Submitted to: Proceedings of the Annual Precision Ag Conference
Publication Type: Proceedings
Publication Acceptance Date: July 20, 2008
Publication Date: July 20, 2008
Citation: Lan, Y., Huang, Y., Martin, D.E., Hoffmann, W.C., Fritz, B.K., Lopez, J. 2008. Development of an airborne remote sensing system for aerial applicators. Proceedings of the Annual Precision Ag Conference, July 20-23, 2008, Denver, CO. p. 5-25. Interpretive Summary: Airborne remote sensing technology along with Global Positioning Systems, Geographic Information Systems, and variable rate technology is critical to successful implementation of aerial application in precision agriculture. A multispectral camera was coupled with a specifically designed camera control system to develop a cost-effective tool for airborne remote sensing in pest management. The automated multispectral imaging system consistently produced precise images for the spatial analysis of pest infestations. Through image processing, data from the system was converted into input for the prescription of variable rate aerial application in site-specific pest management. The systems and techniques used in this work will increase the speed of image acquisition and enhance the use of aerially-acquired images for precision application in pest management.
Technical Abstract: An airborne remote sensing system was developed and tested for recording aerial images of field crops, which were analyzed for variations of crop health or pest infestation. The multicomponent system consists of a multi-spectral camera system, a camera control system, and a radiometer for normalizing images. To overcome the difficulties currently associated with correlating imagery data with what is actually occurring on the ground (a process known as ground truthing), a hyperspectral reflectance instrument was integrated into the image processing system. A GreenSeeker 505 Handheld Optical Sensor was mounted on a John Deere 4710 sprayer with a 30-meter swath and used to map the field. Data from the handheld optical sensor were georeferenced and converted to NDVI. The data were imported into Farm Works software and classified based on NDVI values. The data were then smoothed using the inverse distance subroutine and prescription maps were generated for each of the remote sensing methods. Good correlation was obtained between the aerially-acquired images and the GreenSeeker data. Irradiance data measured from a radiometer were used to normalize imagery. Traditionally, several large standardized reflectance panels have been used for this purpose. A less cumbersome approach is to use radiometers to record solar irradiance which is then used to convert recorded solar irradiance and images to milliwatts per square centimeter of energy. The data were imported into software and prescription maps were produced. This system is able to provide aerial applicators with remote sensing service and prescription mapping of fields.