Agricultural Science

The University of Illinois at Chicago utilized 5-meter 5-band RapidEye imagery purchased from Apollo Mapping to help predict corn yields and monitor crop health in the Midwest. This question and answer series was completed with Kenneth Copenhaver, a lead researchers on the project, during September 2012.

Question 1: Can you provide me with an overview of your project, its duration and the study sites?


This study hopes to use 5-meter 5-band RapidEye imagery to predict crop yields and conditions for corn fields in the Midwest of the United States. Our specific study sites are in central and western Illinois as well as eastern and northern Iowa. The study will span the summer and fall of 2012 from June 15th to October 30th.

Question 2: What groups are involved with this research project?

I am a part of the University of Illinois at Chicago Energy Resources Center. The Energy Resources Center is an inter-disciplinary research organization focused on the resolution of energy-related issues affecting the institutional, industrial and commercial sectors. Our current programs include: energy management assessments, economic modeling, biofuels, analysis of policy and regulatory initiatives, public outreach and education among others.

The biofuels group at ERC was involved in this project which has an over-arching goal to help ethanol plants produce efficiently at the best price for the consumer. Our group’s focus is to make significant contributions to energy conservation and production technologies while creating a cleaner, more sustainable environment. ERC currently employs 18 full-time and 9 part-time employees, many of which are students. Given the early, yet promising results of this project, we expect that farmers and ethanol plants in the Midwest can benefit by using RapidEye imagery to predict and improve yields as well as monitor conditions of corn fields.

Question 3: How is satellite imagery used in this project?

Our project uses satellite imagery from multiple platforms and resolutions combined with ground truth data from growers and weather data to predict corn yields from the field up to the regional level. If our project is successful, this type of geospatial analysis could be utilized by corn growers and ethanol plants to help improve marketing decisions. Information on weather conditions, weather trends and comparisons to previous years’ satellite data could also be offered to the growers and plants to make more informed business decisions. ‘Real time’ analysis of the 5-meter RapidEye imagery could offer insight to growers about the health of plants which cannot be determined by the human eye alone. With this information, growers could modify irrigation, fertilizer and pesticide regimes to maximize a field’s corn yield.

Question 4: What technology and/or software packages were used to complete the geospatial analysis required for this project?

For parts of the projects that required in-house mapping, we utilized Esri’s ArcGIS and ArcGIS Server. For our remote sensing needs, we employed ERDAS Imagine. And to verify results of our analysis in the field as well as to collect ground truth data, we used tablet PC’s with Esri’s ArcPad installed on them. Geospatial layers, including the RapidEye imagery purchased from Apollo Mapping were loaded onto the tablet PC’s and displayed using ArcPad GIS software. Project scouts took the tablets out into growers’ fields and, using the GPS on the tablet, were able to navigate to areas indicative of stress as well as to record other location-based notes on plant conditions, yields, etc.


Question 5: Could you elaborate on how ArcGIS and ERDAS were used in this project?

ArcGIS, ArcGIS Server and ArcPad were used primarily to display our geospatial data and generate maps which were PDF and web-based. Spatial algorithms such as zonal analysis and spatial statistics were used to prepare the satellite data for analysis. We also displayed, worked with and created weather data at the zip-code level, including layers on precipitation, change in precipitation, growing degree days and change in growing degree days.

ArcGIS Server allowed us to display weather and image maps on the Internet for project members to review. In the future, we could also set up ArcGIS Server so that ethanol plants and their grower cooperators could enter additional information about the maps, such as planting date, seed hybrid and field conditions – thereby making our spatial analysis even more accurate with additional ground truth data.

ERDAS Imagine was used to process and analyze the satellite data. We generated vegetation indices and change in vegetation indices (from previous years and as the year progressed) which were then brought into ArcGIS to display to the project members. We also used ERDAS to break up imagery collected over individual corn fields into smaller zones. These zones were based on levels of vigor according to the vegetation indices.

Question 6: How did Apollo Mapping contribute to this project?

Apollo provided us with RapidEye satellite imagery in a timely and efficient manner, as well as expertise regarding the availability of other satellite products. We purchased 5-meter, 5-band RapidEye imagery from Apollo Mapping on multiple occasions with data covering more than 12,100 square kilometers and spanning 2010 to 2012 over our various study sites. This imagery proved to be invaluable to the predictive power of our geospatial analysis.

Question 7: How did geospatial data, services, etc. contribute to the initial successes of the project?

Geospatial data and services have been integral to the success of this project. The RapidEye imagery provided by Apollo Mapping was used to help train lower resolution imagery for corn acreage and yield predictions. In the future, it could also be used by corn growers to identify ‘go-to’ locations in their fields for yield estimations, nitrogen requirements and weed density identification. By applying statistical techniques to the current RapidEye-derived vegetation indices, we could identify zones in grower’s fields so that scouting could be minimized to several locations in each zone. Once the grower scouted each zone, they could make determinations on the proper water, fertilizer and pesticide regimes to apply in order to maximize crop yields at the end of the growing season.

Question 8: Could you tell us a bit about your experience working with the Apollo Mapping sales team?

Brock McCarty and Apollo Mapping provided exceptional service, going above and beyond in their efforts to provide information on available geospatial products and secure the products for our use. It seemed that I could write an email request at almost any time of the day or night, and Brock would reply within five minutes. Further, they provided the data I ordered in as timely a fashion as possible which was crucial given the ‘real-time’ need for accurate crop yield predictions.