Integrating environmental and satellite data to estimate county-level cotton yield in Xinjiang Province.

ABSTRACT: Accurate and timely estimation of cotton yield over large areas is essential for precision agriculture, facilitating the operation of commodity markets and guiding agronomic management practices. Remote sensing (RS) and crop models are effective means to predict cotton yield in the field. The satellite vegetation indices (VIs) can describe crop yield variations over large areas but can't take the exact environmental impact into consideration. Climate variables (CVs), the result of the influence of spatial heterogeneity in large regions, can provide environmental information for better estimation of cotton yield. In this study, the most important VIs and CVs for estimating county-level cotton yield across Xinjiang Province were screened out. We found that the VIs of canopy structure and chl

SUBMITTER: Lang P 

PROVIDER: S-EPMC9889829 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature