Crop phenology retrieval via polarimetric SAR decomposition and Random Forest algorithm

Knowledge of crop phenology assists in making agricultural decisions such as appropriate irrigation and fertilization applications in order to optimize crop yield. The objective of this study is to monitor crop phenology using Synthetic Aperture Radar (SAR) polarimetric decompositions and a random f...

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Vydáno v:	Remote sensing of environment Ročník 231; s. 111234
Hlavní autoři:	Wang, Hongquan, Magagi, Ramata, Goïta, Kalifa, Trudel, Melanie, McNairn, Heather, Powers, Jarrett
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York Elsevier BV 15.09.2019
Témata:	Algorithms Artificial neural networks canola Corn Correlation coefficient Correlation coefficients Crop phenology Crop yield Crops data collection Decision trees Decomposition Fertilization Irrigation Manitoba Mathematical models Neural networks Parameter identification Parameter sensitivity Phenology polarimetry Radar Radar polarimetry Radarsat Regression analysis remote sensing Retrieval satellites Scattering soil Soil moisture Soils Soybeans Support vector machines Synthetic aperture radar vegetation Wheat Manitoba
ISSN:	0034-4257, 1879-0704
On-line přístup:	Získat plný text
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