Crop Disease Detection Using Remote Sensing Image Analysis

Pest and crop disease threats are often estimated by complex changes in crops and the applied agricultural practices that result mainly from the increasing food demand and climate change at global level. In an attempt to explore high-end and sustainable solutions for both pest and crop disease manag...

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Médium:	Online
Jazyk:	angličtina
Vydáno:	MDPI - Multidisciplinary Digital Publishing Institute 2022
Témata:	hyperspectral thermal proximal sensing disease detection signal-to-noise ratio outbreak prediction sensor fusion unsupervised clustering multispectral imaging thermal imaging unmanned aerial vehicle UAV lodging unmanned aerial vehicle (UAV) canopy structure feature Akaike information criterion (AIC) method difference index (DI) texture canopy model of row crops multiple scattering for geometric optical approach the gap probabilities of row crops overlapping relationship hotspot n/a wheat yellow rust vegetation indices meteorological information food security regional remote sensing vegetation health monitoring remote sensing NDVI polarization image fusion wheat powdery mildew hyperspectral imaging early detect the crop disease quantify the disease severity plant disease band selection machine learning anthocyanin hyperspectral reflectance linear discriminant analysis precision crop protection object detection UAV images maturity detection efficientdet retinanet centernet deep learning precision agriculture broccoli thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general thema EDItEUR::R Earth Sciences, Geography, Environment, Planning::RG Geography
On-line přístup:	ONIX_20221117_9783036556062_120
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Crop Disease Detection Using Remote Sensing Image Analysis

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