Data_Organization_Information: 

 Direct_Spatial_Reference_Method: Vector 

 Point_and_Vector_Object_Information: 

 SDTS_Terms_Description: 

 SDTS_Point_and_Vector_Object_Type: G-polygon 

 Point_and_Vector_Object_Count: 33 

Spatial_Reference_Information: 

 Horizontal_Coordinate_System_Definition: 

 Planar: 

 Grid_Coordinate_System: 

 Grid_Coordinate_System_Name: Universal Transverse Mercator 

 Universal_Transverse_Mercator: 

 UTM_Zone_Number: 12 

 Transverse_Mercator: 

 Scale_Factor_at_Central_Meridian: 0.999600 

 Longitude_of_Central_Meridian: -111.000000 

 Latitude_of_Projection_Origin: 0.000000 

 False_Easting: 500000.000000 

 False_Northing: 0.000000 

 Planar_Coordinate_Information: 

 Planar_Coordinate_Encoding_Method: coordinate pair 

 Coordinate_Representation: 

 Abscissa_Resolution: 0.000016 

 Ordinate_Resolution: 0.000016 

 Planar_Distance_Units: meters 

 Geodetic_Model: 

 Horizontal_Datum_Name: North American Datum of 1983 

 Ellipsoid_Name: Geodetic Reference System 80 

 Semi-major_Axis: 6378137.000000 

 Denominator_of_Flattening_Ratio: 298.257222 

Entity_and_Attribute_Information: 

 Detailed_Description: 

 Entity_Type: 

 Entity_Type_Label: 2000 

 Entity_Type_Definition: Polygon used to portray urban extent in 2000 

 Attribute: 

 Attribute_Label: FID 

 Attribute_Definition: Internal feature number. 

 Attribute_Definition_Source: ESRI 

67
 Attribute_Domain_Values: 

 Unrepresentable_Domain: Sequential unique whole numbers that are automatically 

generated. 

 Attribute: 

 Attribute_Label: Shape 

 Attribute_Definition: Feature geometry. 

 Attribute_Definition_Source: ESRI 

 Attribute_Domain_Values: 

 Unrepresentable_Domain: Coordinates defining the features. 

 Attribute: 

 Attribute_Label: ID 

Distribution_Information: 

 Distributor: 

 Contact_Information: 

 Contact_Organization_Primary: 

 Contact_Organization: U.S. Geological Survey 

 Resource_Description: Downloadable Data 

 Distribution_Liability: 

 The U.S. Geological Survey (USGS) provides these geographic data "as is." The USGS 

makes no guarantee or warranty concerning the accuracy of information contained in the 

geographic data. The USGS further makes no warranties, either expressed or implied, as to any 

other matter whatsoever, including, without limitation, the condition of the product or its fitness for 

any particular purpose. The burden for determining fitness for use lies entirely with the user. 

Although these data have been processed successfully on computers at the USGS, no warranty, 

expressed or implied, is made by the USGS regarding the use of these data on any other system, 

nor does the fact of distribution constitute or imply any such warranty. 

 In no event shall the USGS have any liability whatsoever for payment of any consequential, 

incidental, indirect, special, or tort damages of any kind, including, but not limited to, any loss of 

profits arising out of use of or reliance on the geographic data or arising out of the delivery, 

installation, operation, or support by USGS. 

 Standard_Order_Process: 

 Digital_Form: 

 Digital_Transfer_Information: 

 Transfer_Size: 0.016 

Metadata_Reference_Information: 

 Metadata_Date: 20031205 

 Metadata_Contact: 

 Contact_Information: 

 Contact_Person_Primary: 

 Contact_Person: Laura M. Norman 

 Contact_Organization: U.S. Geological Survey 

 Contact_Position: Cartographer, GIS Specialist 

 Contact_Address: 

 Address_Type: mailing address 

 Address: 520 N Park Ave, Ste #355 

 City: Tucson 

 State_or_Province: AZ 

 Postal_Code: 85719 

 Country: U.S.A 

 Contact_Voice_Telephone: 520 670 5510 

 Contact_Facsimile_Telephone: 520 670 5571 

 Contact_Electronic_Mail_Address: lmbrady@usgs.gov 

 Hours_of_Service: 9-5 

 Metadata_Standard_Name: FGDC Content Standards for Digital Geospatial Metadata 

 Metadata_Standard_Version: FGDC-STD-001-1998 

68
 Metadata_Time_Convention: local time 

 Metadata_Access_Constraints: none 

 Metadata_Use_Constraints: none 

 Metadata_Extensions: 

 Online_Linkage: http://www.esri.com/metadata/esriprof80.html 

 Profile_Name: ESRI Metadata Profile 

69
Colonias in Agua Prieta, Sonora 

Identification_Information: 

 Citation: 

 Citation_Information: 

 Originator: Laura M. Norman 

 Publication_Date: 07/03/03 

 Title: Colonias in Agua Prieta, Sonora 

 Geospatial_Data_Presentation_Form: vector digital data 

 Online Linkage: http://codd.art.srnr.arizona.edu/colonias 

 Larger_Work_Citation: 

 Citation_Information: 

 Originator: Norman, Laura M., Donelson, Angela J., Pfeifer, Edwin, Lam, Alven H., and 

Osborn, Kenneth J. 

 Publication_Date: 12/03 

 Title: Analyses of Urban Sprawl and Colonias Development in Douglas, Arizona & Agua 

Prieta, Sonora on the United States–Mexico Border; A Process Application using GIS and 

Remote Sensing 

 Geospatial_Data_Presentation_Form: vector digital data 

 Series_Information: 

 Series_Name: Open File Report 

 Issue_Identification: OFR-03-XXX 

 Publication_Information: 

 Publication_Place: Menlo Park, CA 

 Publisher: USGS 

 Online_Linkage: <http://wgsc.wr.usgs.gov/wrgeog_pubs/> 

 Description: 

 Abstract: A suitability/ capability analysis (SCA) was implemented based on the housing and 

infrastructure suitability and/or capability of given areas to support colonias in Agua Prieta, 

Sonora. 

 Purpose: Colonias designation was done in Agua Prieta, Sonora to identify colonias-like 

neighborhoods in the area to make those neighborhoods recognizable to apply for funding 

 Time_Period_of_Content: 

 Time_Period_Information: 

 Single_Date/Time: 

 Currentness_Reference: 2003 

 Status: 

 Progress: Complete 

 Maintenance_and_Update_Frequency: None planned 

 Spatial_Domain: 

 Bounding_Coordinates: 

 West_Bounding_Coordinate: -109.568835 

 East_Bounding_Coordinate: -109.512347 

 North_Bounding_Coordinate: 31.378782 

 South_Bounding_Coordinate: 31.295863 

 Keywords: 

 Theme: 

 Theme_Keyword_Thesaurus: none 

 Theme_Keyword: Colonias 

 Theme_Keyword: Agua Prieta 

 Place: 

 Place_Keyword_Thesaurus: none 

 Place_Keyword: Agua Prieta 

 Place_Keyword: Sonora 

70
 Place_Keyword: Mexico

 Use_Constraints: This digital database is not meant to be used or displayed at any scale larger 

than 1:24,000 (for example, 1:12,000). Any hardcopies utilizing this dataset shall clearly indicate 

their source. If the user has modified the data in any way, he is obligated to describe the types of 

modifications he has performed on the hardcopy map. User specifically agrees not to 

misrepresent this dataset nor to imply that changes he made were approved by the U.S. 

Geological Survey 

 Point_of_Contact: 

 Contact_Information: 

 Contact_Person_Primary: 

 Contact_Person: Laura M. Norman 

 Contact_Organization: U.S. Geological Survey 

 Contact_Position: Cartographer, GIS Specialist 

 Contact_Address: 

 Address_Type: mailing address 

 Address: 520 N Park Ave, Ste #355 

 City: Tucson 

 State_or_Province: AZ 

 Postal_Code: 85719 

 Country: U.S.A 

 Contact_Voice_Telephone: 520 670 5510 

 Contact_Facsimile_Telephone: 520 670 5571 

 Contact_Electronic_Mail_Address: lmbrady@usgs.gov 

 Hours_of_Service: 9-5 

 Data_Set_Credit: In the municipal of Agua Prieta, Silvia Villalobos de Zuñiga (director of the 

Agua Prieta's National System for the Integral Development of the Family (DIF) and sister to the 

Mayor of Agua Prieta, Irma Villalobos de Terán), Del Cabarga (dual citizen and coordinator for 

Take to the Hills non-profit org), & Reverend Jesus Gallegos (minister at Lily of the Valley 

Presbyterian Church in Agua Prieta, Mexico affiliate of the Frontera de Cristo border ministry) 

identified the poorest neighborhoods (barrios pobres) to call "colonias" for this project. 

 Native_Data_Set_Environment: Microsoft Windows 2000 Version 5.0 (Build 2195) Service Pack 

4; ESRI ArcCatalog 8.2.0.700 

 Cross_Reference: 

 Citation_Information: 

 Publication_Information: 

 Larger_Work_Citation: 

 Citation_Information: 

 Publication_Information: 

 Publication_Place: USGS 

Data_Quality_Information: 

 Attribute_Accuracy: 

 Attribute_Accuracy_Report: While the boundaries are thought to be most accurate according to 

the people who were involved in their deliniation, there were no legal boundaries used to define 

the colonias adataset. 

 Lineage: 

 Source_Information: 

 Source_Citation: 

 Citation_Information: 

 Source_Scale_Denominator: 1:24,000 

 Source_Time_Period_of_Content: 

 Time_Period_Information: 

 Single_Date/Time: 

 Process_Step: 

 Process_Description: Local representatives were asked to draw boundaries on hard copy 

print out maps describing the roads, sewer, and water infrastructure overlain on aerial photos of 

their community. These approximations were based upon previous knowledge and familiarity 

71
with the most impoverished and underprivileged areas known to them at that time. These 

polygons boundaries were then digitized and attributed. 

 Process_Date: 06/03 

Spatial_Data_Organization_Information: 

 Direct_Spatial_Reference_Method: Vector 

 Point_and_Vector_Object_Information: 

 SDTS_Terms_Description: 

 SDTS_Point_and_Vector_Object_Type: G-polygon 

 Point_and_Vector_Object_Count: 8 

Spatial_Reference_Information: 

 Horizontal_Coordinate_System_Definition: 

 Planar: 

 Grid_Coordinate_System: 

 Grid_Coordinate_System_Name: Universal Transverse Mercator 

 Universal_Transverse_Mercator: 

 UTM_Zone_Number: 12 

 Transverse_Mercator: 

 Scale_Factor_at_Central_Meridian: 0.999600 

 Longitude_of_Central_Meridian: -111.000000 

 Latitude_of_Projection_Origin: 0.000000 

 False_Easting: 500000.000000 

 False_Northing: 0.000000 

 Planar_Coordinate_Information: 

 Planar_Coordinate_Encoding_Method: coordinate pair 

 Coordinate_Representation: 

 Abscissa_Resolution: 0.000016 

 Ordinate_Resolution: 0.000016 

 Planar_Distance_Units: meters 

 Geodetic_Model: 

 Horizontal_Datum_Name: North American Datum of 1983 

 Ellipsoid_Name: Geodetic Reference System 80 

 Semi-major_Axis: 6378137.000000 

 Denominator_of_Flattening_Ratio: 298.257222 

Entity_and_Attribute_Information: 

 Detailed_Description: 

 Entity_Type: 

 Entity_Type_Label: Colonias 

 Entity_Type_Definition: Colonias were defined by the Cranston-Gonzales Act of 1990 as rural 

communities and neighborhoods located within 150 miles of the United States–Mexican border. 

Some colonias may be entire border communities, while others are comprised of neighborhoods 

within incorporated communities. They lack adequate infrastructure (sewer or water lines) and/or 

housing.Colonias were defined by the Cranston-Gonzales Act of 1990 as rural communities and 

neighborhoods located within 150 miles of the United States–Mexican border. Some colonias 

may be entire border communities, while others are comprised of neighborhoods within 

incorporated communities. They lack adequate infrastructure (sewer or water lines) and/or 

housing. 

 Entity_Type_Definition_Source: (http://www.hud.gov/groups/frmwrkcoln/whatcol.cfm). 

 Attribute: 

 Attribute_Label: FID 

 Attribute_Definition: Internal feature number. 

 Attribute_Definition_Source: ESRI 

 Attribute_Domain_Values: 

 Unrepresentable_Domain: Sequential unique whole numbers that are automatically 

generated. 

 Attribute: 

 Attribute_Label: Shape 

72
 Attribute_Definition: Feature geometry. 

 Attribute_Definition_Source: ESRI 

 Attribute_Domain_Values: 

 Unrepresentable_Domain: Coordinates defining the features. 

 Attribute: 

 Attribute_Label: ID 

 Attribute: 

 Attribute_Label: Name 

 Attribute_Definition: Name of colonia 

 Attribute_Definition_Source: Local interpretation 

Distribution_Information: 

 Distributor: 

 Contact_Information: 

 Contact_Organization_Primary: 

 Contact_Organization: U.S. Geological Survey 

 Resource_Description: Downloadable Data 

 Distribution_Liability: 

 The U.S. Geological Survey (USGS) provides these geographic data "as is." The USGS 

makes no guarantee or warranty concerning the accuracy of information contained in the 

geographic data. The USGS further makes no warranties, either expressed or implied, as to any 

other matter whatsoever, including, without limitation, the condition of the product or its fitness for 

any particular purpose. The burden for determining fitness for use lies entirely with the user. 

Although these data have been processed successfully on computers at the USGS, no warranty, 

expressed or implied, is made by the USGS regarding the use of these data on any other system, 

nor does the fact of distribution constitute or imply any such warranty. 

 In no event shall the USGS have any liability whatsoever for payment of any consequential, 

incidental, indirect, special, or tort damages of any kind, including, but not limited to, any loss of 

profits arising out of use of or reliance on the geographic data or arising out of the delivery, 

installation, operation, or support by USGS. 

 Standard_Order_Process: 

 Digital_Form: 

 Digital_Transfer_Information: 

 Transfer_Size: 0.016 

Metadata_Reference_Information: 

 Metadata_Date: 20031205 

 Metadata_Contact: 

 Contact_Information: 

 Contact_Person_Primary: 

 Contact_Person: Laura M. Norman 

 Contact_Organization: U.S. Geological Survey 

 Contact_Position: Cartographer, GIS Specialist 

 Contact_Address: 

 Address_Type: mailing address 

 Address: 520 N Park Ave, Ste #355 

 City: Tucson 

 State_or_Province: AZ 

 Postal_Code: 85719 

 Country: U.S.A 

 Contact_Voice_Telephone: 520 670 5510 

 Contact_Facsimile_Telephone: 520 670 5571 

 Contact_Electronic_Mail_Address: lmbrady@usgs.gov 

 Hours_of_Service: 9-5 

 Metadata_Standard_Name: FGDC Content Standards for Digital Geospatial Metadata 

 Metadata_Standard_Version: FGDC-STD-001-1998 

 Metadata_Time_Convention: local time 

73
 Metadata_Access_Constraints: none 

 Metadata_Use_Constraints: none 

 Metadata_Extensions: 

 Online_Linkage: http://www.esri.com/metadata/esriprof80.html 

 Profile_Name: ESRI Metadata Profile 

74
Waterlines in Agua Prieta, Sonora 

Identification_Information: 

 Citation: 

 Citation_Information: 

 Originator: Laura M. Norman 

 Publication_Date: 12/03 

 Title: Waterlines in Agua Prieta, Sonora 

 Geospatial_Data_Presentation_Form: vector digital data 

 Online Linkage: http://codd.art.srnr.arizona.edu/colonias 

 Larger_Work_Citation: 

 Citation_Information: 

 Originator: Norman, Laura M., Donelson, Angela J., Pfeifer, Edwin, Lam, Alven H., and 

Osborn, Kenneth J. 

 Publication_Date: 12/03 

 Title: Analyses of Urban Sprawl and Colonias Development in Douglas, Arizona & Agua 

Prieta, Sonora on the United States–Mexico Border; A Process Application using GIS and 

Remote Sensing 

 Geospatial_Data_Presentation_Form: vector digital data 

 Series_Information: 

 Series_Name: Open File Report 

 Issue_Identification: OFR-03-XXX 

 Publication_Information: 

 Publication_Place: Menlo Park, CA 

 Publisher: USGS 

 Online_Linkage: http://wgsc.wr.usgs.gov/wrgeog_pubs/ 

 Description: 

 Abstract: Data gathered for report (Comisión De Cooperación Ecológica Fronteriza 

(COCEF/BECC)) was systematically translated and synthesized. AutoCAD drawings describing 

the the waterlines in Agua Prieta, Sonora were rectified and digitized within a GIS. These 

geographic features describing the Municipal of Agua Prieta were automated into the geospatial 

database. 

 Purpose: TThe map of waterlines was used to help define colonias. 

 Time_Period_of_Content: 

 Time_Period_Information: 

 Single_Date/Time: 

 Calendar_Date: 12/03 

 Currentness_Reference: publication date 

 Status: 

 Progress: Complete 

 Maintenance_and_Update_Frequency: None planned 

 Spatial_Domain: 

 Bounding_Coordinates: 

 West_Bounding_Coordinate: -109.569582 

 East_Bounding_Coordinate: -109.510386 

 North_Bounding_Coordinate: 31.334005 

 South_Bounding_Coordinate: 31.303353 

 Keywords: 

 Theme: 

 Theme_Keyword_Thesaurus: none 

 Theme_Keyword: Agua Prieta 

 Theme_Keyword: Infrastructure 

 Theme_Keyword: COCEF/BECC 

75
 Place: 

 Place_Keyword_Thesaurus: none 

 Place_Keyword: Waterlines

 Place_Keyword: Agua Prieta 

 Place_Keyword: Infrastructure 

 Place_Keyword: Sonora 

 Use_Constraints: This digital database is not meant to be used or displayed at any scale larger 

than 1:24,000 (for example, 1:12,000). Any hardcopies utilizing this dataset shall clearly indicate 

their source. If the user has modified the data in any way, he is obligated to describe the types of 

modifications he has performed on the hardcopy map. User specifically agrees not to 

misrepresent this dataset nor to imply that changes he made were approved by the U.S. 

Geological Survey. 

 Point_of_Contact: 

 Contact_Information: 

 Contact_Person_Primary: 

 Contact_Person: Laura M. Norman 

 Contact_Organization: U.S. Geological Survey 

 Contact_Position: Cartographer, GIS Specialist 

 Contact_Address: 

 Address_Type: mailing address 

 Address: 520 N Park Ave, Ste #355 

 City: Tucson 

 State_or_Province: AZ 

 Postal_Code: 85719 

 Country: U.S.A 

 Contact_Voice_Telephone: 520 670 5510 

 Contact_Facsimile_Telephone: 520 670 5571 

 Contact_Electronic_Mail_Address: lmbrady@usgs.gov 

 Hours_of_Service: 9-5 

 Native_Data_Set_Environment: Microsoft Windows 2000 Version 5.0 (Build 2195) Service Pack 

4; ESRI ArcCatalog 8.2.0.700 

 Cross_Reference: 

 Citation_Information: 

Data_Quality_Information: 

 Attribute_Accuracy: 

 Attribute_Accuracy_Report: Accuracy is based on AutoCAD drawings from 1998. 

 Completeness_Report: This information was created according to data compiled in 1998. 

 Lineage: 

 Source_Information: 

 Source_Citation: 

 Citation_Information: 

 Originator: Comisión De Cooperación Ecológica Fronteriza (COCEF/BECC) 

 Publication_Date: 1998 

 Title: Agua Prieta, Sonora, Plan Maestro; Para el Mejoramiento de los Servicios de Agua 

Potable, Alcantarillado y Saneamiento de la Ciudad de Agua Prieta, Son. Y Levatamiento de 

Redes Hidraulicas. 

 Geospatial_Data_Presentation_Form: document 

 Other_Citation_Details: CONTA 98-023 

 Source_Time_Period_of_Content: 

 Time_Period_Information: 

 Single_Date/Time: 

 Calendar_Date: unknown 

 Source_Currentness_Reference: ground condition 

 Process_Step: 

 Process_Description: AutoCAD drawings were rectified in ArcView 3.3 using world files that 

were created according to known bounding coordinates. The data were exported into ArcGIS for 

76
processing. In ArcPlot coverages were generated utilizing drawing layers from AutoCAD created 

previously by COCEF/BECC in the master plan of the city. Coverages were exported to ArcEdit, 

cleaned and built. And in ArcINFO exported to shapefiles. 

 Process_Date: 05/03 

Spatial_Data_Organization_Information: 

 Direct_Spatial_Reference_Method: Vector 

 Point_and_Vector_Object_Information: 

 SDTS_Terms_Description: 

 SDTS_Point_and_Vector_Object_Type: String 

 Point_and_Vector_Object_Count: 1023 

Spatial_Reference_Information: 

 Horizontal_Coordinate_System_Definition: 

 Planar: 

 Grid_Coordinate_System: 

 Grid_Coordinate_System_Name: Universal Transverse Mercator 

 Universal_Transverse_Mercator: 

 UTM_Zone_Number: 12 

 Transverse_Mercator: 

 Scale_Factor_at_Central_Meridian: 0.999600 

 Longitude_of_Central_Meridian: -111.000000 

 Latitude_of_Projection_Origin: 0.000000 

 False_Easting: 500000.000000 

 False_Northing: 0.000000 

 Planar_Coordinate_Information: 

 Planar_Coordinate_Encoding_Method: coordinate pair 

 Coordinate_Representation: 

 Abscissa_Resolution: 0.000008 

 Ordinate_Resolution: 0.000008 

 Planar_Distance_Units: meters 

 Geodetic_Model: 

 Horizontal_Datum_Name: North American Datum of 1983 

 Ellipsoid_Name: Geodetic Reference System 80 

 Semi-major_Axis: 6378137.000000 

 Denominator_of_Flattening_Ratio: 298.257222 

 Vertical_Coordinate_System_Definition: 

 Altitude_System_Definition: 

 Altitude_Resolution: 0.000001 

 Altitude_Encoding_Method: Explicit elevation coordinate included with horizontal coordinates 

Entity_and_Attribute_Information: 

 Detailed_Description: 

 Entity_Type: 

 Entity_Type_Label: ap_waterlines 

 Attribute: 

 Attribute_Label: FID 

 Attribute_Definition: Internal feature number. 

 Attribute_Definition_Source: ESRI 

 Attribute_Domain_Values: 

 Unrepresentable_Domain: Sequential unique whole numbers that are automatically 

generated. 

 Attribute: 

 Attribute_Label: Shape 

 Attribute_Definition: Feature geometry. 

 Attribute_Definition_Source: ESRI 

 Attribute_Domain_Values: 

 Unrepresentable_Domain: Coordinates defining the features. 

 Attribute: 

77
 Attribute_Label: ENTITY 

 Attribute_Definition: This may have to do with diameter variation of the pipes. 

 Attribute: 

 Attribute_Label: LAYER 

 Attribute_Definition: AutoCAD color assigned to pipe. 

 Attribute: 

 Attribute_Label: COLOR 

 Attribute_Definition: Well access number. 

 Attribute: 

 Attribute_Label: AREA_POZO 

Distribution_Information: 

 Distributor: 

 Contact_Information: 

 Contact_Organization_Primary: 

 Contact_Organization: U.S. Geological Survey 

 Resource_Description: Downloadable Data 

 Distribution_Liability: 

 The U.S. Geological Survey (USGS) provides these geographic data "as is." The USGS makes 

no guarantee or warranty concerning the accuracy of information contained in the geographic 

data. The USGS further makes no warranties, either expressed or implied, as to any other matter 

whatsoever, including, without limitation, the condition of the product or its fitness for any 

particular purpose. The burden for determining fitness for use lies entirely with the user. Although 

these data have been processed successfully on computers at the USGS, no warranty, 

expressed or implied, is made by the USGS regarding the use of these data on any other system, 

nor does the fact of distribution constitute or imply any such warranty. 

 In no event shall the USGS have any liability whatsoever for payment of any consequential, 

incidental, indirect, special, or tort damages of any kind, including, but not limited to, any loss of 

profits arising out of use of or reliance on the geographic data or arising out of the delivery, 

installation, operation, or support by USGS. 

 Standard_Order_Process: 

 Digital_Form: 

 Digital_Transfer_Information: 

 Transfer_Size: 0.016 

Metadata_Reference_Information: 

 Metadata_Date: 20031205 

 Metadata_Contact: 

 Contact_Information: 

 Contact_Person_Primary: 

 Contact_Person: Laura M. Norman 

 Contact_Organization: U.S. Geological Survey 

 Contact_Position: Cartographer, GIS Specialist 

 Contact_Address: 

 Address_Type: mailing address 

 Address: 520 N Park Ave, Ste #355 

 City: Tucson 

 State_or_Province: AZ 

 Postal_Code: 85719 

 Country: U.S.A 

 Contact_Voice_Telephone: 520 670 5510 

 Contact_Facsimile_Telephone: 520 670 5571 

 Contact_Electronic_Mail_Address: lmbrady@usgs.gov 

 Hours_of_Service: 9-5 

 Metadata_Standard_Name: FGDC Content Standards for Digital Geospatial Metadata 

 Metadata_Standard_Version: FGDC-STD-001-1998 

 Metadata_Time_Convention: local time 

 Metadata_Access_Constraints: none 

78
 Metadata_Use_Constraints: none 

 Metadata_Extensions: 

 Online_Linkage: http://www.esri.com/metadata/esriprof80.html 

 Profile_Name: ESRI Metadata Profile 

79
Floodzones in Agua Prieta, Sonora 

Identification_Information: 

 Citation: 

 Citation_Information: 

 Originator: Laura M. Norman 

 Publication_Date: 07/03/03 

 Title: Floodzones in Agua Prieta, Sonora 

 Geospatial_Data_Presentation_Form: vector digital data 

 Online Linkage: http://codd.art.srnr.arizona.edu/colonias 

 Larger_Work_Citation: 

 Citation_Information: 

 Originator: Norman, Laura M., Donelson, Angela J., Pfeifer, Edwin, Lam, Alven H., and 

Osborn, Kenneth J. 

 Publication_Date: 12/03 

 Title: Analyses of Urban Sprawl and Colonias Development in Douglas, Arizona & Agua 

Prieta, Sonora on the United States–Mexico Border; A Process Application using GIS and 

Remote Sensing 

 Geospatial_Data_Presentation_Form: vector digital data 

 Series_Information: 

 Series_Name: Open File Report 

 Issue_Identification: OFR-03-XXX 

 Publication_Information: 

 Publication_Place: Menlo Park, CA 

 Publisher: USGS 

 Online_Linkage: http://wgsc.wr.usgs.gov/wrgeog_pubs/ 

 Description: 

 Abstract: Data gathered for report (Comisión De Cooperación Ecológica Fronteriza 

(COCEF/BECC)) was systematically translated and synthesized. AutoCAD drawings describing 

the floodzones in Agua Prieta, Sonora were rectified and digitized within a GIS. Geographic 

features describing the Municipal of Agua Prieta were automated into the geospatial database. 

 Purpose: This information was automated to assist in planning in the city of Agua Prieta, 

Sonora. 

 Time_Period_of_Content: 

 Time_Period_Information: 

 Single_Date/Time: 

 Calendar_Date: 12/03 

 Currentness_Reference: publication date 

 Status: 

 Progress: Complete 

 Maintenance_and_Update_Frequency: None planned 

 Spatial_Domain: 

 Bounding_Coordinates: 

 West_Bounding_Coordinate: -109.568835 

 East_Bounding_Coordinate: -109.512347 

 North_Bounding_Coordinate: 31.323972 

 South_Bounding_Coordinate: 31.295863 

 Keywords: 

 Theme: 

 Theme_Keyword_Thesaurus: none 

 Theme_Keyword: COCEF/BECC 

 Theme_Keyword: Floodzone 

 Place: 

80
 Place_Keyword_Thesaurus: none 

 Place_Keyword: Sonora 

 Place_Keyword: Agua Prieta 

 Place_Keyword: Mexico

 Use_Constraints: This digital database is not meant to be used or displayed at any scale larger 

than 1:24,000 (for example, 1:12,000). Any hardcopies utilizing this dataset shall clearly indicate 

their source. If the user has modified the data in any way, he is obligated to describe the types of 

modifications he has performed on the hardcopy map. User specifically agrees not to 

misrepresent this dataset nor to imply that changes he made were approved by the U.S. 

Geological Survey. 

 Point_of_Contact: 

 Contact_Information: 

 Contact_Person_Primary: 

 Contact_Person: Laura M. Norman 

 Contact_Organization: U.S. Geological Survey 

 Contact_Position: Cartographer, GIS Specialist 

 Contact_Address: 

 Address_Type: mailing address 

 Address: 520 N Park Ave, Ste#355 

 City: Tucson 

 State_or_Province: AZ 

 Postal_Code: 85719 

 Country: U.S.A 

 Contact_Voice_Telephone: 520 670 5510 

 Contact_Facsimile_Telephone: 520 670 5571 

 Contact_Electronic_Mail_Address: lmbrady@usgs.gov 

 Hours_of_Service: 9-5 

 Native_Data_Set_Environment: Microsoft Windows 2000 Version 5.0 (Build 2195) Service Pack 

4; ESRI ArcCatalog 8.2.0.700 

 Cross_Reference: 

 Citation_Information: 

Data_Quality_Information: 

 Attribute_Accuracy: 

 Attribute_Accuracy_Report: Dataset according to AutoCAD darwings done in 1998. 

 Lineage: 

 Source_Information: 

 Source_Citation: 

 Citation_Information: 

 Originator: Comisión De Cooperación Ecológica Fronteriza (COCEF/BECC) 

 Publication_Date: 1998 

 Title: Agua Prieta, Sonora, Plan Maestro; Para el Mejoramiento de los Servicios de Agua 

Potable, Alcantarillado y Saneamiento de la Ciudad de Agua Prieta, Son. Y Levatamiento de 

Redes Hidraulicas. 

 Geospatial_Data_Presentation_Form: document 

 Other_Citation_Details: CONTA 98-023 

 Source_Time_Period_of_Content: 

 Time_Period_Information: 

 Single_Date/Time: 

 Calendar_Date: unknown 

 Source_Currentness_Reference: ground condition 

 Process_Step: 

 Process_Description: AutoCAD drawings of floodzones in Agua Prieta were rectified in 

ArcView 3.3 using world files that were created according to known bounding coordinates. The 

data were exported into ArcGIS for processing. In ArcPlot coverages were generated utilizing 

drawing layers from AutoCAD created previously by COCEF/BECC in the master plan of the city. 

Coverages were exported to ArcEdit, cleaned and built. And in ArcINFO exported to shapefiles. 

81
 Process_Date: 05/03 

Spatial_Data_Organization_Information: 

 Direct_Spatial_Reference_Method: Vector 

 Point_and_Vector_Object_Information: 

 SDTS_Terms_Description: 

 SDTS_Point_and_Vector_Object_Type: String 

 Point_and_Vector_Object_Count: 45 

Spatial_Reference_Information: 

 Horizontal_Coordinate_System_Definition: 

 Planar: 

 Grid_Coordinate_System: 

 Grid_Coordinate_System_Name: Universal Transverse Mercator 

 Universal_Transverse_Mercator: 

 UTM_Zone_Number: 12 

 Transverse_Mercator: 

 Scale_Factor_at_Central_Meridian: 0.999600 

 Longitude_of_Central_Meridian: -111.000000 

 Latitude_of_Projection_Origin: 0.000000 

 False_Easting: 500000.000000 

 False_Northing: 0.000000 

 Planar_Coordinate_Information: 

 Planar_Coordinate_Encoding_Method: coordinate pair 

 Coordinate_Representation: 

 Abscissa_Resolution: 0.000008 

 Ordinate_Resolution: 0.000008 

 Planar_Distance_Units: meters 

 Geodetic_Model: 

 Horizontal_Datum_Name: North American Datum of 1983 

 Ellipsoid_Name: Geodetic Reference System 80 

 Semi-major_Axis: 6378137.000000 

 Denominator_of_Flattening_Ratio: 298.257222 

 Vertical_Coordinate_System_Definition: 

 Altitude_System_Definition: 

 Altitude_Resolution: 0.000001 

 Altitude_Encoding_Method: Explicit elevation coordinate included with horizontal coordinates 

Entity_and_Attribute_Information: 

 Detailed_Description: 

 Entity_Type: 

 Entity_Type_Label: ap_floodzone 

 Attribute: 

 Attribute_Label: FID 

 Attribute_Definition: Internal feature number. 

 Attribute_Definition_Source: ESRI 

 Attribute_Domain_Values: 

 Unrepresentable_Domain: Sequential unique whole numbers that are automatically 

generated. 

 Attribute: 

 Attribute_Label: Shape 

 Attribute_Definition: Feature geometry. 

 Attribute_Definition_Source: ESRI 

 Attribute_Domain_Values: 

 Unrepresentable_Domain: Coordinates defining the features. 

 Attribute: 

 Attribute_Label: ENTITY 

 Attribute: 

 Attribute_Label: LAYER 

82
 Attribute_Definition: Describes flood (INUNDATION) zones 

 Attribute: 

 Attribute_Label: COLOR 

 Attribute_Definition: That AutoCAD color assigned to floodzones. 

Distribution_Information: 

 Distributor: 

 Contact_Information: 

 Contact_Organization_Primary: 

 Contact_Organization: U.S. Geological Survey 

 Resource_Description: Downloadable Data 

 Distribution_Liability: The U.S. Geological Survey (USGS) provides these geographic data "as 

is." The USGS makes no guarantee or warranty concerning the accuracy of information 

contained in the geographic data. The USGS further makes no warranties, either expressed or 

implied, as to any other matter whatsoever, including, without limitation, the condition of the 

product or its fitness for any particular purpose. The burden for determining fitness for use lies 

entirely with the user. Although these data have been processed successfully on computers at 

the USGS, no warranty, expressed or implied, is made by the USGS regarding the use of these 

data on any other system, nor does the fact of distribution constitute or imply any such warranty. 

In no event shall the USGS have any liability whatsoever for payment of any consequential, 

incidental, indirect, special, or tort damages of any kind, including, but not limited to, any loss of 

profits arising out of use of or reliance on the geographic data or arising out of the delivery, 

installation, operation, or support by USGS. 

 Standard_Order_Process: 

 Digital_Form: 

 Digital_Transfer_Information: 

 Transfer_Size: 0.016 

Metadata_Reference_Information: 

 Metadata_Date: 20031205 

 Metadata_Contact: 

 Contact_Information: 

 Contact_Person_Primary: 

 Contact_Person: Laura M. Norman 

 Contact_Organization: U.S. Geological Survey 

 Contact_Position: Cartographer, GIS Specialist 

 Contact_Address: 

 Address_Type: mailing address 

 Address: 520 N Park Ave, Ste #355 

 City: Tucson 

 State_or_Province: AZ 

 Postal_Code: 85719 

 Country: U.S.A 

 Contact_Voice_Telephone: 520 670 5510 

 Contact_Facsimile_Telephone: 520 670 5571 

 Contact_Electronic_Mail_Address: lmbrady@usgs.gov 

 Hours_of_Service: 9-5 

 Metadata_Standard_Name: FGDC Content Standards for Digital Geospatial Metadata 

 Metadata_Standard_Version: FGDC-STD-001-1998 

 Metadata_Time_Convention: local time 

 Metadata_Access_Constraints: none 

 Metadata_Use_Constraints: none 

 Metadata_Extensions: 

 Online_Linkage: http://www.esri.com/metadata/esriprof80.html 

 Profile_Name: ESRI Metadata Profile 

 Metadata_Extensions: 

 Online_Linkage: http://www.esri.com/metadata/esriprof80.html 

 Profile_Name: ESRI Metadata Profile 

83
Sewerlines in Agua Prieta, Sonora 

Identification_Information: 

 Citation: 

 Citation_Information: 

 Originator: Laura M. Norman 

 Publication_Date: 12/03 

 Title: Sewerlines in Agua Prieta, Sonora 

 Geospatial_Data_Presentation_Form: vector digital data 

 Online Linkage: http://codd.art.srnr.arizona.edu/colonias 

 Larger_Work_Citation: 

 Citation_Information: 

 Originator: Norman, Laura M., Donelson, Angela J., Pfeifer, Edwin, Lam, Alven H., and 

Osborn, Kenneth J. 

 Publication_Date: 12/03 

 Title: Analyses of Urban Sprawl and Colonias Development in Douglas, Arizona & Agua 

Prieta, Sonora on the United States–Mexico Border; A Process Application using GIS and 

Remote Sensing 

 Geospatial_Data_Presentation_Form: vector digital data 

 Series_Information: 

 Series_Name: Open File Report 

 Issue_Identification: OFR-03-XXX 

 Publication_Information: 

 Publication_Place: Menlo Park, CA 

 Publisher: USGS 

 Online_Linkage: <http://wgsc.wr.usgs.gov/wrgeog_pubs/> 

 Description: 

 Abstract: Data gathered for report (Comisión De Cooperación Ecológica Fronteriza 

(COCEF/BECC)) was systematically translated and synthesized. AutoCAD drawings describing 

the sewerlines in Agua Prieta, Sonora were rectified and digitized within a GIS. Geographic 

features describing the Municipal of Agua Prieta were automated into the geospatial database. 

 Purpose: The map of sewerlines was used to help define colonias. 

 Time_Period_of_Content: 

 Time_Period_Information: 

 Single_Date/Time: 

 Calendar_Date: 12/03 

 Currentness_Reference: publication date 

 Status: 

 Progress: Complete 

 Maintenance_and_Update_Frequency: None planned 

 Spatial_Domain: 

 Bounding_Coordinates: 

 West_Bounding_Coordinate: -109.571534 

 East_Bounding_Coordinate: -109.497212 

 North_Bounding_Coordinate: 31.334142 

 South_Bounding_Coordinate: 31.296728 

 Keywords: 

 Theme: 

 Theme_Keyword_Thesaurus: none 

 Theme_Keyword: Infrastructure 

 Theme_Keyword: COCEF/BECC 

 Theme_Keyword: sewerlines 

 Place: 

84
 Place_Keyword_Thesaurus: none 

 Place_Keyword: Agua Preita 

 Place_Keyword: Sonora 

 Place_Keyword: Mexico

 Use_Constraints: This digital database is not meant to be used or displayed at any scale larger 

than 1:24,000 (for example, 1:12,000). Any hardcopies utilizing this dataset shall clearly indicate 

their source. If the user has modified the data in any way, he is obligated to describe the types of 

modifications he has performed on the hardcopy map. User specifically agrees not to 

misrepresent this dataset nor to imply that changes he made were approved by the U.S. 

Geological Survey. 

 Point_of_Contact: 

 Contact_Information: 

 Contact_Person_Primary: 

 Contact_Person: Laura M. Norman 

 Contact_Organization: U.S. Geological Survey 

 Contact_Position: Cartographer, GIS Specialist 

 Contact_Address: 

 Address_Type: mailing address 

 Address: 520 N Park Ave, Ste #355 

 City: Tucson 

 State_or_Province: AZ 

 Postal_Code: 85719 

 Country: U.S.A 

 Contact_Voice_Telephone: 520 670 5510 

 Contact_Facsimile_Telephone: 520 670 5571 

 Contact_Electronic_Mail_Address: lmbrady@usgs.gov 

 Hours_of_Service: 9-5 

 Native_Data_Set_Environment: Microsoft Windows 2000 Version 5.0 (Build 2195) Service Pack 

4; ESRI ArcCatalog 8.2.0.700 

 Cross_Reference: 

 Citation_Information: 

Data_Quality_Information: 

 Attribute_Accuracy: 

 Attribute_Accuracy_Report: Accuracy dependant on AutoCAD drawings from 1998. 

 Lineage: 

 Source_Information: 

 Source_Citation: 

 Citation_Information: 

 Originator: Comisión De Cooperación Ecológica Fronteriza (COCEF/BECC) 

 Publication_Date: 1998 

 Title: Agua Prieta, Sonora, Plan Maestro; Para el Mejoramiento de los Servicios de Agua 

Potable, Alcantarillado y Saneamiento de la Ciudad de Agua Prieta, Son. Y Levatamiento de 

Redes Hidraulicas. 

 Geospatial_Data_Presentation_Form: document 

 Other_Citation_Details: CONTA 98-023 

 Source_Time_Period_of_Content: 

 Time_Period_Information: 

 Single_Date/Time: 

 Calendar_Date: 1998 

 Source_Currentness_Reference: ground condition 

 Process_Step: 

 Process_Description: AutoCAD drawings of sewerlines in Agua Prieta, Sonora were rectified 

in ArcView 3.3 using world files that were created according to known bounding coordinates. The 

data were exported into ArcGIS for processing. In ArcPlot coverages were generated utilizing 

drawing layers from AutoCAD created previously by COCEF/BECC in the master plan of the city. 

Coverages were exported to ArcEdit, cleaned and built. And in ArcINFO exported to shapefiles. 

85
 Process_Date: 05/03 

Spatial_Data_Organization_Information: 

 Direct_Spatial_Reference_Method: Vector 

 Point_and_Vector_Object_Information: 

 SDTS_Terms_Description: 

 SDTS_Point_and_Vector_Object_Type: String 

 Point_and_Vector_Object_Count: 57 

Spatial_Reference_Information: 

 Horizontal_Coordinate_System_Definition: 

 Planar: 

 Grid_Coordinate_System: 

 Grid_Coordinate_System_Name: Universal Transverse Mercator 

 Universal_Transverse_Mercator: 

 UTM_Zone_Number: 12 

 Transverse_Mercator: 

 Scale_Factor_at_Central_Meridian: 0.999600 

 Longitude_of_Central_Meridian: -111.000000 

 Latitude_of_Projection_Origin: 0.000000 

 False_Easting: 500000.000000 

 False_Northing: 0.000000 

 Planar_Coordinate_Information: 

 Planar_Coordinate_Encoding_Method: coordinate pair 

 Coordinate_Representation: 

 Abscissa_Resolution: 0.000016 

 Ordinate_Resolution: 0.000016 

 Planar_Distance_Units: meters 

 Geodetic_Model: 

 Horizontal_Datum_Name: North American Datum of 1983 

 Ellipsoid_Name: Geodetic Reference System 80 

 Semi-major_Axis: 6378137.000000 

 Denominator_of_Flattening_Ratio: 298.257222 

 Vertical_Coordinate_System_Definition: 

 Altitude_System_Definition: 

 Altitude_Resolution: 0.000001 

 Altitude_Encoding_Method: Explicit elevation coordinate included with horizontal coordinates 

Entity_and_Attribute_Information: 

 Detailed_Description: 

 Entity_Type: 

 Entity_Type_Label: ap_sewerlines 

 Attribute: 

 Attribute_Label: FID 

 Attribute_Definition: Internal feature number. 

 Attribute_Definition_Source: ESRI 

 Attribute_Domain_Values: 

 Unrepresentable_Domain: Sequential unique whole numbers that are automatically 

generated. 

 Attribute: 

 Attribute_Label: Shape 

 Attribute_Definition: Feature geometry. 

 Attribute_Definition_Source: ESRI 

 Attribute_Domain_Values: 

 Unrepresentable_Domain: Coordinates defining the features. 

 Attribute: 

 Attribute_Label: ENTITY 

 Attribute: 

 Attribute_Label: LAYER 

86
 Attribute_Definition: This may have to do with the diameter of the pipes. 

 Attribute: 

 Attribute_Label: COLOR 

 Attribute_Definition: This is the color assigned to the attribute for AutoCAD drawings. 

Distribution_Information: 

 Distributor: 

 Contact_Information: 

 Contact_Organization_Primary: 

 Contact_Organization: U.S. Geological Survey 

 Resource_Description: Downloadable Data 

 Distribution_Liability: The U.S. Geological Survey (USGS) provides these geographic data "as 

is." The USGS makes no guarantee or warranty concerning the accuracy of information 

contained in the geographic data. The USGS further makes no warranties, either expressed or 

implied, as to any other matter whatsoever, including, without limitation, the condition of the 

product or its fitness for any particular purpose. The burden for determining fitness for use lies 

entirely with the user. Although these data have been processed successfully on computers at 

the USGS, no warranty, expressed or implied, is made by the USGS regarding the use of these 

data on any other system, nor does the fact of distribution constitute or imply any such warranty. 

In no event shall the USGS have any liability whatsoever for payment of any consequential, 

incidental, indirect, special, or tort damages of any kind, including, but not limited to, any loss of 

profits arising out of use of or reliance on the geographic data or arising out of the delivery, 

installation, operation, or support by USGS. 

 Standard_Order_Process: 

 Digital_Form: 

 Digital_Transfer_Information: 

 Transfer_Size: 0.016 

Metadata_Reference_Information: 

 Metadata_Date: 20031205 

 Metadata_Contact: 

 Contact_Information: 

 Contact_Person_Primary: 

 Contact_Person: Laura M. Norman 

 Contact_Organization: U.S. Geological Survey 

 Contact_Position: Cartographer, GIS Specialist 

 Contact_Address: 

 Address_Type: mailing address 

 Address: 520 N Park Ave, Ste #355 

 City: Tucson 

 State_or_Province: AZ 

 Postal_Code: 85719 

 Country: U.S.A 

 Contact_Voice_Telephone: 520 670 5510 

 Contact_Facsimile_Telephone: 520 670 5571 

 Contact_Electronic_Mail_Address: lmbrady@usgs.gov 

 Hours_of_Service: 9-5 

 Metadata_Standard_Name: FGDC Content Standards for Digital Geospatial Metadata 

 Metadata_Standard_Version: FGDC-STD-001-1998 

 Metadata_Time_Convention: local time 

 Metadata_Access_Constraints: none 

 Metadata_Use_Constraints: none 

 Metadata_Extensions: 

 Online_Linkage: http://www.esri.com/metadata/esriprof80.html 

 Profile_Name: ESRI Metadata Profile 

87
Wells in Agua Prieta, Sonora 

Identification_Information: 

 Citation: 

 Citation_Information: 

 Originator: Laura M. Norman 

 Publication_Date: 12/03 

 Title: Wells in Agua Prieta, Sonora 

 Geospatial_Data_Presentation_Form: vector digital data 

 Online Linkage: http://codd.art.srnr.arizona.edu/colonias 

 Larger_Work_Citation: 

 Citation_Information: 

 Originator: Norman, Laura M., Donelson, Angela J., Pfeifer, Edwin, Lam, Alven H., and 

Osborn, Kenneth J. 

 Publication_Date: 12/03 

 Title: Analyses of Urban Sprawl and Colonias Development in Douglas, Arizona & Agua 

Prieta, Sonora on the United States–Mexico Border; A Process Application using GIS and 

Remote Sensing 

 Geospatial_Data_Presentation_Form: vector digital data 

 Series_Information: 

 Series_Name: Open File Report 

 Issue_Identification: OFR-03-XXX 

 Publication_Information: 

 Publication_Place: Menlo Park, CA 

 Publisher: USGS 

 Online_Linkage: <http://wgsc.wr.usgs.gov/wrgeog_pubs/> 

 Description: 

 Abstract: Data gathered for report (Comisión De Cooperación Ecológica Fronteriza 

(COCEF/BECC)) was systematically translated and synthesized. AutoCAD drawings describing 

the wells in Agua Prieta, Sonora were rectified and digitized within a GIS. Geographic features 

describing the Municipal of Agua Prieta were automated into the geospatial database. 

 Purpose: The process was necessary to create real-time maps of the city's infrastructure for 

colonias designation. 

 Time_Period_of_Content: 

 Time_Period_Information: 

 Single_Date/Time: 

 Calendar_Date: unknown 

 Currentness_Reference: publication date 

 Status: 

 Progress: Complete 

 Maintenance_and_Update_Frequency: None planned 

 Spatial_Domain: 

 Bounding_Coordinates: 

 West_Bounding_Coordinate: -109.549092 

 East_Bounding_Coordinate: -109.521078 

 North_Bounding_Coordinate: 31.333764 

 South_Bounding_Coordinate: 31.306057 

 Keywords: 

 Theme: 

 Theme_Keyword_Thesaurus: none 

 Theme_Keyword: Infrastructure 

 Theme_Keyword: COCEF/BECC 

 Theme_Keyword: Wells 

 Place: 

88
 Place_Keyword_Thesaurus: none 

 Place_Keyword: Agua Prieta 

 Place_Keyword: Sonora 

 Place_Keyword: Mexico

 Use_Constraints: This digital database is not meant to be used or displayed at any scale larger 

than 1:24,000 (for example, 1:12,000). Any hardcopies utilizing this dataset shall clearly indicate 

their source. If the user has modified the data in any way, he is obligated to describe the types of 

modifications he has performed on the hardcopy map. User specifically agrees not to 

misrepresent this dataset nor to imply that changes he made were approved by the U.S. 

Geological Survey. 

 Point_of_Contact: 

 Contact_Information: 

 Contact_Person_Primary: 

 Contact_Person: Laura M. Norman 

 Contact_Organization: U.S. Geological Survey 

 Contact_Position: Cartographer, GIS Specialist 

 Contact_Address: 

 Address_Type: mailing address 

 Address: 520 N Park Ave, Ste #355 

 City: Tucson 

 State_or_Province: AZ 

 Postal_Code: 85719 

 Country: U.S.A 

 Contact_Voice_Telephone: 520 670 5510 

 Contact_Facsimile_Telephone: 520 670 5571 

 Contact_Electronic_Mail_Address: lmbrady@usgs.gov 

 Hours_of_Service: 9-5 

 Native_Data_Set_Environment: Microsoft Windows 2000 Version 5.0 (Build 2195) Service Pack 

4; ESRI ArcCatalog 8.2.0.700 

 Cross_Reference: 

 Citation_Information: 

Data_Quality_Information: 

 Attribute_Accuracy: 

 Attribute_Accuracy_Report: Localities were assigned in AutoCAD in 1998. 

 Completeness_Report: These wells are those that were represented in the cited document. It is 

not known if other wells exist. 

 Lineage: 

 Source_Information: 

 Source_Citation: 

 Citation_Information: 

 Originator: Comisión De Cooperación Ecológica Fronteriza (COCEF/BECC) 

 Publication_Date: 1998 

 Title: Agua Prieta, Sonora, Plan Maestro; Para el Mejoramiento de los Servicios de Agua 

Potable, Alcantarillado y Saneamiento de la Ciudad de Agua Prieta, Son. Y Levatamiento de 

Redes Hidraulicas. 

 Geospatial_Data_Presentation_Form: document 

 Other_Citation_Details: CONTA 98-023 

 Source_Time_Period_of_Content: 

 Time_Period_Information: 

 Single_Date/Time: 

 Calendar_Date: unknown 

 Source_Currentness_Reference: ground condition 

 Process_Step: 

 Process_Description: AutoCAD drawings of well locations in Agua Prieta, Sonora were 

rectified in ArcView 3.3 using world files that were created according to known bounding 

coordinates. The data was then exported into ArcGIS for processing. In ArcPlot coverages were 

89
generated utilizing drawing layers from AutoCAD created previously by COCEF/BECC in the 

master plan of the city. Coverages were exported to ArcEdit, cleaned and built. And in ArcINFO 

exported to shapefiles. 

 Process_Date: 05/03 

Spatial_Data_Organization_Information: 

 Direct_Spatial_Reference_Method: Vector 

 Point_and_Vector_Object_Information: 

 SDTS_Terms_Description: 

 SDTS_Point_and_Vector_Object_Type: Entity point 

 Point_and_Vector_Object_Count: 11 

Spatial_Reference_Information: 

 Horizontal_Coordinate_System_Definition: 

 Planar: 

 Grid_Coordinate_System: 

 Grid_Coordinate_System_Name: Universal Transverse Mercator 

 Universal_Transverse_Mercator: 

 UTM_Zone_Number: 12 

 Transverse_Mercator: 

 Scale_Factor_at_Central_Meridian: 0.999600 

 Longitude_of_Central_Meridian: -111.000000 

 Latitude_of_Projection_Origin: 0.000000 

 False_Easting: 500000.000000 

 False_Northing: 0.000000 

 Planar_Coordinate_Information: 

 Planar_Coordinate_Encoding_Method: coordinate pair 

 Coordinate_Representation: 

 Abscissa_Resolution: 0.000008 

 Ordinate_Resolution: 0.000008 

 Planar_Distance_Units: meters 

 Geodetic_Model: 

 Horizontal_Datum_Name: North American Datum of 1983 

 Ellipsoid_Name: Geodetic Reference System 80 

 Semi-major_Axis: 6378137.000000 

 Denominator_of_Flattening_Ratio: 298.257222 

 Vertical_Coordinate_System_Definition: 

 Altitude_System_Definition: 

 Altitude_Resolution: 0.000001 

 Altitude_Encoding_Method: Explicit elevation coordinate included with horizontal coordinates 

Entity_and_Attribute_Information: 

 Detailed_Description: 

 Entity_Type: 

 Entity_Type_Label: ap_wells 

 Attribute: 

 Attribute_Label: FID 

 Attribute_Definition: Internal feature number. 

 Attribute_Definition_Source: ESRI 

 Attribute_Domain_Values: 

 Unrepresentable_Domain: Sequential unique whole numbers that are automatically 

generated. 

 Attribute: 

 Attribute_Label: Shape 

 Attribute_Definition: Feature geometry. 

 Attribute_Definition_Source: ESRI 

 Attribute_Domain_Values: 

 Unrepresentable_Domain: Coordinates defining the features. 

 Attribute: 

90
 Attribute_Label: ID 

Distribution_Information: 

 Distributor: 

 Contact_Information: 

 Contact_Organization_Primary: 

 Contact_Organization: U.S. Geological Survey 

 Resource_Description: Downloadable Data 

 Distribution_Liability: The U.S. Geological Survey (USGS) provides these geographic data "as 

is." The USGS makes no guarantee or warranty concerning the accuracy of information 

contained in the geographic data. The USGS further makes no warranties, either expressed or 

implied, as to any other matter whatsoever, including, without limitation, the condition of the 

product or its fitness for any particular purpose. The burden for determining fitness for use lies 

entirely with the user. Although these data have been processed successfully on computers at 

the USGS, no warranty, expressed or implied, is made by the USGS regarding the use of these 

data on any other system, nor does the fact of distribution constitute or imply any such warranty. 

In no event shall the USGS have any liability whatsoever for payment of any consequential, 

incidental, indirect, special, or tort damages of any kind, including, but not limited to, any loss of 

profits arising out of use of or reliance on the geographic data or arising out of the delivery, 

installation, operation, or support by USGS. 

 Standard_Order_Process: 

 Digital_Form: 

 Digital_Transfer_Information: 

 Transfer_Size: 0.016 

Metadata_Reference_Information: 

 Metadata_Date: 20031205 

 Metadata_Contact: 

 Contact_Information: 

 Contact_Person_Primary: 

 Contact_Person: Laura M. Norman 

 Contact_Organization: U.S. Geological Survey 

 Contact_Position: Cartographer, GIS Specialist 

 Contact_Address: 

 Address_Type: mailing address 

 Address: 520 N Park Ave, Ste #355 

 City: Tucson 

 State_or_Province: AZ 

 Postal_Code: 85719 

 Country: U.S.A 

 Contact_Voice_Telephone: 520 670 5510 

 Contact_Facsimile_Telephone: 520 670 5571 

 Contact_Electronic_Mail_Address: lmbrady@usgs.gov 

 Hours_of_Service: 9-5 

 Metadata_Standard_Name: FGDC Content Standards for Digital Geospatial Metadata 

 Metadata_Standard_Version: FGDC-STD-001-1998 

 Metadata_Time_Convention: local time 

 Metadata_Access_Constraints: none 

 Metadata_Use_Constraints: none 

 Metadata_Extensions: 

 Online_Linkage: http://www.esri.com/metadata/esriprof80.html 

 Profile_Name: ESRI Metadata Profile 

91
Colonias in Douglas, Ariz. 

Identification_Information: 

 Citation: 

 Citation_Information: 

 Originator: Laura M. Norman 

 Publication_Date: 12/03 

 Title: Colonias in Douglas, AZ 

 Geospatial_Data_Presentation_Form: vector digital data 

 Online Linkage: http://codd.art.srnr.arizona.edu/colonias 

 Larger_Work_Citation: 

 Citation_Information: 

 Originator: Norman, Laura M., Donelson, Angela J., Pfeifer, Edwin, Lam, Alven H., and 

Osborn, Kenneth J. 

 Publication_Date: 12/03 

 Title: Analyses of Urban Sprawl and Colonias Development in Douglas, Arizona & Agua 

Prieta, Sonora on the U.S.-Mexico Border; A Process Application using GIS and Remote Sensing 

 Geospatial_Data_Presentation_Form: vector digital data 

 Series_Information: 

 Series_Name: Open File Report 

 Issue_Identification: OFR-03-XXX 

 Publication_Information: 

 Publication_Place: Menlo Park, CA 

 Publisher: USGS 

 Online_Linkage: <http://wgsc.wr.usgs.gov/wrgeog_pubs/> 

 Description: 

 Abstract: A suitability/ capability analysis (SCA) was implemented based on the housing and 

infrastructure suitability and/or capability of given areas to support colonias in Douglas, AZ. The 

City of Douglas, Public Works Department used these newly automated sewer lines and water 

lines in collaboration with street maps to pinpoint known colonia boundaries. It was recorded in 

the city office that the 'suggested' boundaries be included in this project according to complaints 

and pleas for assistance from those neighborhoods to install new infrastructure. 

 Purpose: Colonias designation was done in Douglas, AZ to identify colonias-like 

neighborhoods in the area to make those neighborhoods recognizable to apply for funding. 

 Time_Period_of_Content: 

 Time_Period_Information: 

 Single_Date/Time: 

 Currentness_Reference: 2003 

 Status: 

 Progress: Complete 

 Maintenance_and_Update_Frequency: None planned 

 Spatial_Domain: 

 Bounding_Coordinates: 

 West_Bounding_Coordinate: -109.568835 

 East_Bounding_Coordinate: -109.512347 

 North_Bounding_Coordinate: 31.378782 

 South_Bounding_Coordinate: 31.295863 

 Keywords: 

 Theme: 

 Theme_Keyword_Thesaurus: none 

 Theme_Keyword: Colonias 

 Place: 

 Place_Keyword_Thesaurus: none 

 Place_Keyword: Douglas 

92
 Place_Keyword: Arizona 

 Use_Constraints: This digital database is not meant to be used or displayed at any scale larger 

than 1:24,000 (for example, 1:12,000). Any hardcopies utilizing this dataset shall clearly 

indicate their source. If the user has modified the data in any way, he is obligated to describe the 

types of modifications he has performed on the hardcopy map. User specifically agrees not to 

misrepresent this dataset nor to imply that changes he made were approved by the U.S. 

Geological Survey. 

 Point_of_Contact: 

 Contact_Information: 

 Contact_Person_Primary: 

 Contact_Person: Laura M. Norman 

 Contact_Organization: U.S. Geological Survey 

 Contact_Position: Cartographer, GIS Specialist 

 Contact_Address: 

 Address_Type: mailing address 

 Address: 520 N Park Ave, Ste #355 

 City: Tucson 

 State_or_Province: AZ 

 Postal_Code: 85719 

 Country: U.S.A 

 Contact_Voice_Telephone: 520 670 5510 

 Contact_Facsimile_Telephone: 520 670 5571 

 Contact_Electronic_Mail_Address: lmbrady@usgs.gov 

 Hours_of_Service: 9-5 

 Data_Set_Credit: Chuck Ebner (City of Douglas - Department of Public Works, Assistant 

Director), Rosael Torres (City of Douglas-Housing Authority), Carlos de la Torre (City of Douglas - 

Department of Public Works, Director), Carol Huddleston (head of Turning Point, a non-profit 

local organization) identified the poorest neighborhoods to call "colonias" for this project. 

 Native_Data_Set_Environment: Microsoft Windows 2000 Version 5.0 (Build 2195) Service Pack 

4; ESRI ArcCatalog 8.2.0.700 

 Cross_Reference: 

 Citation_Information: 

 Publication_Information: 

 Larger_Work_Citation: 

 Citation_Information: 

 Publication_Information: 

 Publication_Place: USGS 

Data_Quality_Information: 

 Attribute_Accuracy: 

 Attribute_Accuracy_Report: While the boundaries are thought to be most accurate according to 

the people who were involved in their deliniation, there were no legal boundaries used to define 

the colonias dataset. 

 Completeness_Report: Only those neighborhoods that were deemed colonias by the 

participants were incorporated in this dataset. 

 Lineage: 

 Source_Information: 

 Source_Citation: 

 Citation_Information: 

 Source_Time_Period_of_Content: 

 Time_Period_Information: 

 Single_Date/Time: 

 Process_Step: 

 Process_Description: Local representatives were asked to draw boundaries on hard copy 

print out maps describing the roads, sewer, and water infrastructure overlain on aerial photos of 

their community. These approximations were based upon previous knowledge and familiarity 

93
with the most impoverished and underprivileged areas known to them at that time. These 

polygons boundaries were then digitized and attributed. 

 Process_Date: 06/03 

Spatial_Data_Organization_Information: 

 Direct_Spatial_Reference_Method: Vector 

 Point_and_Vector_Object_Information: 

 SDTS_Terms_Description: 

 SDTS_Point_and_Vector_Object_Type: G-polygon 

 Point_and_Vector_Object_Count: 9 

Spatial_Reference_Information: 

 Horizontal_Coordinate_System_Definition: 

 Planar: 

 Grid_Coordinate_System: 

 Grid_Coordinate_System_Name: Universal Transverse Mercator 

 Universal_Transverse_Mercator: 

 UTM_Zone_Number: 12 

 Transverse_Mercator: 

 Scale_Factor_at_Central_Meridian: 0.999600 

 Longitude_of_Central_Meridian: -111.000000 

 Latitude_of_Projection_Origin: 0.000000 

 False_Easting: 500000.000000 

 False_Northing: 0.000000 

 Planar_Coordinate_Information: 

 Planar_Coordinate_Encoding_Method: coordinate pair 

 Coordinate_Representation: 

 Abscissa_Resolution: 0.000016 

 Ordinate_Resolution: 0.000016 

 Planar_Distance_Units: meters 

 Geodetic_Model: 

 Horizontal_Datum_Name: North American Datum of 1983 

 Ellipsoid_Name: Geodetic Reference System 80 

 Semi-major_Axis: 6378137.000000 

 Denominator_of_Flattening_Ratio: 298.257222 

Entity_and_Attribute_Information: 

 Detailed_Description: 

 Entity_Type: 

 Entity_Type_Label: Colonias 

 Entity_Type_Definition: Colonias were defined by the Cranston-Gonzales Act of 1990 as rural 

communities and neighborhoods located within 150 miles of the United States-Mexican border. 

Some colonias may be entire border communities, while others are comprised of neighborhoods 

within incorporated communities. They lack adequate infrastructure (sewer or water lines) and/or 

housing. 

 Entity_Type_Definition_Source: http://www.hud.gov/groups/frmwrkcoln/whatcol.cfm 

 Attribute: 

 Attribute_Label: FID 

 Attribute_Definition: Internal feature number. 

 Attribute_Definition_Source: ESRI 

 Attribute_Domain_Values: 

 Unrepresentable_Domain: Sequential unique whole numbers that are automatically 

generated. 

 Attribute: 

 Attribute_Label: Shape 

 Attribute_Definition: Feature geometry. 

 Attribute_Definition_Source: ESRI 

 Attribute_Domain_Values: 

 Unrepresentable_Domain: Coordinates defining the features. 

94
 Attribute: 

 Attribute_Label: ID 

 Attribute: 

 Attribute_Label: NAME 

 Attribute_Definition: Name of colonia 

 Attribute: 

 Attribute_Label: AREA 

 Attribute_Definition: Area of polygon (Square meters) 

 Attribute: 

 Attribute_Label: POP2000 

 Attribute_Definition: Population according to sum of U.S. Census 2000 Blocks within 

boundaries. 

Distribution_Information: 

 Distributor: 

 Contact_Information: 

 Contact_Organization_Primary: 

 Contact_Organization: U.S. Geological Survey 

 Resource_Description: Downloadable Data 

 Distribution_Liability: 

 The U.S. Geological Survey (USGS) provides these geographic data "as is." The USGS 

makes no guarantee or warranty concerning the accuracy of information contained in the 

geographic data. The USGS further makes no warranties, either expressed or implied, as to any 

other matter whatsoever, including, without limitation, the condition of the product or its fitness for 

any particular purpose. The burden for determining fitness for use lies entirely with the user. 

Although these data have been processed successfully on computers at the USGS, no warranty, 

expressed or implied, is made by the USGS regarding the use of these data on any other system, 

nor does the fact of distribution constitute or imply any such warranty. 

 In no event shall the USGS have any liability whatsoever for payment of any consequential, 

incidental, indirect, special, or tort damages of any kind, including, but not limited to, any loss of 

profits arising out of use of or reliance on the geographic data or arising out of the delivery, 

installation, operation, or support by USGS. 

 Standard_Order_Process: 

 Digital_Form: 

 Digital_Transfer_Information: 

 Transfer_Size: 0.016 

Metadata_Reference_Information: 

 Metadata_Date: 20031205 

 Metadata_Contact: 

 Contact_Information: 

 Contact_Person_Primary: 

 Contact_Person: Laura M. Norman 

 Contact_Organization: U.S. Geological Survey 

 Contact_Position: Cartographer, GIS Specialist 

 Contact_Address: 

 Address_Type: mailing address 

 Address: 520 N Park Ave, Ste #355 

 City: Tucson 

 State_or_Province: AZ 

 Postal_Code: 85719 

 Country: U.S.A 

 Contact_Voice_Telephone: 520 670 5510 

 Contact_Facsimile_Telephone: 520 670 5571 

 Contact_Electronic_Mail_Address: lmbrady@usgs.gov 

 Hours_of_Service: 9-5 

 Metadata_Standard_Name: FGDC Content Standards for Digital Geospatial Metadata 

95
 Metadata_Standard_Version: FGDC-STD-001-1998 

 Metadata_Time_Convention: local time 

 Metadata_Access_Constraints: none 

 Metadata_Use_Constraints: none 

 Metadata_Extensions: 

 Online_Linkage: http://www.esri.com/metadata/esriprof80.html 

 Profile_Name: ESRI Metadata Profile 

96
Sewerlines- Douglas, Ariz. 

Identification_Information: 

 Citation: 

 Citation_Information: 

 Originator: Laura M. Norman 

 Publication_Date: 12/03 

 Title: Sewerlines in Douglas, AZ 

 Geospatial_Data_Presentation_Form: vector digital data 

 Online Linkage: http://codd.art.srnr.arizona.edu/colonias 

 Larger_Work_Citation: 

 Citation_Information: 

 Originator: Norman, Laura M., Donelson, Angela J., Pfeifer, Edwin, Lam, Alven H., and 

Osborn, Kenneth J. 

 Publication_Date: 12/03 

 Title: Analyses of Urban Sprawl and Colonias Development in Douglas, Arizona & Agua 

Prieta, Sonora on the U.S.-Mexico Border; A Process Application using GIS and Remote Sensing 

 Geospatial_Data_Presentation_Form: vector digital data 

 Series_Information: 

 Series_Name: Open File Report 

 Issue_Identification: OFR-03-XXX 

 Publication_Information: 

 Publication_Place: Menlo Park, CA 

 Publisher: USGS 

 Online_Linkage: http://wgsc.wr.usgs.gov/wrgeog_pubs/ 

 Description: 

 Abstract: This shapefile of sewerlines in Douglas, AZ was taken from infrastructure data from 

the City of Douglas Public Works Department's AutoCAD drawings in relation to street maps 

 Purpose: The was done to aid in the delineation of neighborhood style colonias that exist within 

the city itself. 

 Time_Period_of_Content: 

 Time_Period_Information: 

 Single_Date/Time: 

 Currentness_Reference: 2003 

 Status: 

 Progress: Complete 

 Maintenance_and_Update_Frequency: None planned 

 Spatial_Domain: 

 Bounding_Coordinates: 

 West_Bounding_Coordinate: -109.568835 

 East_Bounding_Coordinate: -109.512347 

 North_Bounding_Coordinate: 31.378782 

 South_Bounding_Coordinate: 31.295863 

 Keywords: 

 Theme: 

 Theme_Keyword_Thesaurus: none 

 Theme_Keyword: Sewerlines 

 Theme_Keyword: Infrastructure 

 Place: 

 Place_Keyword_Thesaurus: none 

 Place_Keyword: Douglas 

 Place_Keyword: Arizona 

 Stratum: 

97
 Temporal: 

 Use_Constraints: This digital database is not meant to be used or displayed at any scale larger 

than 1:24,000 (for example, 1:12,000). Any hardcopies utilizing this dataset shall clearly indicate 

their source. If the user has modified the data in any way, he is obligated to describe the types of 

modifications he has performed on the hardcopy map. User specifically agrees not to 

misrepresent this dataset nor to imply that changes he made were approved by the U.S. 

Geological Survey. 

 Point_of_Contact: 

 Contact_Information: 

 Contact_Person_Primary: 

 Contact_Person: Laura M. Norman 

 Contact_Organization: U.S. Geological Survey 

 Contact_Position: Cartographer, GIS Specialist 

 Contact_Address: 

 Address_Type: mailing address 

 Address: 520 N Park Ave, Ste #355 

 City: Tucson 

 State_or_Province: AZ 

 Postal_Code: 85719 

 Country: U.S.A 

 Contact_Voice_Telephone: 520 670 5510 

 Contact_Facsimile_Telephone: 520 670 5571 

 Contact_Electronic_Mail_Address: lmbrady@usgs.gov 

 Hours_of_Service: 9-5 

 Native_Data_Set_Environment: Microsoft Windows 2000 Version 5.0 (Build 2195) Service Pack 

4; ESRI ArcCatalog 8.2.0.700 

 Cross_Reference: 

 Citation_Information: 

 Publication_Information: 

 Larger_Work_Citation: 

 Citation_Information: 

 Publication_Information: 

 Publication_Place: USGS 

Data_Quality_Information: 

 Attribute_Accuracy: 

 Attribute_Accuracy_Report: The sewerlines were digitized by means of dead reckoning and 

are only as good as those AutoCAD drawings they were digitized from, and may contain errors in 

this process. 

 Completeness_Report: This dataset represents sewerlines as described by the Dept of Public 

Works for the City of Douglas in 2003. 

 Lineage: 

 Source_Information: 

 Source_Citation: 

 Citation_Information: 

 Source_Time_Period_of_Content: 

 Time_Period_Information: 

 Single_Date/Time: 

 Calendar_Date: 06/06/1985 

 Source_Currentness_Reference: ground condition 

 Process_Step: 

 Process_Description: These data were automated through the means of dead reckoning in 

Arc View 3.3, by heads up digitizing the CAD drawings onto DOQQ's, with known street lines 

overlain 

 Process_Date: 05/03 

Spatial_Data_Organization_Information: 

 Direct_Spatial_Reference_Method: Vector 

98
 Point_and_Vector_Object_Information: 

 SDTS_Terms_Description: 

 SDTS_Point_and_Vector_Object_Type: String 

 Point_and_Vector_Object_Count: 341 

Spatial_Reference_Information: 

 Horizontal_Coordinate_System_Definition: 

 Planar: 

 Grid_Coordinate_System: 

 Grid_Coordinate_System_Name: Universal Transverse Mercator 

 Universal_Transverse_Mercator: 

 UTM_Zone_Number: 12 

 Transverse_Mercator: 

 Scale_Factor_at_Central_Meridian: 0.999600 

 Longitude_of_Central_Meridian: -111.000000 

 Latitude_of_Projection_Origin: 0.000000 

 False_Easting: 500000.000000 

 False_Northing: 0.000000 

 Planar_Coordinate_Information: 

 Planar_Coordinate_Encoding_Method: coordinate pair 

 Coordinate_Representation: 

 Abscissa_Resolution: 0.000016 

 Ordinate_Resolution: 0.000016 

 Planar_Distance_Units: meters 

 Geodetic_Model: 

 Horizontal_Datum_Name: North American Datum of 1983 

 Ellipsoid_Name: Clarke 1866 

 Semi-major_Axis: 6378137.000000 

 Denominator_of_Flattening_Ratio: 298.257222 

Entity_and_Attribute_Information: 

 Detailed_Description: 

 Entity_Type: 

 Entity_Type_Label: Sewerlines 

 Attribute: 

 Attribute_Label: FID 

 Attribute_Definition: Internal feature number. 

 Attribute_Definition_Source: ESRI 

 Attribute_Domain_Values: 

 Unrepresentable_Domain: Sequential unique whole numbers that are automatically 

generated. 

 Attribute: 

 Attribute_Label: Shape 

 Attribute_Definition: Feature geometry. 

 Attribute_Definition_Source: ESRI 

 Attribute_Domain_Values: 

 Unrepresentable_Domain: Coordinates defining the features. 

 Attribute: 

 Attribute_Label: FNODE_ 

 Attribute: 

 Attribute_Label: TNODE_ 

 Attribute: 

 Attribute_Label: LPOLY_ 

 Attribute: 

 Attribute_Label: RPOLY_ 

 Attribute: 

 Attribute_Label: LENGTH 

 Attribute: 

99
 Attribute_Label: SEWER1_ 

 Attribute: 

 Attribute_Label: SEWER1_ID 

 Attribute: 

 Attribute_Label: NUMBER_ 

 Attribute_Definition: Number assigned to AutoCAD color 

 Attribute: 

 Attribute_Label: DIAMETER 

 Attribute_Definition: Pipeline diameter (inches) 

Distribution_Information: 

 Distributor: 

 Contact_Information: 

 Contact_Organization_Primary: 

 Contact_Organization: U.S. Geological Survey 

 Resource_Description: Downloadable Data 

 Distribution_Liability: 

 The U.S. Geological Survey (USGS) provides these geographic data "as is." The USGS 

makes no guarantee or warranty concerning the accuracy of information contained in the 

geographic data. The USGS further makes no warranties, either expressed or implied, as to any 

other matter whatsoever, including, without limitation, the condition of the product or its fitness for 

any particular purpose. The burden for determining fitness for use lies entirely with the user. 

Although these data have been processed successfully on computers at the USGS, no warranty, 

expressed or implied, is made by the USGS regarding the use of these data on any other system, 

nor does the fact of distribution constitute or imply any such warranty. 

 In no event shall the USGS have any liability whatsoever for payment of any consequential, 

incidental, indirect, special, or tort damages of any kind, including, but not limited to, any loss of 

profits arising out of use of or reliance on the geographic data or arising out of the delivery, 

installation, operation, or support by USGS. 

 Standard_Order_Process: 

 Digital_Form: 

 Digital_Transfer_Information: 

 Transfer_Size: 0.016 

Metadata_Reference_Information: 

 Metadata_Date: 20031205 

 Metadata_Contact: 

 Contact_Information: 

 Contact_Person_Primary: 

 Contact_Person: Laura M. Norman 

 Contact_Organization: U.S. Geological Survey 

 Contact_Position: Cartographer, GIS Specialist 

 Contact_Address: 

 Address_Type: mailing address 

 Address: 520 N Park Ave, Ste #355 

 City: Tucson 

 State_or_Province: AZ 

 Postal_Code: 85719 

 Country: U.S.A 

 Contact_Voice_Telephone: 520 670 5510 

 Contact_Facsimile_Telephone: 520 670 5571 

 Contact_Electronic_Mail_Address: lmbrady@usgs.gov 

 Hours_of_Service: 9-5 

 Metadata_Standard_Name: FGDC Content Standards for Digital Geospatial Metadata 

 Metadata_Standard_Version: FGDC-STD-001-1998 

 Metadata_Time_Convention: local time 

 Metadata_Access_Constraints: none 

100
 Metadata_Use_Constraints: none 

 Metadata_Extensions: 

 Online_Linkage: http://www.esri.com/metadata/esriprof80.html 

 Profile_Name: ESRI Metadata Profile 

 Metadata_Extensions: 

 Online_Linkage: http://www.esri.com/metadata/esriprof80.html 

 Profile_Name: ESRI Metadata Profile 

 Metadata_Extensions: 

 Online_Linkage: http://www.esri.com/metadata/esriprof80.html 

 Profile_Name: ESRI Metadata Profile 

101
Waterlines- Douglas, Ariz.

Identification_Information: 

 Citation: 

 Citation_Information: 

 Originator: Laura M. Norman 

 Publication_Date: 12/03 

 Title: Waterlines in Douglas, AZ 

 Geospatial_Data_Presentation_Form: vector digital data 

 Online Linkage: http://codd.art.srnr.arizona.edu/colonias 

 Larger_Work_Citation: 

 Citation_Information: 

 Originator: Norman, Laura M., Donelson, Angela J., Pfeifer, Edwin, Lam, Alven H., and 

Osborn, Kenneth J. 

 Publication_Date: 12/03 

 Title: Analyses of Urban Sprawl and Colonias Development in Douglas, Arizona & Agua 

Prieta, Sonora on the U.S.-Mexico Border; A Process Application using GIS and Remote Sensing 

 Geospatial_Data_Presentation_Form: vector digital data 

 Series_Information: 

 Series_Name: Open File Report 

 Issue_Identification: OFR-00-XXX 

 Publication_Information: 

 Publication_Place: Menlo Park, CA 

 Publisher: USGS 

 Online_Linkage: <http://wgsc.wr.usgs.gov/wrgeog_pubs/> 

 Description: 

 Abstract: This shapefile of waterlines in Douglas, AZ was taken from infrastructure data from 

the City of Douglas Public Works Department's AutoCAD drawings in relation to street maps 

 Purpose: The was done to aid in the delineation of neighborhood style colonias that exist within 

the city itself. 

 Time_Period_of_Content: 

 Time_Period_Information: 

 Single_Date/Time: 

 Currentness_Reference: 2003 

 Status: 

 Progress: Complete 

 Maintenance_and_Update_Frequency: None planned 

 Spatial_Domain: 

 Bounding_Coordinates: 

 West_Bounding_Coordinate: -109.568835 

 East_Bounding_Coordinate: -109.512347 

 North_Bounding_Coordinate: 31.378782 

 South_Bounding_Coordinate: 31.295863 

 Keywords: 

 Theme: 

 Theme_Keyword_Thesaurus: none 

 Theme_Keyword: Waterlines 

 Theme_Keyword: Infrastructure 

 Place: 

 Place_Keyword_Thesaurus: none 

 Place_Keyword: Douglas 

 Place_Keyword: Arizona 

 Stratum: 

 Temporal: 

102
 Use_Constraints: This digital database is not meant to be used or displayed at any scale larger 

than 1:24,000 (for example, 1:12,000). Any hardcopies utilizing this dataset shall clearly indicate 

their source. If the user has modified the data in any way, he is obligated to describe the types of 

modifications he has performed on the hardcopy map. User specifically agrees not to 

misrepresent this dataset nor to imply that changes he made were approved by the U.S. 

Geological Survey. 

 Point_of_Contact: 

 Contact_Information: 

 Contact_Person_Primary: 

 Contact_Person: Laura M. Norman 

 Contact_Organization: U.S. Geological Survey 

 Contact_Position: Cartographer, GIS Specialist 

 Contact_Address: 

 Address_Type: mailing address 

 Address: 520 N Park Ave, Ste #355 

 City: Tucson 

 State_or_Province: AZ 

 Postal_Code: 85719 

 Country: U.S.A 

 Contact_Voice_Telephone: 520 670 5510 

 Contact_Facsimile_Telephone: 520 670 5571 

 Contact_Electronic_Mail_Address: lmbrady@usgs.gov 

 Hours_of_Service: 9-5 

 Native_Data_Set_Environment: Microsoft Windows 2000 Version 5.0 (Build 2195) Service Pack 

4; ESRI ArcCatalog 8.2.0.700 

 Cross_Reference: 

 Citation_Information: 

 Publication_Information: 

 Larger_Work_Citation: 

 Citation_Information: 

 Publication_Information: 

 Publication_Place: USGS 

Data_Quality_Information: 

 Attribute_Accuracy: 

 Attribute_Accuracy_Report: The waterlines were digitized by means of dead reckoning and are 

only as good as those AutoCAD drawings they were digitized from, and may contain errors in this 

process. 

 Completeness_Report: This dataset represents waterlines as described by the Dept of Public 

Works for the City of Douglas in 2003. 

 Lineage: 

 Source_Information: 

 Source_Citation: 

 Citation_Information: 

 Source_Time_Period_of_Content: 

 Time_Period_Information: 

 Single_Date/Time: 

 Process_Step: 

 Process_Description: These data were automated through the means of dead reckoning in 

Arc View 3.3, by heads up digitizing the CAD drawings onto DOQQ's, with known street lines 

overlain 

 Process_Date: 05/03 

Spatial_Data_Organization_Information: 

 Direct_Spatial_Reference_Method: Vector 

 Point_and_Vector_Object_Information: 

 SDTS_Terms_Description: 

 SDTS_Point_and_Vector_Object_Type: String 

103
 Point_and_Vector_Object_Count: 709 

Spatial_Reference_Information: 

 Horizontal_Coordinate_System_Definition: 

 Planar: 

 Grid_Coordinate_System: 

 Grid_Coordinate_System_Name: Universal Transverse Mercator 

 Universal_Transverse_Mercator: 

 UTM_Zone_Number: 12 

 Transverse_Mercator: 

 Scale_Factor_at_Central_Meridian: 0.999600 

 Longitude_of_Central_Meridian: -111.000000 

 Latitude_of_Projection_Origin: 0.000000 

 False_Easting: 500000.000000 

 False_Northing: 0.000000 

 Planar_Coordinate_Information: 

 Planar_Coordinate_Encoding_Method: coordinate pair 

 Coordinate_Representation: 

 Abscissa_Resolution: 0.000016 

 Ordinate_Resolution: 0.000016 

 Planar_Distance_Units: meters 

 Geodetic_Model: 

 Horizontal_Datum_Name: North American Datum of 1983 

 Ellipsoid_Name: Clarke 1866 

 Semi-major_Axis: 6378137.000000 

 Denominator_of_Flattening_Ratio: 298.257222 

Entity_and_Attribute_Information: 

 Detailed_Description: 

 Entity_Type: 

 Entity_Type_Label: waterlines 

 Attribute: 

 Attribute_Label: FID 

 Attribute_Definition: Internal feature number. 

 Attribute_Definition_Source: ESRI 

 Attribute_Domain_Values: 

 Unrepresentable_Domain: Sequential unique whole numbers that are automatically 

generated. 

 Attribute: 

 Attribute_Label: Shape 

 Attribute_Definition: Feature geometry. 

 Attribute_Definition_Source: ESRI 

 Attribute_Domain_Values: 

 Unrepresentable_Domain: Coordinates defining the features. 

 Attribute: 

 Attribute_Label: FNODE_ 

 Attribute: 

 Attribute_Label: TNODE_ 

 Attribute: 

 Attribute_Label: LPOLY_ 

 Attribute: 

 Attribute_Label: RPOLY_ 

 Attribute: 

 Attribute_Label: LENGTH 

 Attribute: 

 Attribute_Label: WATER1_ 

 Attribute: 

 Attribute_Label: WATER1_ID 

104
 Attribute: 

 Attribute_Label: NUMBER 

 Attribute_Definition: Number assigned to AutoCAD color 

 Attribute: 

 Attribute_Label: DIAMETER 

 Attribute_Definition: Pipeline diameter (inches) 

Distribution_Information: 

 Distributor: 

 Contact_Information: 

 Contact_Organization_Primary: 

 Contact_Organization: U.S. Geological Survey 

 Resource_Description: Downloadable Data 

 Distribution_Liability: 

 The U.S. Geological Survey (USGS) provides these geographic data "as is." The USGS makes 

no guarantee or warranty concerning the accuracy of information contained in the geographic 

data. The USGS further makes no warranties, either expressed or implied, as to any other matter 

whatsoever, including, without limitation, the condition of the product or its fitness for any 

particular purpose. The burden for determining fitness for use lies entirely with the user. Although 

these data have been processed successfully on computers at the USGS, no warranty, 

expressed or implied, is made by the USGS regarding the use of these data on any other system, 

nor does the fact of distribution constitute or imply any such warranty. 

 In no event shall the USGS have any liability whatsoever for payment of any consequential, 

incidental, indirect, special, or tort damages of any kind, including, but not limited to, any loss of 

profits arising out of use of or reliance on the geographic data or arising out of the delivery, 

installation, operation, or support by USGS. 

 Standard_Order_Process: 

 Digital_Form: 

 Digital_Transfer_Information: 

 Transfer_Size: 0.016 

Metadata_Reference_Information: 

 Metadata_Date: 20031205 

 Metadata_Contact: 

 Contact_Information: 

 Contact_Person_Primary: 

 Contact_Person: Laura M. Norman 

 Contact_Organization: U.S. Geological Survey 

 Contact_Position: Cartographer, GIS Specialist 

 Contact_Address: 

 Address_Type: mailing address 

 Address: 520 N Park Ave, Ste #355 

 City: Tucson 

 State_or_Province: AZ 

 Postal_Code: 85719 

 Country: U.S.A 

 Contact_Voice_Telephone: 520 670 5510 

 Contact_Facsimile_Telephone: 520 670 5571 

 Contact_Electronic_Mail_Address: lmbrady@usgs.gov 

 Hours_of_Service: 9-5 

 Metadata_Standard_Name: FGDC Content Standards for Digital Geospatial Metadata 

 Metadata_Standard_Version: FGDC-STD-001-1998 

 Metadata_Time_Convention: local time 

 Metadata_Access_Constraints: none 

 Metadata_Use_Constraints: none 

 Metadata_Extensions: 

 Online_Linkage: http://www.esri.com/metadata/esriprof80.html 

 Profile_Name: ESRI Metadata Profile 

105
 Metadata_Extensions: 

 Online_Linkage: http://www.esri.com/metadata/esriprof80.html 

 Profile_Name: ESRI Metadata Profile 

106
Attractions in Douglas, Ariz. 

Identification_Information: 

 Citation: 

 Citation_Information: 

 Originator: Laura M. Norman 

 Publication_Date: 2003 

 Title: Attractions in Douglas, AZ Identified by Youth Advocates! 

 Geospatial_Data_Presentation_Form: vector digital data 

 Online Linkage: http://codd.art.srnr.arizona.edu/colonias 

 Larger_Work_Citation: 

 Citation_Information: 

 Originator: Norman, Laura M., Donelson, Angela J., Pfeifer, Edwin, Lam, Alven H., and 

Osborn, Kenneth J. 

 Publication_Date: 12/03 

 Title: Analyses of Urban Sprawl and Colonias Development in Douglas, Arizona & Agua 

Prieta, Sonora on the U.S.-Mexico Border; A Process Application using GIS and Remote Sensing 

 Geospatial_Data_Presentation_Form: vector digital data 

 Series_Information: 

 Series_Name: Open File Report 

 Issue_Identification: OFR-03-XXX 

 Publication_Information: 

 Publication_Place: Menlo Park, CA 

 Publisher: USGS 

 Online_Linkage: <http://wgsc.wr.usgs.gov/wrgeog_pubs/> 

 Description: 

 Abstract: The Southeast Arizona Health Behavioral Services (SEAHBS) sponsors a group 

called the New Turf/ Youth Advocates, which is comprised of about 20 high school aged kids and 

mentored by Ana Maria Flannigan. An informal presentation at their conference room in Douglas 

was presented to the group. Using aerial photos plotted onto posters, the kids identified features 

that they could recognize on the map (pools, baseball diamonds, track & field). This was followed 

by an introduction of how to turn layers describing their city on/off in Arc View and a 

demonstration of a hand held GPS device-- to help the youths conceptualize the transition of XY 

coordinates to a hard copy map. The youth group offered to help in the project. 

 Purpose: To identify Attractions in the City of Douglas, AZ 

 Time_Period_of_Content: 

 Time_Period_Information: 

 Single_Date/Time: 

 Calendar_Date: 12/03 

 Currentness_Reference: Completed September 9, 2003 

 Status: 

 Progress: Complete 

 Maintenance_and_Update_Frequency: As needed 

 Spatial_Domain: 

 Bounding_Coordinates: 

 West_Bounding_Coordinate: -109.568835 

 East_Bounding_Coordinate: -109.512347 

 North_Bounding_Coordinate: 31.378782 

 South_Bounding_Coordinate: 31.295863 

 Keywords: 

 Theme: 

 Theme_Keyword_Thesaurus: none 

 Theme_Keyword: Attractions

 Place: 

107
 Place_Keyword_Thesaurus: none 

 Place_Keyword: Douglas, AZ 

 Place_Keyword: Arizona 

 Use_Constraints: This digital database is not meant to be used or displayed at any scale larger 

than 1:24,000 (for example, 1:12,000). Any hardcopies utilizing this dataset shall clearly indicate 

their source. If the user has modified the data in any way, he is obligated to describe the types of 

modifications he has performed on the hardcopy map. User specifically agrees not to 

misrepresent this dataset nor to imply that changes he made were approved by the U.S. 

Geological Survey. 

 Point_of_Contact: 

 Contact_Information: 

 Contact_Person_Primary: 

 Contact_Person: Laura M. Norman 

 Contact_Organization: U.S.G.S. 

 Contact_Position: Cartographer 

 Contact_Address: 

 Address_Type: mailing address 

 Address: 520 N Park Ave, Ste #355 

 City: Tucson 

 State_or_Province: AZ 

 Postal_Code: 85719 

 Country: U.S.A 

 Contact_Voice_Telephone: 520-670-5510 

 Contact_Electronic_Mail_Address: lmbrady@usgs.gov 

 Native_Data_Set_Environment: Microsoft Windows 2000 Version 5.0 (Build 2195) Service Pack 

4; ESRI ArcCatalog 8.2.0.700 

Data_Quality_Information: 

 Attribute_Accuracy: 

 Attribute_Accuracy_Report: The kids identified most of the locations using street maps, 

addresses and recognizable intersections. The accuracy of the locations is variable and 

dependent on the youth group's knowledge of that site. Most locations are correspondent with 

the street addresses provided. 

 Completeness_Report: These are not all of the attractions that are available in Douglas, AZ- just 

a representative sample. 

 Lineage: 

 Process_Step: 

 Process_Description: 

 This "photo-points" project for the cities was implemented in 4 phases. 

 1. The youths began identifying important resources in their community; these included a 

new skate park, community pools and soccer fields. 

 2. The youths out in the City to photograph these sights and others (town hall, movie 

theatre, etc.) 

 3. The locations of the resources were coordinated with these photographs using Global 

Positioning System (GPS) readings. Carlos de la Torre instructed the youth group using a Trimble 

4700-4800 GPS system from the neighboring City of Bisbee, AZ. 

 4. Lastly, this was incorporated into the GIS database and is be viewable on the proposed 

web site, allowing the Internet user to click on a point on a map and open up the photograph 

taken by the youth. 

Spatial_Data_Organization_Information: 

 Direct_Spatial_Reference_Method: Vector 

 Point_and_Vector_Object_Information: 

 SDTS_Terms_Description: 

 SDTS_Point_and_Vector_Object_Type: Entity point 

 Point_and_Vector_Object_Count: 20 

Spatial_Reference_Information: 

 Horizontal_Coordinate_System_Definition: 

108
 Planar: 

 Grid_Coordinate_System: 

 Grid_Coordinate_System_Name: Universal Transverse Mercator 

 Universal_Transverse_Mercator: 

 UTM_Zone_Number: 12 

 Transverse_Mercator: 

 Scale_Factor_at_Central_Meridian: 0.999600 

 Longitude_of_Central_Meridian: -111.000000 

 Latitude_of_Projection_Origin: 0.000000 

 False_Easting: 500000.000000 

 False_Northing: 0.000000 

 Planar_Coordinate_Information: 

 Planar_Coordinate_Encoding_Method: coordinate pair 

 Coordinate_Representation: 

 Abscissa_Resolution: 0.000008 

 Ordinate_Resolution: 0.000008 

 Planar_Distance_Units: meters 

 Geodetic_Model: 

 Horizontal_Datum_Name: North American Datum of 1983 

 Ellipsoid_Name: Geodetic Reference System 80 

 Semi-major_Axis: 6378137.000000 

 Denominator_of_Flattening_Ratio: 298.257222 

Entity_and_Attribute_Information: 

 Detailed_Description: 

 Entity_Type: 

 Entity_Type_Label: d_attractions 

 Attribute: 

 Attribute_Label: FID 

 Attribute_Definition: Internal feature number. 

 Attribute_Definition_Source: ESRI 

 Attribute_Domain_Values: 

 Unrepresentable_Domain: Sequential unique whole numbers that are automatically 

generated. 

 Attribute: 

 Attribute_Label: Shape 

 Attribute_Definition: Feature geometry. 

 Attribute_Definition_Source: ESRI 

 Attribute_Domain_Values: 

 Unrepresentable_Domain: Coordinates defining the features. 

 Attribute: 

 Attribute_Label: ID 

 Attribute: 

 Attribute_Label: NAME 

 Attribute_Definition: Name of feature 

 Attribute: 

 Attribute_Label: ADDRESS 

 Attribute_Definition: Addresss 

 Attribute: 

 Attribute_Label: PHONE 

 Attribute_Definition: Phone Number 

 Attribute: 

 Attribute_Label: ATTRACTION 

 Attribute_Definition: Web address of picture portraying feature, as taken by Youth Advocates! 

Distribution_Information: 

 Resource_Description: Downloadable Data 

 Distribution_Liability: 

109
 The U.S. Geological Survey (USGS) provides these geographic data "as is." The USGS makes 

no guarantee or warranty concerning the accuracy of information contained in the geographic 

data. The USGS further makes no warranties, either expressed or implied, as to any other matter 

whatsoever, including, without limitation, the condition of the product or its fitness for any 

particular purpose. The burden for determining fitness for use lies entirely with the user. Although 

these data have been processed successfully on computers at the USGS, no warranty, 

expressed or implied, is made by the USGS regarding the use of these data on any other system, 

nor does the fact of distribution constitute or imply any such warranty. 

 In no event shall the USGS have any liability whatsoever for payment of any consequential, 

incidental, indirect, special, or tort damages of any kind, including, but not limited to, any loss of 

profits arising out of use of or reliance on the geographic data or arising out of the delivery, 

installation, operation, or support by USGS. 

 Standard_Order_Process: 

 Digital_Form: 

 Digital_Transfer_Information: 

 Transfer_Size: 0.017 

Metadata_Reference_Information: 

 Metadata_Date: 20031205 

 Metadata_Contact: 

 Contact_Information: 

 Contact_Organization_Primary: 

 Contact_Organization: USGS 

 Contact_Person: Laura M. Norman 

 Contact_Address: 

 Address_Type: mailing and physical address 

 City: Tucson 

 State_or_Province: AZ 

 Postal_Code: 85719 

 Country: U.S.A 

 Contact_Voice_Telephone: 520--670-5510 

 Contact_Electronic_Mail_Address: lmbrady@usgs.gov 

 Metadata_Standard_Name: FGDC Content Standards for Digital Geospatial Metadata 

 Metadata_Standard_Version: FGDC-STD-001-1998 

 Metadata_Time_Convention: local time 

 Metadata_Extensions: 

 Online_Linkage: http://www.esri.com/metadata/esriprof80.html 

 Profile_Name: ESRI Metadata Profile 

110