Journal
REMOTE SENSING
Volume 13, Issue 20, Pages -Publisher
MDPI
DOI: 10.3390/rs13204155
Keywords
crop water stress; hyperspectral; LiDAR; multispectral; optical sensing; remote sensing; sentinel-1; soil moisture; thermometric sensing
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The current world is facing high competition and market risks in improving yield, crop illness, and crop water stress. Technological advancements, especially in the form of remote-sensing systems, are seen as effective solutions to address these issues with scalability and sustainability. Remote-sensing systems not only provide simple and timely solutions but also effectively assess crop production, security, and crop water stress, with potential for further enhancement in the future.
Currently, the world is facing high competition and market risks in improving yield, crop illness, and crop water stress. This could potentially be addressed by technological advancements in the form of precision systems, improvements in production, and through ensuring the sustainability of development. In this context, remote-sensing systems are fully equipped to address the complex and technical assessment of crop production, security, and crop water stress in an easy and efficient way. They provide simple and timely solutions for a diverse set of ecological zones. This critical review highlights novel methods for evaluating crop water stress and its correlation with certain measurable parameters, investigated using remote-sensing systems. Through an examination of previous literature, technologies, and data, we review the application of remote-sensing systems in the analysis of crop water stress. Initially, the study presents the relationship of relative water content (RWC) with equivalent water thickness (EWT) and soil moisture crop water stress. Evapotranspiration and sun-induced chlorophyll fluorescence are then analyzed in relation to crop water stress using remote sensing. Finally, the study presents various remote-sensing technologies used to detect crop water stress, including optical sensing systems, thermometric sensing systems, land-surface temperature-sensing systems, multispectral (spaceborne and airborne) sensing systems, hyperspectral sensing systems, and the LiDAR sensing system. The study also presents the future prospects of remote-sensing systems in analyzing crop water stress and how they could be further improved.
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