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当前位置: 首页 > 文章 > Ground-based hyperspectral remote sensing for weed management in crop production 国际农业与生物工程学报 2016,9 (2)
Position: Home > Articles > Ground-based hyperspectral remote sensing for weed management in crop production International Journal of Agricultural and Biological Engineering 2016,9 (2)

Ground-based hyperspectral remote sensing for weed management in crop production

作  者：
Yanbo Huang;Matthew A. Lee;Steven J. Thomson;Krishna N. Redd
单  位：
;Department of Electrical and Computer Engineering , Mississippi State University , Mississippi State , MS , 39762 , USA;Agricultural Research Service, United States Department of Agriculture;United States Department of Agriculture, National Institute of Food and Agriculture, Washington, DC 20024, USA;United States Department of Agriculture, Agricultural Research Service, Crop Production Systems Research Unit, PO Box 350, Stoneville MS 38776, US
关键词：
based;ground;weed management;hyperspectral remote sensing;crop injury;precisio
摘  要：
Agricultural remote sensing has been developed and applied in monitoring soil, crop growth, weed infestation, insects, diseases and water status in farm fields to provide data and information to guide agricultural management practices. Precision agriculture has been implemented through prescription mapping of crop fields at different scales with the data remotely sensed from space-borne, airborne and ground-based platforms. Ground-based remote sensing techniques offer portability, flexibility and controllability in applications for precision agriculture. In weed management, crop injury from off-target herbicide spray drift and herbicide resistance in weeds are two important issues. For precision weed management, ground-based hyperspectral remote sensing techniques were developed for detection of crop injury from dicamba and differentiation between glyphosate resistant and sensitive weeds. This research presents the techniques for ground-based hyperspectral remote sensing for these two applications. Results illustrate the advantages of ground-based hyperspectral remote sensing for precision weed management.

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