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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Hydrology and Remote Sensing Laboratory » Research » Publications at this Location » Publication #368560
Research Project: Improving Agroecosystem Services by Measuring, Modeling, and Assessing Conservation Practices

Location: Hydrology and Remote Sensing Laboratory

Title: Linear transects of imagery increase crop monitoring using fixed-wing unmanned aircraft systems

Author
item Hunt Jr, Earle
item Daughtry, Craig
item Stern, Alan
item Russ, Andrew - Andy

Submitted to: Agricultural and Environmental Letters
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/29/2019
Publication Date: 11/22/2019
Citation: Hunt, E.R., Daughtry, C.S., Stern, A.J., Russ, A.L. 2019. Linear transects of imagery increase crop monitoring using fixed-wing unmanned aircraft systems. Agricultural and Environmental Letters. 04(1):1-4. https://doi.org/10.2134/ael2019.09.0040.
DOI: https://doi.org/10.2134/ael2019.09.0040

Interpretive Summary: One of the uses of unmanned aircraft systems (UAS), or drones, is to detect problems early for actions to prevent yield losses. Currently, large numbers of images are acquired with large amounts of overlap create an image mosaic of the whole field. However, acquiring and processing these images is costly and takes time. Therefore, we test the idea that the images may be analyzed as vegetation plots along a linear transect. The vegetation index calculated from the UAS imagery over the growing season was about equal to Landsat data acquired either a few days before or after the UAS flight. The results of this study will help farm managers and crop scouts to reduce the cost of monitoring and make more timely decisions to prevent yield losses.

Technical Abstract: Crop monitoring with unmanned aircraft must be timely to prevent yield losses and have low cost to be profitable. However, the expenses of acquiring large numbers of images with large overlap and creation of ortho-rectified mosaics may make unmanned aircraft system monitoring slow and cost prohibitive. A fixed-wing UAS was flown over six center-pivot irrigated fields and untilled sagebrush steppe over the 2014 growing season. A 90-m by 90-m area centered at the image nadir point was analyzed as a single point along a linear transect. When compared to the corresponding area on a Landsat image, mean NDVI from the UAS agreed well with NDVI from Landsat. Since each image retains its high spatial resolution, the proposed transect method may retain its accuracy for detecting problems. However, the geographic location is expected to be less accurate compared to an ortho-rectified mosaic.