A Summary of Issues Associated With the 

Modernization of Data Collection

 

Linda A. Lawson, Denise A. Abreu,

Claire Boryan, Michael Gerling, Rick Hardin

National Agricultural Statistics Service 

1400 Independence Avenue, SW, Washington DC 20250

Key Words: Mobile Mapping, Data Collection, Interface Design, GIS 

Abstract 

The National Agricultural Statistics Service (NASS) is considering the use of a permanent grid frame instead of its 

area frame for the June Agricultural Survey (JAS). The proposed grid frame would include sample units having 

roughly equal-sized and shaped areas called grids or grid cells. The grid cells would be stratified by agricultural 

intensity and content and then a stratified random sample drawn. As with the current area frame, every year 20 percent 

of the sampled grids would be rotated out and a new rotation of grids introduced. A challenge associated with this

proposed approach is that only a portion of an agricultural field may lie within the selected grid whereas currently 

sampled units have boundaries that follow roads or other physical features. 

Because of the presence of partial fields in a sampled grid cell, the use of mobile mapping technology may be critical 

for proper identification of the areas to be included in a sampled grid cell. Currently, enumerators identify fields within 

a sampled unit onan aerial photo. The mobile mapping instrument also allows electronic data entry. To test the concept 

of a grid cell, in conjunction with the mobile mapping instrument, enumerators in North Carolina, Pennsylvania and 

South Dakota visited with farm operators during Summer 2014. A sample of grid cells was selected in each state. For 

each sampled grid, the enumerators completed an evaluation form to obtain information on a variety of issues 

including 1) those associated with the grid concept, 2) use of a mobile mapping instrument, 3) connectivity and 4)

visualization problems associated with the iPad (e.g. sun glare). This paper documents the research results and 

discusses future instrument enhancements as well as potential improvements in data collection activities. 

I. Introduction

The National Agricultural Statistics Service (NASS) conducts the June Agricultural Survey (JAS), which uses an area 

sampling frame. The JAS sampling unit is a segment, which is about one-square mile of land with well-defined 

boundaries, such as roads or fences. Field enumerators currently use a hard copy aerial photo to identify JAS 

operator’s land within the traditional JAS segment boundary. Enumerators draw the field boundaries on the aerial 

photo and report the crop type and acreage information on the paper questionnaire (Cotter et al., 2010). 

The agency is considering the use of a permanent grid frame instead of its current area frame for the JAS. The

proposed grid frame has units, which are roughly equal-sized and shaped areas called grid cells or grids. A challenge 

associated with this proposed approach is that fields may not be fully contained within a grid cell boundary. Because 

of the presence of partial fields, the use of mobile mapping technology may be critical for proper identification of the 

areas to be included in a sampled grid cell. 

NASS has been testing and refining a prototype mobile mapping instrument. Although it is being used to test the grid 

frame concept, the mobile mapping technology has the potential to reduce costs by eliminating the need for data entry 

from paper questionnaires, to improve data quality with electronic edit checks, and to lengthen the data collection 

window since the data can be sent electronically, unlike the paper questionnaires, which are mailed. The mobile 

mapping instrument can be utilized to collect data on both traditional JAS segments and on grid cells. In 2014, 

enumerators used the prototype instrumentto collect JAS data for grid cells in North Carolina, Pennsylvania and South 

Dakota. This paper documents the issues identified that are related to the use of the mobile mapping instrument and 

discusses future instrument enhancements as well as potential improvements in data collection activities. See Abreu 

et. al (2015), for information specific to testing the grid frame concept. 
II. JAS Background Information and Proposed Grid Sampling Frame 

The JAS is an annual area-frame-based survey with approximately 11,000 sample units known as segments. 

Enumerators are provided a paper aerial photo with the segment area outlined in red and are required to account for 

all land within the segment boundary (Figure 1). 

Enumerators divide the segment into separate tracts of land that represent each unique operating arrangement. Each 

tract is assigned a letter and drawn in blue on the aerial photo (Figure 2). Tracts are then screened for agricultural 

activity of which about 42,000 of them are classified as Agricultural Tracts (Ag-Tracts). 

Ag-Tract farm operators are contacted and asked general questions about their entire farming operation. Additional 

information is collected about all fields that fall within the segment boundary. Field boundaries are drawn in red on

the aerial photo and labeled with a field number (Figure 3). Section D of the paper questionnaire, as shown in

Attachment A, is used to record detailed information about each field (Cotter et al., 2010). 

 

 indicating sampled area representing unique land operating arrangements red for each Ag-Tract 

 Figure 1: Segment outline Figure 2: Segment divided into tracts Figure 3: Fields drawn in

The proposed grid frame, has units having roughly equal-sized and shaped areas called grid cells or grids. This 

permanent frame was developed based on the Public Land Survey System (PLSS), which lacks any physically 

identifiable boundaries. A challenge associated with this proposed approach is that fields may not be fully contained 

within a grid cell boundary. In these instances, information must be collected for the portion of the field that lies 

within the grid. Reporting accurate information on a partial field may be challenging, especially if the included area 

is only delineated on a printed aerial photo. One way to address this issue is to use a mobile mapping instrument, 

which incorporates GIS technology, to delineate fields and tracts within the grid cell. GIS calculations could be used 

to determine the acreage of each field (or portion of field) included in the grids, eliminating the need for agricultural 

operators to report acreage for partial fields. The mobile mapping instrument developed could handle both grid cells 

as well as traditional JAS segments. Figure 4 shows the grid frame concept (outlined in red) compared with a 

traditional JAS segment (outlined in purple). 

Figure 4: An illustration of a grid cell (outlined in red) compared with a segment (outlined in purple)
III. Overview of the Prototype Mobile Mapping Instrument 

 

Development of the prototype JAS mobile mapping instrument began in 2012. The instrument is an offline-capable 

web application designed to run within the Safari browser on an iPad. A substantial amount of the JAS data collection 

takes place in rural areas that tend to have intermittent signal; therefore, it was essential that the instrument be able to

operate without an Internet connection. Prior to data collection, enumerators run a cache routine to store the required 

imagery in the iPad’s memory (Gerling et al., 2015). 

Fields are delineated on digital imagery in place of the paper aerial photo. Detailed field information is captured in a 

streamlined electronic version of the Section D questionnaire. Field boundaries are captured as polygons with the 

Section D data linked as attributes (Figure 5). 

Figure 5: Mobile mapping instrument Figure 6: Geolocation feature

If a wireless broadband connection is available, the instrument transmits a copy of the data to the web server as it is

entered or modified by an enumerator. Otherwise, the data remains stored locally on the iPad. All data are 

automatically transmitted to the web server whenever a wireless broadband connection is available. Up-to-date traffic 

light symbols are displayed to indicate if the data has been stored locally on the iPad, saved to the server or both. 

The instrument contains a wide range of Geographic Information Systems (GIS) tools and features. Enhancements 

are made each year to improve usability. A sophisticated geolocation feature was added to the prototype instrument 

in 2014 to help the enumerators orientate themselves in relation to the segment or grid cell (Figure 6). 

IV. Aerial Imagery Part of the Instrument 

The aerial imagery part of the instrument displays a red segment or grid cell boundary overlaid on digital imagery on

the left side of the screen (Figure 5). This can also be run in full screen mode (Figure 7). The digital imagery is

obtained from the National Agricultural Imagery Program (NAIP), which acquires aerial imagery during the 

agricultural growing seasons in the continental U.S. Typically, this digital ortho-rectified aerial photography is

available to governmental agencies and the public within two to four months after acquisition. 

Figure 7: Instrument shown in full screen mode Figure 8: Displaying the CDL in place of the NAIP imagery 
The instrument is capable of presenting additional resource material using Web Map Service (WMS) overlays. This 

allows the ability to replace the NAIP imagery with another layer, such as roads or the Cropland Data Layer (CDL) 

(Figure 8). The CDL is an annual crop specific land cover product, depicting more than one hundred unique crop 

categories across the nation. NASS derived this cropland area monitoring program via remote sensing (satellite 

data) using a supervised land cover classification approach. The national CDL product (Boryan et. al (2011)) is

available on NASS’s CropScape web portal at http://nassgeodata.gmu.edu/CropScape. 

The majority of the functions are performed within the aerial imagery part of the instrument using the various tools 

created within OpenLayers, which is an open-source JavaScript mapping library and provides basic web and GIS 

functionality. 

In the current JAS enumeration process, enumerators use a blue grease pencil to outline tracts and a red grease pencil 

to outline fields on the paper aerial photo. The process within the mobile mapping instrument requires “splitting” a 

segment or grid cell into tracts and fields instead of outlining them. The polygons representing each of the fields are 

created by using the split feature tool. Splitting ensures that all land parcels are included within the segment or grid 

cell boundary. 

The split tool was integrated into a toolbar on an OpenLayers map in the instrument. The map allowed a loaded 

segment or grid displayed over NAIP aerial imagery to be repeatedly split into component tracts and fields. A merge 

tool was also developed for updating/correcting errors made when splitting. Several additional tools were added to

the OpenLayers map, including zoom tools, selection tools, and undo/redo buttons to make it more user friendly. The 

mobile mapping instrument has touch screen pinch zooming capabilities, but also includes buttons to quickly zoom to

preset levels. 

V. Electronic Section D Form 

The right side of the mobile mapping instrument main screen (Figure 9) displays the calculated GIS acreage along 

with general information about all of the polygons or fields that have been delineated on the aerial imagery. A button 

to the right of each field is used to open the electronic Section D form (Figure10). 

 

 Figure 9: The right side of main screen displays the Figure 10: A view of the opened Section D 

calculated GIS acreage and general field information form for the first field in the table

The mobile mapping instrument provides a highly optimized version of the paper Section D form. The specific details 

for each field are captured in a survey like format containing drop down menus and basic edit checks. Skip rules and 

validation logic were specified per-question dynamically. This effectively reduces the complex paper table as shown 

in Attachment A, to a handful of questions that relate to the specific crop or land use (Figure 11). 
 

 

Figure 11: Skip rules facilitate streamlined questions specific to each crop or land use. Indicators 

pinpoint missing information and any data inconsistencies found during basic edit checks 

VI. Field Data Collection Test 

During Summer 2014, enumerators in North Carolina (NC), Pennsylvania (PA) and South Dakota (SD) visited with 

farm operators to test the concept of grid cells in conjunction with the mobile mapping instrument. A sample of 20

grid cells was selected in each state. Field enumerators identified a total of 917 tracts, which are unique farm 

operations, (457 agricultural and 460 non-agricultural). Enumerators delineated all the fields and attemptedto conduct 

interviews with farm operators for all tracts with agriculture. 

 Table 1: Agricultural and Non-Agricultural Tracts by State 

North Carolina Pennsylvania South Dakota All 3 States 

Number Percent Number Percent Number Percent Number Percent 

Agricultural Tract 136 36.3 239 54.4 82 79.6 457 49.8 

Non-Agricultural 239 63.7 200 45.6 21 20.4 460 50.2 

Total 375 100.0 439 100.0 103 100.0 917 100.0 

 Table 2: Completed, Partial and Estimated Ag-Tract Interviews by State 

North Carolina Pennsylvania South Dakota All 3 States 

Number of

Ag-Tracts Percent Number ofAg-Tracts Percent Number ofAg-Tracts Percent Number ofAg-Tracts Percent 

Complete Live 

Interview 86 63.3 171 71.5 66 80.5 323 70.7 

Refusal Partial 

Interview 18 13.2 11 4.6 3 3.7 32 7.0 

Estimated 

(No Contact) 32 23.5 57 23.9 13 15.8 102 22.3 

Total 136 100.0 239 100.0 82 100.0 457 100.0 
For each sampled grid cell, the enumerators completed the evaluation form shown in Attachment B to obtain 

information on issues associated with the grid concept, use of a mobile mapping instrument, connectivity and glare 

associated with the iPad. In addition to providing a yes/no response, enumerators wrote notes on the back of the 

form describing the nature of any positive response. This enabled proper determination of the exact cause of the issue 

encountered. 

 

 

VII. Reported Issues: Aerial Imagery Part of Instrument 

Enumerators were asked whether they had any problems using the aerial imagery part of the instrument. Their 

responses were tabulated for each of the 457 agricultural (Ag) tracts completed. Table 3 displays the number of times 

field enumerators experienced difficulty navigating within the aerial imagery portion of the mobile mapping 

instrument. It was concerning that issues occurred during almost 40% of all Ag-Tract interviews. The Pennsylvania 

enumerators may have had more problems due to the complexity of their grid cells, which contained numerous small 

fields. 

 Table 3: Frequency of Reported Issues Using the Aerial Imagery Part of Instrument

North Carolina Pennsylvania South Dakota All 3 States 

Number of

Ag-Tracts Percent Number ofAg-Tracts Percent Number ofAg-Tracts Percent Number ofAg-Tracts Percent 

Yes 11 9.6 42 22.0 10 12.7 63 16.4 

Sometimes 36 31.3 41 21.5 11 13.9 88 22.8 

No 68 59.1 108 56.5 58 73.4 234 60.8 

Total 1/ 115 100.0 191 100.0 79 100.0 385 100.0 

 1/ There were 72 instances of non-response that are not accounted for in the total. Counts by state: NC-21, PA-48 and SD-3.

All positive responses were investigated, and the vast majority of the issues reported were based upon difficulty 

splitting fields, a failed merge or unresponsiveness of the touch screen. Various factors can contribute to an enumerator 

struggling with splitting fields. The main difficulty reported was accidentally double-tapping on the screen before the 

polygon was complete. This erased all of the vertices and forced them to start over. The option to double-tap to

complete the split was removed, and the vertices are now retained when a split fails. 

A merge will fail if all of the selected areas are not adjacent to one another. The enumerators were inadvertently 

selecting additional fields while using the select tool to move around so a pan tool was added, allowing them to

navigate without selecting. Pop-up warning messages were also clarified to indicate the number of fields involved and 

the reason the merge failed. Additional training exercises focusing specifically on the merge process were created. 

A number of enumerators commented that the iPad touch screen was unresponsive at times. They were particularly 

frustrated by the fact that it seemed to mainly occur when they were trying to delineate the field boundaries in the 

middle of an interview. It was discovered that the touch screen became unresponsive when the user’s finger wiggled 

as it pressed a button. This instability was previously undetected because testing and training were primarily done 

with the iPad on a flat surface whereas these tests were conducted holding the iPad in one hand while standing outside. 

Programmers were able to fix this by specifying that slight finger movements were to be ignored. 

VIII. Reported Issues: Electronic Section D Form 

Enumerators were asked whether they had any problems completing the electronic Section D. Their responses were 

tabulated for each of the 457 Ag tracts completed. Table 4 displays the number of times field enumerators reported 

issues while answering the questions within Section D of the mobile mapping instrument. 
 Table 4: Frequency of Issues Reported While Completing the Electronic Section D Form

 

North Carolina Pennsylvania South Dakota All 3 States 

Number of

Ag-Tracts Percent Number ofAg-Tracts Percent Number ofAg-Tracts Percent Number ofAg-Tracts Percent 

Yes 6 5.3 21 11.3 4 5.1 31 8.2 

Sometimes 5 4.4 44 23.7 3 3.8 52 13.7 

No 103 90.3 121 65.0 72 91.1 296 78.1 

Total 1/ 114 100.0 186 100.0 79 100.0 379 100.0 

 1/ There were 78 instances of non-response that are not accounted for in the total. Counts by state: NC-22, PA-53 and SD-3.

NC and SD enumerators reported no issues completing over 90% of the Ag-Tracts. The primary complaint of the 

Pennsylvania enumerators was having to scroll through a list of 32 “other” crops that were not alphabetized. The 

survey form designed for PA was much more complicated than in the other states due to an extensive listing of other 

crops. In 2015, the other crop question was eliminated from the instrument due to a policy change eliminating the 

need to specify the type of other crop. 

Some enumerators from each state reported frustration with the placement of the calculated GIS acreage. If the 

respondent did not know the number of acres in a field, the enumerator had to close the Section D survey form to view 

the calculated acres in the general table and then reopen the survey form in order to continue. The program was 

changed to also display the calculated GIS acres for each field at the bottom of the Section D form (Figure 12). 

IX. Reported Issues: Connectivity 

Enumerators were asked to report any issues related to connectivity. Their responses were tabulated for each of the 

457 Ag tracts completed. Table 5 displays the number of times field enumerators reported connectivity problems. 

Even though the mobile mapping instrument was designed to function without an internet connection, there were 

connectivity problems 9% of the time. 

Figure 12: Shows the additional placement of calculated GIS acreage
 Table 5: Frequency of Connectivity Related Issues

 

North Carolina Pennsylvania South Dakota All 3 States 

Number of

Ag-Tracts Percent Number ofAg-Tracts Percent Number ofAg-Tracts Percent Number ofAg-Tracts Percent 

Yes 24 20.9 7 3.7 4 5.1 35 9.1 

Sometimes 32 27.8 41 21.6 0 0.0 73 19.0 

No 59 51.3 142 74.7 75 94.9 276 71.9 

Total 1/ 115 100.0 190 100.0 79 100.0 384 100.0 

 1/ There were 73 instances of non-response that are not accounted for in the total. Counts by state: NC-21, PA-49 and SD-3.

In areas of low signal strength, the geolocation feature actually timed out and caused the instrument to malfunction. 

NC may have experienced more issues due to the mountains and poor cellular coverage. The geolocation feature was 

removed from the instrument. 

The Pennsylvania enumerators misunderstood the cache routine. They thought that it automatically cached all zoom 

levels when in reality it was not designed to capture the higher zoom levels they needed to view the smaller fields. 

The training has been modified to help enumerators identify areas that are not cached. They will be instructed to

switch the iPad to airplane mode after running the cache routine. This will prevent any signal and display a pink tile 

in place of any imagery that has not been cached. They will then turn airplane mode off and cache any additional 

imagery needed before heading out to the field. 

Some of the connectivity issues were instances when the NAIP imagery was not available. The instrument is

dependent on public servers for hosting aerial photography (www.nationalmap.gov). To avoid the NAIP unreliability, 

all images required for testing will be stored on the same server as the mobile mapping instrument. 

X. Reported Issues: Visibility 

 

Up to this point, summary tables refer to all 457 agricultural tracts. To study visibility issues and, in particular, whether 

the farm operator had any difficulty viewing the iPad screen, instances of refusal or non-response are excluded, 

allowing the focus to be on 323 completed interviews. Table 6 displays the results to the screen visibility question. 

 Table 6: Number of Interviews with Impaired Screen Visibility

North Carolina Pennsylvania South Dakota All 3 States 

Number of

Ag-Tracts Percent Number ofAg-Tracts Percent Number ofAg-Tracts Percent Number ofAg-Tracts Percent 

Yes 21 26.2 87 57.6 6 9.2 114 38.5 

Sometimes 15 18.8 17 11.3 22 33.9 54 18.2 

No 44 55.0 47 31.1 37 56.9 128 43.3 

Total 1/ 80 100.0 151 100.0 65 100.0 296 100.0 

 1/ There were 27 instances of non-response that are not accounted for in the total. Counts by state: NC-6, PA-20 and SD-1. 

Glare, especially in bright sunlight, hinders the ability to collect data and needs to be significantly reduced to avoid 

visibility difficulties, which were observed in over half of all interviews. Pennsylvania reported the highest level of

difficulty, which is likely due to difficulty viewing smaller fields as the test area in PA had almost twice the number 

of fields per grid cell than the test areas in the other two states. 
Two modifications were made to the instrument in an effort to improve visibility: (1) adjusting the color scheme and 

(2) increasing the width of the segment border to distinguish it from roads. 

Additional training will be provided to show enumerators how to quickly switch on (Figure 13) and off (Figure 14) 

the iPad invert colors option. 

 

Figure 13: iPad screen with invert colors option turned on Figure 14: Normal view of iPad screen with invert colors off

The enumerators will also be provided new iPad cases 

that can be easilybe tilted to avoid sun glare (Figure 15). 

Figure 15: iPad case with rotary handle 

XI. Summary 

The best practices to enhance usability of the mobile mapping instrument is to simplify the design. Many enumerators 

in rural areas do not have high speed WiFi in their homes, therefore it is important to be mindful of connectivity 

limitations. Sophisticated GIS features may not be practical due to connectivity requirements. Further, enumerators 

need to have a higher level of technical expertise than with the current operational procedures. Efforts will continue 

to obtain feedback from enumerators on instrument enhancements and to test the instrument in all possible 

environments. 

Enumerator training should incorporate more role-play practice that mimics live interviews. Additional practice 

should be provided on specific skills. In addition to training enumerators on the fundamentals, tips, such as the use 

of airplane mode and the invert colors option, should be provided to better prepare enumerators for what they will 

encounter during live interviews. 

Screen visibility on the iPad continues to be a problem and needs to be significantly reduced. Efforts will continue to

identify new devices and screen protectors as they come on the market.
XII. References 

 

Abreu D., Lawson L., Boryan C., Gerling M., Hardin R., (2015) “Using a Mobile Mapping Instrument to Evaluate a 

Permanent Grid Sampling Frame”, Proc. In the 2015 Federal Committee on Statistical Methodology. 

Boryan C., Yang Z., Mueller R., Craig M., (2011) “Monitoring US Agriculture: the U.S. Department of Agriculture, 

National Agricultural Statistics Service Cropland Data Layer Program”, Geocarto International, 26, (5): 341-358. 

Cotter, J. Davies, C., Nealon, J., & Roberts R. (2010). Area Frame Design for Agricultural Surveys in Agricultural 

Survey Methods (eds R. Benedetti, M. Bee, G. Espa and F. Piersimoni), John Wiley & Sons, TD, Chichester, UK,

doi:10.1002/9780470665480.ch11. 

Gerling M., Lawson L., Weaber J., Dotts A., Vardeman A., Wilson E., (2015) “Field Data Collection Using 

Geographic Information Systems Technologies and iPads on the USDA’s June Area Frame Survey”, Research and 

Development Report RDD-15-03, United States Department of Agriculture, National Agricultural Statistics Service. 
Attachment A 

JAS Questionnaire 

 
Attachment B

Evaluation Form (Front) 

 
Attachment B

Evaluation Form (Back)