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A review of agricultural drought assessment with remote sensing data: methods, issues, challenges and opportunities
Published in Springer Science and Business Media Deutschland GmbH
Drought is a frequent hydrometeorological phenomenon that affects every individual, including animals. It causes significant economic and human losses. Various traditional methods are used to assess droughts in the early stages. However, conventional ways are time-consuming, expensive, and laborious. This has led to exploring remote sensing with recent methods for drought assessment. Therefore, the current paper gives a comprehensive overview of the recent studies on agricultural drought impact and its assessment using remote sensing datasets and various spectral index methods. The available satellite data sources have been provided with their sensors and spectral, spatial, and temporal information. Furthermore, we have also provided the general schema for agricultural drought assessment, essential indices, and drought severity methods with their importance and limitations. The normalized difference vegetation index (NDVI), standardized soil moisture index (SSMI), soil moisture percentile (SMP), normalized soil moisture (NSM), standardized precipitation index (SPI), vegetation health index (VHI), and soil moisture deficit index (SMDI) are the most used indices by researchers for drought detection and its assessment. Lastly, this review examines the challenges that need to be handled for the early detection of agricultural drought episodes. It is concluded that a long-term historical record of satellite images and meteorological data is required to calculate drought severity levels and identify drought-prone areas. This review can detect the hidden risks of agricultural drought and offer a theoretical foundation for decision-makers and mitigation agencies. © 2022, The Author(s), under exclusive licence to Società Italiana di Fotogrammetria e Topografia (SIFET).
About the journal
JournalApplied Geomatics
PublisherSpringer Science and Business Media Deutschland GmbH
Open AccessNo