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Perspectives for Remote Sensing with Unmanned Aerial Vehicles in Precision Agriculture

Author:
Maes, Wouter H., Steppe, Kathy
Source:
Trends in plant science 2019 v.24 no.2 pp. 152-164
ISSN:
1360-1385
Subject:
growth models, microbial detection, precision agriculture, regression analysis, remote sensing, unmanned aerial vehicles, vegetation, vigor, water stress, weeds, yield forecasting
Abstract:
Remote sensing with unmanned aerial vehicles (UAVs) is a game-changer in precision agriculture. It offers unprecedented spectral, spatial, and temporal resolution, but can also provide detailed vegetation height data and multiangular observations. In this article, we review the progress of remote sensing with UAVs in drought stress, in weed and pathogen detection, in nutrient status and growth vigor assessment, and in yield prediction. To transfer this knowledge to everyday practice of precision agriculture, future research should focus on exploiting the complementarity of hyperspectral or multispectral data with thermal data, on integrating observations into robust transfer or growth models rather than linear regression models, and on combining UAV products with other spatially explicit information.
Agid:
6234197