The application of GIS and AHP to time series satellite image data for the evaluation of agricultural drought | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The application of GIS and AHP to time series satellite image data for the evaluation of agricultural drought GyongBong Ju, Chol Jin Oh, CholMin Won, YongMin Kim, YunHui Kim, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7840734/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 9 You are reading this latest preprint version Abstract Agricultural drought is considered as one of the critical problems which cause a decrease in crop production. In this study, a methodology to determine the drought index used for the comprehensive evaluation of agricultural drought was proposed by applying GIS technology and AHP (Analytical Hierarchy Process) method to time series satellite image data. Firstly, VCI, TCI, VHI, NVSWI and WCI were calculated in GIS using the sequence MODIS data, and the change trend of drought according to the characteristic of each drought index during the growing season from 2012 to 2021 was analyzed. Secondly, the contribution of each drought index to the drought assessment of the research area was investigated by calculating the SPI from the sequential CHIRPS data and analyzing its correlation with those drought indices. Then, AHP method was used to calculate the weight of each drought index to the drought assessment of research area. Finally, the comprehensive drought index capable of representing those drought indices was developed by applying the weight of each drought index and used to evaluate the agricultural drought of the research area. The present study provides a useful methodology to develop a comprehensive drought index capable of representing the agricultural drought status of target area. Agricultural drought remote sensing data drought index GIS AHP Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 13 Mar, 2026 Reviews received at journal 08 Feb, 2026 Reviews received at journal 03 Feb, 2026 Reviewers agreed at journal 26 Jan, 2026 Reviewers agreed at journal 23 Jan, 2026 Reviewers invited by journal 22 Jan, 2026 Editor assigned by journal 21 Oct, 2025 Submission checks completed at journal 21 Oct, 2025 First submitted to journal 12 Oct, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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