Submitted to: ASABE Annual International Meeting
Publication Type: Proceedings
Publication Acceptance Date: 7/15/2007
Publication Date: 7/20/2007
Citation: Lan, Y., Huang, Y., Hoffmann, W.C. 2007. Airborne multi-spectral remote sensing with ground truth for areawide pest management. Proceedings of the ASABE Annual International Meeting, St. Louis, MO. Paper No. 07-3004. Interpretive Summary: Pest management has evolved from single field control to larger multiple field management systems known as areawide pest management. Use of remote sensing data will play an increasingly important role in American agriculture; therefore, airborne remote sensing technology, along with Global Positioning Systems, Geographic Information Systems, and variable rate technology, are critical to successful implementation of areawide pest management strategies. A multi-spectral imaging system for use on agricultural aircraft was developed and tested to provide images of fields that can help farmers and crop consultants manage agricultural lands. 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 and areawide pest management.
Technical Abstract: Scientists and researchers have been developing, integrating, and evaluating multiple strategies and technologies into a systems approach for management of field crop insect pests. Remote sensing along with Global Positioning Systems, Geographic Information Systems, and variable rate technology are additional technologies that scientists are implementing to help farmers maximize the economic and environmental benefits related to precision agriculture. A multi-spectral imaging system for use on agricultural aircraft was developed and tested to provide images of fields to help farmers and crop consultants manage agricultural lands. The results of this research indicate that the airborne MS4100 multi-spectral imaging system has a great potential for use in areawide pest management systems, such as weed control or detection of insect damage. Multi-spectral image processing produces NIR, red, green, NR, NG, NDVI, and NDNG indices or images, which can be used to evaluate biomass, crop health, biotypes, and pest infestations in agricultural fields. The classified images identify the ground land cover clusters by differentiating the variation of spectral signatures in the image. The results of the image classification can provide the critical input to generate prescription data for precision application of crop production and protection materials.