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Making Cropland Data Layer Data Accessible and

Actionable in GIS Education

Weiguo Han a , Zhengwei Yang b , Liping Di c , Ali Levent Yagci d & Song Han e

a

 Center for Spatial Information Science and Systems, George Mason University , Fairfax ,

Virginia , USA

b

 Geospatial Information Branch, Research and Development Division, National Agricultural

Statistics Service , Fairfax , Virginia , USA

c

 Department of Geography and Geoinformation Science , George Mason University ,

Fairfax , Virginia , USA

d

 Department of Geography and Geoinformation Science , Center for Spatial Information

Science and Systems, George Mason University , Fairfax , Virginia , USA

e

 Department of Economics, School of Economics , Renmin University of China , Beijing ,

China

Published online: 09 Jan 2014.

To cite this article: Weiguo Han , Zhengwei Yang , Liping Di , Ali Levent Yagci & Song Han , Journal of Geography

(2014): Making Cropland Data Layer Data Accessible and Actionable in GIS Education, Journal of Geography, DOI:

10.1080/00221341.2013.838286

To link to this article: http://dx.doi.org/10.1080/00221341.2013.838286

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TEACHER’S NOTEBOOK

Making Cropland Data Layer Data Accessible and Actionable

in GIS Education

Weiguo Han, Zhengwei Yang, Liping Di, Ali Levent Yagci, and Song Han

ABSTRACT

The Cropland Data Layer (CDL) product provides

categorized land-cover information encompassing

the whole contiguous United States. Using the latest

Web and geospatial interoperability technologies,

CropScape was built to visualize, query, disseminate,

and analyze historical and current CDL data

interactively and intuitively over the Internet.

CropScape can be utilized as a useful online mapping

educational tool and an important source of free

geospatial data and geospatial Web services in GIS

education. This article introduces the CDL product

and functions of CropScape, and presents several

specific examples of cropland exploring, thematic

map creation, natural disaster assessment, crop

planting patterns discovery, geospatial data mashup,

and geospatial Web application development to

demonstrate CropScape’s capabilities.

Key Words: GIS, geography education,

land-cover change, Web-portal

Dr. Weiguo Han is a research assistant professor in

the Center for Spatial Information Science and Systems,

George Mason University, Fairfax, Virginia, USA. His

research activities encompass geospatial Web services,

geospatial data sharing and interoperability, semantic Web, geospatial Web portal, and geospatial cyberinfrastructure.

Dr. Zhengwei Yang is an information technology specialist at Geospatial Information Branch, Research and

Development Division, National Agricultural Statistics

Service, in Fairfax, Virginia, USA. His research interests

include land-cover classification and change detection

methods, crop growth and condition monitoring, crop

growth modeling and simulation, geospatial information

system technology, and image processing methods. Since

2009 Dr. Yang has been an affiliated faculty member of the

Department of Geography and GeoInformation Science,

George Mason University.

Dr. Liping Di a professor and the founding director

of the Center for Spatial Information Science and Systems and a professor of the Department of Geography

and Geoinformation Science, George Mason University,

Fairfax, Virginia, USA. His current research interests

include remote sensing standards, Web-based geospatial

information and knowledge systems, and remote sensing

applications.

Ali Levent Yagci is a Ph.D. candidate in the Department

of Geography and Geoinformation Science and a research

assistant in the Center for Spatial Information Science

and Systems, George Mason University, Fairfax, Virginia,

USA. His research areas cover evapotranspiration mapping using remote sensing data and methods, image processing, agricultural drought monitoring and forecasting,

and land use and land cover.

Dr. Song Han is an associate professor in the Department

of Economics, School of Economics, Renmin University

of China, Beijing, China. Her research interests include

optimal method, mathematics in economics, game theory,

microeconomic theory, and applied econometrics.

INTRODUCTION

Geospatial Web applications offer a timely and accessible way to disseminate

and explore various types of geospatial data. Meanwhile, these Web applications

can be leveraged by teachers in the classroom as online geospatial data sources

and mapping educational tools to improve students’ abilities to access, retrieve,

and analyze geospatial data and solve real-world problems and complex issues

(Sui 2004; Baker 2005; Harris, Rouse, and Bergeron 2010). CropScape1 is such an

application that is of interest to both public and academic users; it disseminates

the Cropland Data Layer (CDL) data produced by National Agricultural Statistical

Service (NASS) of United States Department of Agriculture (USDA) to public users

in an open and interoperable manner, and provides value-added analytical services

of data mashup, statistics analysis, change analysis, thematic map creation, and

so on (Han, Yang, et al. 2012). This article aims to introduce the CDL product and

functions of CropScape, and illustrates CropScape’s applicability in GIS education

using several illustrative examples.

CROPLAND DATA LAYER

In GIS education, utilizing a variety of thematic spatial data in classrooms

or laboratories is very helpful to deepen students’ understanding of important

concepts and to promote their skills in solving real-world problems. The CDL

product depicts detailed information on crop and noncrop categories and locations

covering the contiguous United States (CONUS) (Boryan et al. 2011). This valuable

geospatial data offers independent statistical estimates of crop acreage throughout

the growing season, and serves as an important input in the official statistical

reporting process (Johnson and Mueller 2010). And it has been extensively used by

policy and decision makers, scientists, educators, and farm producers on the issues

of food security (Hartz et al. 2012), land-cover change (Wright and Wimberly 2013),

pesticide control (Belden et al. 2012), agricultural sustainability (Kutz et al. 2012),

bioenergy crop inventory (Wang et al. 2011), and hazards assessment (Breazeale

2012). This georeferenced raster data can be used as an important geospatial data

source for teachers and students exploring land-cover and land-use change or

agricultural geoinformation of the CONUS in the GIS-related courses.

CROPSCAPE

In the past decade geospatial Web applications have become the major channels

of geospatial data dissemination and publication. These applications offer basic

map operations and advanced functions of data customization, visualization,

and analysis. Users can utilize them at any time from any place using Internetconnected computers (Di and Deng 2010). Many easy-to-use online mapping tools

like Google Earth (Todd 2007), Global Visualization Viewer (GloVis) (Campbell

2007), and DEM Explorer (Han, Di, et al. 2012) have been recommended for

classroom use.

The latest Web technologies and open geospatial standards make it more feasible

to build powerful Web geospatial applications. Using Asynchronous JavaScript

Journal of Geography 00: 1–10

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and XML (AJAX), Rich Internet Application (RIA), Simple

Object Access Protocol (SOAP), Web Services Description

Language (WSDL), and Open Geospatial Consortium’s

(OGC) geospatial standards of Web Map Service (WMS),

Web Feature Service (WFS), Web Coverage Service (WCS),

and Geography Markup Language (GML), CropScape

was developed to provide users with useful functions of

online visualization, geospatial navigation and querying,

reformatting and transformation, delineation of area of

interest (AOI), on-the-fly data analysis, on-demand data

processing and dissemination, thematic map creation, etc.,

in a service-oriented architecture (SOA) environment (Han,

Yang, et al. 2012). Besides popular OGC, WCS, WFS, and

WMS serving the CDL data and other geospatial data,

CropScape also provides Web geoprocessing services to

disseminate, visualize, retrieve, and analyze the CDL data

for any AOI in the CONUS. For example, the GetCDLPDF

service creates the on-demand CDL thematic maps with

customized settings, and it has been proven very useful in

NASS operation and been utilized by CropScape’s users;

there exists no online geospatial applications having such

a functional service available. Educators and students can

consume these services in their applications or scientific

workflows to accomplish the specialized tasks. Technical

methods of these geoprocessing services design and implementation can be adopted to disseminate and analyze other

geospatial data.

Teachers and students can access CropScape through

common Web browsers, like Internet Explorer or Firefox,

on any Internet-connected computer. They can explore

the CDL data within the state of interest simply by

entering CropScape link plus state abbreviation (e.g.,

http://nassgeodata.gmu.edu/CropScape/VA). It is a very useful

Figure 1. CropScape user interface in the browser window, showing the function

of each component. (Color figure available online.)

online learning portal to teach GIS concepts and skills

in the K–12 classrooms, especially where desktop GIS

software is not available. The detailed functionalities and

geospatial Web services of CropScape can be referred from

the published article (see Han. Yang, et al. 2012). CropScape

can help educators and students access, visualize, retrieve,

and analyze on-demand CDL data at any geographic

level in the CONUS through its intuitive graphical user

interface (GUI), as seen Figure 1. The functions of each GUI

component are described briefly as follows.

Map View

CropScape opens to display the latest CDL data (NASS

normally releases the CDL data for the previous year at

the end of January of each year), the CONUS state and

county boundaries, and other geospatial data in the map

view. These vector and raster data layers are combined

together to generate useful and helpful maps. The map

view provides students with a rich visual context to view

the nationwide land-cover features, find out and interpret

information contained in these layers, and tell stories about

cropland lands and resources. The geographic coordinates

of the current cursor location in the projection of USA

Contiguous Albers Equal Area Conic (USGS version) are

given on the toolbar. This location information tells where

the pixel attached with the land-cover feature is.

Map Layers

The map layer list includes not only the CDL layers

from 1997 to 2012 but also the background layer (global

land cover), the crop-mask layer, the boundary layers of

states, agricultural statistics districts (ASDs), counties in

the CONUS, the water layers (rivers and lakes), and the

road layers (national freeway system and regional major highways).

These reference layers help students navigate geographical context and define their AOIs. In

addition, students can add other

geospatial data of their interest as

the auxiliary layers into the map

view to offer additional information by uploading the raster file in

GeoTIFF format or the vector file

in GML or ESRI shapefile format.

They can learn how to choose helpful layers and integrate them with

other existing layers to make the

map view more informative from

a geographic perspective.

Map Operations

The map operation buttons

on the upper toolbar provide

shortcuts to navigate the map

extent and view crop fields clearly,

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including Zoom In/Out, Pan, Drag-Box Zoom, Full Extent,

Refresh, Previous/Next View, and Saving Current Map

Extent. Students can be guided to use these basic operations

to change the scale and location of the map view or center

their AOIs in the map view.

Information Query

The information query tools help query the land-cover

category information and the county level crop acreages

that are obtained from the 2007 Census of Agriculture

to answer spatial questions. Category Name, Value, and

Color are displayed in the popup box when querying

land-cover information at the specified location, or County

Name, State Name, FIPS Code, Total Cropland Acreage, and

Total Irrigated Cropland information when querying the

2007 county cropland statistical information of the selected

county. Based on their geography knowledge of specified

area, students can learn how to interpret these land-cover

features and related statistics information.

AOI Operations

The AOI operation buttons offer the shortcuts to define,

import, export, and erase AOI. CropScape provides three

options of AOI definition. The complete list of the CONUS

states, ASDs, and counties is loaded in the popup dialog

for selection. The AOI in the shape of rectangle, circle, and

polygon can be dragged and drawn in the map view. In

addition, students can upload the polygon vector file in

GML or ESRI shapefile format. After the AOI is defined,

the map view will be zoomed to appropriate extent and

centered on the location of interest. Students can leverage

this function to define an AOI, like one community of

their choice, in a familiar geographic context, so they can

discover more information and answer questions about this

area by starting with their familiar district and moving

outward.

Geospatial Analysis

Statistical analysis offers acreage estimates of landcover categories within the AOI for a specified crop year.

Students can use the output maps, charts, and tables to

gather and report land-cover information and explore cropdistribution patterns both regionally and locally. They can

also extract cropland information from multiyear CDL data

and discover cropland changes or planting patterns over

years. The CDL image swiping helps students view the

differences between images of two crop years interactively.

Change analysis helps students investigate the detailed

land-cover changes between two selected years. The detailed functional description will be demonstrated in the

subsequent sections. These analytical functions are very

helpful for developing students’ skills to analyze questions

about land cover of AOI and utilize geographic knowledge

in finding the solutions to these problems.

Data Retrieval

Students can retrieve the CDL data within a given AOI

for the available crop years in the preferred projection in

a compressed or uncompressed form. The image of the

output CDL file can be viewed in the output window or

be exported in a KML (Keyhole Markup Language) file for

visualization in Google Earth or Google Maps. For students

who are interested in the hardcopy map, the CDL data

within a defined AOI can be outputted as a thematic map

with presentable quality in PDF format for print.

Help Resources

The Demo, Help, Developer Guide, and FAQ buttons

on the right of the toolbar allow students to access

the demonstration video and user guide of CropScape

application, developer guide of using CDL Web data and

processing services, and frequently anticipated questions

on the CDL data and CropScape.

Social Media

The Facebook, Twitter, and LinkedIn links of the CropScape group are put at the lower right corner for learning

the latest updates or important news from these popular

social media sites.

CropScape makes a nationwide archive of cropland

information freely available for the use in a variety of GIS

curricula, and supports land-use/land-cover exploration

and applications in classrooms at different grade levels.

Easy-to-use and intuitive, CropScape is an ideal Web

mapping tool to help students gain experience of applying

GIS technology and methods towards solving real-world

problems such as natural resource and environmental

management, and expand their knowledge of using GIS

in problem-based learning activities.

The following illustrative examples, which can be used

in simple individual or group projects of college-level GIS

courses, are given in the subsequent sections:

1. Explore agricultural characteristics within an AOI

that is defined by the uploaded vector file.

2. Present the CDL data and other geospatial data in a

thematic map.

3. Upload and display geospatial data to designate

natural disaster area and evaluate cropland damages.

4. Extract the CDL data of interest for several continuous

years and discover crop planting patterns.

5. Mashup CDL data with other online geospatial data

to build a comprehensive map.

6. Build a Web mapping application using CropScape’s

Web geospatial services.

EXAMPLE 1: CROPLAND EXPLORING

With CropScape, students can explore the CDL data

within any AOI across the CONUS to answer questions

having local, regional, state, or national implications. The

specific AOI can be a state, ASD, or county of interest,

or be defined by the uploaded vector file. The online

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Figure 2. Statistical analysis of and thematic map creation of the Cropland Data Layer data within the area of interest,

taking Lower Susquehanna Watershed as an example. (Color figure available online.)

functions of statistical analysis and change analysis can be

performed on the CDL data within the highlighted AOI to

generate tabular and graphical summaries of land-cover

categories and tabular and imagery data of land-cover

changes respectively.

The preloaded list of the CONUS states, ASDs, and counties from the user interface of CropScape helps students

select any administrative or statistical district of interest.

However, a hydrologic unit defined by U.S. Geological

Survey (USGS) (Seaber, Kapanos, and Knapp 1987) is often

used as the study area in land cover and change, agricultural drought, agricultural irrigation, conservation tillage,

precision farming, etc., which are related to landscape

information. Here, Lower Susquehanna Watershed (USGS

Cataloging Unit 02050306), located mainly in southeastern

Pennsylvania with a small portion in Maryland, is selected

as the study area (Fig. 2). The study showed that one of

key factors affecting water quality in this watershed area

was agricultural activity (U.S. Geological Survey 1998). The

boundary file of this hydrological unit is extracted from

the 1:250,000-scale hydrological units of the United States

(U.S. Geological Survey 1994), and uploaded to CropScape

in a compressed file to define the AOI. The 2012 CDL data

within this watershed is counted using statistical analysis,

and the result is displayed in the form of table and bar

chart. The statistical summaries in the table can be saved

in a CSV (comma-separated values) file, and the selected

land-cover categories (crop categories only) from the list

can be exported in a GeoTIFF file for mapping to display

major crops distribution. These land-cover summaries

provide useful information to understand the agricultural

facts and land-use/land-cover characteristics in watershed

assessment and other study fields.

EXAMPLE 2: THEMATIC MAP CREATION

Utilizing cartographic principles to create a thematic map

with basic map elements is one of the important goals of GIS

courses. Discovering the appropriate geospatial datasets

for use in a GIS course project, understanding their types,

sources, and metadata information, and processing these

data by georeferencing, clipping, and reformatting can be

also covered in this technical topic. CropScape offers data

downloading of the CDL file in GeoTiff format along with its

attribute table, including category value; name; red, green,

blue color values; and opacity value for generating elements

related the CDL data in a thematic map.

Here, creating a thematic map of the 2011 Iowa CDL

data and ethanol plant locations is given to demonstrate

how to integrate data from different sources and convey

spatial relationship to audiences. The state of Iowa is the top

corn-producing state in the United States and has the most

corn-based biorefineries in the country (Renewable Fuels

Association 2013). It will be very meaningful to display

spatial patterns of corn, biorefinery locations, and railroads

in a thematic map. The 2011 Iowa CDL data as well as

its attribute table is obtained directly from CropScape. The

Web site of Iowa Corn provides the detailed information on

ethanol plants and their locations in the state in Google

Map (Iowa Corn Promotion Board/Iowa Corn Growers

Association 2012), which can be exported as a KML file and

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Figure 3. The 2011 Iowa Cropland Data Layer data and ethanol plant locations.

(Color figure available online.)

be converted to an ESRI shapefile file using GIS software.

The Iowa rail lines in ESRI shapefile format can be obtained

freely from the Iowa Department of Transportation (Iowa

Department of Transportation 2002). These data can be

overlaid and combined with title, north, legend, scale,

and projection information in ArcGIS software to create

the thematic map (Fig. 3), which shows that all ethanol

refineries are located in the corn-planted areas and on

or near the railway lines for convenient production and

transportation.

EXAMPLE 3: NATURAL DISASTER ASSESSMENT

Applying GIS analysis functions in natural resource

management, agriculture, and biology is very helpful for

Table 1. Crop damage estimation (unit: acre).

Crop 2010 2009 2008 2007 2006 Average

Corn 20,254.1 20,142.5 17,946.4 32,442.9 20,758.6 22,308.9

Cotton 456.4 492.9 462.6 23,28.6 3,274 1,402.9

Rice 4,554 3,258.5 3,758.4 4,080 6,395.4 4,409.3

Sorghum 501.7 1091.9 3,530.5 1,532 1,580.8 1,647.4

Soybeans 116,330.4 10,1323.3 92,745.7 84,845.4 93,692.7 97,787.5

Double Crop: Winter

Wheat/Soybeans

7541 20,308.4 24,164.4 17,063.8 19,483.1 17,712.14

developing students’ problemsolving skills. Students can upload

their raster or vector data of the

selected topic or the project area to

CropScape and analyze the CDL

data within the study area. A realworld scenario of crop damage

assessment of the 2011 Mississippi

River floods is presented below

according to the technical report

of Food and Agricultural Policy

Research Institute, University

of Missouri (Brown, Gerlt, and

Wilcox 2011).

The LandSat TM data for the

study area (part of Mississippi

County, Missouri) are downloaded

from the USGS Web site, then

clipped and reprojected to generate the raster file in GeoTIFF format. Figure 4 shows the May 7,

2010, image that depicts no flooding and the May 10, 2011, image

that illustrates flood inundation

after the levee was breached. At

first, the raster files are uploaded

to the server side of CropScape and

added as the auxiliary layers. Next, the inundated area is

identified and drawn roughly according to the differences

between these two layers. Then, the above-mentioned

statistical analysis is performed on the AOI CDL data

available for the previous years (here, using the crop years

of 2006–2010), the acreage of primary crops (i.e., corn,

cotton, rice, sorghum, soybeans, double-crop winter wheat,

and soybean) planted in this area are extracted from the

results, and averaged to estimate the possible damages of

croplands caused by the flood in 2011, as shown in Table 1.

In this scenario, if the flood areas can be recognized more

accurately and be exported to an ESRI shapefile in remote

sensing software, the AOI can be defined in CropScape in

the same way as in Example 1.

EXAMPLE 4: CROP-PLANTING

PATTERNS DISCOVERY

Gaining practical and research

experiences in the applications of

GIS and understanding of how GIS

operates in public sectors are important objectives of GIS courses.

The CDL data from CropScape

provides a useful online mapping

resource to engage students in research activities related to agricultural problems and promote

their research practices through

both individual and group projects.

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Figure 4. Define one inundated area of the 2011 Mississippi River flood by

comparison of LandSat TM images. (Color figure available online.)

Students can analyze the CDL data to discover information

and knowledge of cropland-cover change and crop-spatial

pattern and density (Boryan, Craig, and Willis 2009).

The following gives an example of exploring single crop

planting intensity during the crop years of 2006–2011 in

Delaware County, Iowa.

The 2006–2011 CDL data for this county can be customized and easily downloaded in a compressed file from

CropScape. After obtaining these data, a workflow is built

using ArcGIS ModelBuilder (Fig. 5). In the ModelBuilder,

these CDL data serve as the input data variables of the

workflow, and the crop value of corn is used as the value

variable. The Equal To and the

Raster Calculatortools of Spatial Analyst in ArcGIS are added as model

tools. The output data parameter

is the raster file with values (0–6)

to represent the corn-planting intensity of this county during 2006–

2011. Here, 6 means six years in a

row planted to corn, 5 means five

out of six years planted to corn,

and so on. The continuous corncropping areas are easily identified from the image. Students can

overlay the raster file of planting intensity with other geospatial

data like digital elevation model

(DEM) data, average annual precipitation, water resource points,

soil classification, land capability

classification to discover more useful information and knowledge

from spatial relationships between

them.

EXAMPLE 5: GEOSPATIAL DATA

MASHUP

Geospatial data mashup that

integrates online geospatial data

from a variety of sources intuitively

helps students access Web mapping programs for their visualization needs, develop their familiarity with these online data sources,

inspire their curiosity of spatial

patterns, and enhance their spatial

thinking abilities (Batty et al. 2010).

CropScape provides standard OGC

WCS and WMS services along with

the KML output of the CDL data for

use in Google Earth, Google Maps,

ArcGIS Explore, Bing Maps, and

other software with WCS, WMS,

and KML support. An example

of geospatial data mashup using Google Earth as a platform

is given as follows.

The 2006–2011 CDL data of Colby County, Kansas, is

clipped and exported as a KML file in CropScape. U.S.

Drought Monitor provides the datasets of weekly drought

condition in multiple formats across the United States and

Puerto Rico (Svoboda et al. 2002). Polygons that contain the

spatial information and the drought intensity (including

five levels, abnormally dry, moderate drought, severe

drought, extreme drought, and exceptional drought) can be

downloaded in the KMZ files by week from U.S. Drought

Monitor Web site. To display the 2012 Midwest drought

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Figure 5. Corn planting intensity for the crop years of 2006–2011, Delaware County,

Iowa. (Color figure available online.)

impact in this county, the KMZ file for August 21, 2012,

is downloaded. The KMZ file of the U.S. General Soil

Map, which contains locations and names of the soils, can

be downloaded from the Google Earth Library Web site

(Google Earth Library 2010). The KML and KMZ files are

loaded flexibly and operated intuitively in Google Earth to

explore drought impacts on crops planted on different soils

and convey useful information for further analysis (Fig. 6).

This kind of data mashup not only enhances the value of

Figure 6. Multisource geospatial data mashup. (Color figure available online.)

these data sources effectively, but

also potentially inspires students’

research interests and creative

thinking.

EXAMPLE 6: GEOSPATIAL WEB

APPLICATION DEVELOPMENT

The geospatial Web services enable users to leverage distributed

geospatial data and computing resources over the Web, and to automate geospatial data integration

and analysis (Zhao and Di 2010).

Building a GIS application using

open-standard-compliant geospatial services and open-source packages promotes students’ skills in

programming and develops their

experiences with presentation and

production of a GIS project. CropScape offers free and standard

geospatial data and processing

services and detailed developer guide2 to support machineto-machine interactions with the CDL data and other

geospatial data and spatial analysis functions. The following example presents how to construct a Web mapping

application that loads geospatial data services provided by

CropScape.

Open-source packages, including OpenLayers, ExtJS,

and GeoExt, are utilized to build this Web application.

OpenLayers is the most popular open-source mapping

library that can consume layers

from free OGC WMS and WFS

servers, Google Maps, Bing Maps,

Yahoo Maps, OpenStreetMap, and

ArcGIS Servers, and interact with

these layers through a suite of

map controls. ExtJS is a free crossbrowser JavaScript framework for

building responsive Web applications using its GUI components. GeoExt is an open-source

JavaScript library that connects

OpenLayers and ExtJS by loading

OpenLayers map object in the ExtJS

panel and linking OpenLayers objects in ExtJS data components. It is

easy to build a Web geospatial application utilizing the components

and objects defined in these packages (Appendix). At first, an OpenLayers Map object is constructed in

the Web page. Then, the required

WMS layers of the 2008–2012

CDL data and the boundary files

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Figure 7. Simple Web application example integrating the Web Map Service layers

of the 2008–2012 Cropland Data Layer (CDL) data and the boundary files of

Virginia. ASD = agricultural statistics district. (Color figure available online.)

(including state, ASDs, and counties) of Virginia are created

and added in the above map. Next, a toolbar containing the

created shortcut buttons of map navigation and geometry

drawing is constructed, and a map panel is created to load

the toolbar and display the map at the specified scale and

location. Finally, a layer tree is created to control the display

of these layers, and a view port is constructed to combine

the layer tree and the map panel together. This simple Web

application can be opened in the Web browser, as displayed

in Figure 7. For students with advanced programming

skills, they can try to add Google Maps layers or Bing

Maps layers in this Web application through OpenLayers

API and integrate CropScape’s Web geoprocessing services

using ExtJS GUI components and AJAX requests.

CONCLUSIONS

CropScape provides the GIS education community with

online informative tools to visualize, query, download, and

analyze the landscape information across the CONUS. It is

running in a cluster environment of four high-performance

servers to ensure its reliability and responsiveness, and we

conducted the load test of 250 concurrent users successfully

before official release in January 2011. CropScape has been

used as one of the federal geospatial data sources in GIS

courses by educators at institutions such as University of

Alabama in Huntsville (UAH), Eastern Illinois University,

University of Hawaii, and George Mason University. For

instance, in the course Introduction to Remote Sensing

(Atmospheric Science Department in UAH)3, students use

CropScape to answer questions related to crop categories,

such as these: What were the dominant crop categories in

Madison County Alabama in 2008? What was the dominant

land cover for the specified

drainage basin in 2011? What can

you infer about the land-cover

changes in the specified drainage

basin between 2008 and 2011?

Moreover, CropScape has been

identified as a recommended

geospatial data resource by the

libraries of several universities,

including Cornell University, the

University of Wisconsin–Madison,

and the University of Maryland.

The examples presented in this

article are for illustrative purposes

only; more practical cases will be

created by experienced educators

with CropScape’s applications in

GIS courses. In sum, CropScape

is an ideal tool for use as a contextual mapping backdrop in GIS

education at different levels to help

increase students’ GIS technical

skills, develop new information

and knowledge for the study area

with the CDL data, and support a wide variety of land use

and land-cover-related GIS course projects.

ACKNOWLEDGMENTS

Support under National Agricultural Statistics Service

of U.S. Department of Agriculture Grant (No. 58-3AEU-0-

0067) is gratefully acknowledged. The authors thank Dr.

Jerry T. Mitchell and three anonymous reviewers for their

helpful and valuable comments on this article.

NOTES

1. CropScape: http://nassgeodata.gmu.edu/CropScape/

(accessed July 21, 2012).

2. CropScape Developer Guide: http://nassgeodata.gmu.

edu/CropScape/devhelp/help.html (accessed July 21,

2012).

3. GIS in APES Learning Materials: http://nsstc.uah.

edu/∼anderse/docs/GIS-in-APES Lab2-3 GPS water.

doc (accessed July 14, 2013).

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APPENDIX: AN EXAMPLE CODE OF CONSUMING CROPSCAPE WEB SERVICES

(Color figure available online.)

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