{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,18]],"date-time":"2026-01-18T07:57:42Z","timestamp":1768723062579,"version":"3.49.0"},"reference-count":46,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2021,1,25]],"date-time":"2021-01-25T00:00:00Z","timestamp":1611532800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>In semi-arid pasture areas, drought may directly influence livestock production, cause economic losses, and accelerate the processes of desertification along with destructive human activities (i.e., overgrazing). The aim of this article is to analyze the disadvantages of several drought indices derived from remote sensing data and develop a new vegetation drought index (VDI) for monitoring of grassland drought with high temporal frequency (dekad) and fine spatial resolution (1 km). The site-based soil moisture data from the field campaign in 2014 and the fenced biomass values at nine sites from 2000 to 2015 were adopted for validation. The results indicate that the proposed VDI would better reflect the extent, severity, and changes of drought compared with single drought indices or the vegetation health index (VHI); specifically, the VDI is more closely related to site-based soil moisture, with R human increasing to approximately 0.07 compared with the VHI; and with normalized fenced biomass (NFB) values, with average R human increasing to approximately 0.11 compared with the VHI. However, the correlations between VHI and VDI with NFB values are relatively lower in desert steppe regions. Furthermore, regional drought-affected data (RDA) are used to ensure spatial consistency of the evaluation; the VDI map is in good agreement with the RDA map based on field measurements. The presented VDI shows reliable and stable drought monitoring ability, which will play an important role in the future drought monitoring of inland grassland.<\/jats:p>","DOI":"10.3390\/rs13030414","type":"journal-article","created":{"date-parts":[[2021,1,25]],"date-time":"2021-01-25T12:28:31Z","timestamp":1611577711000},"page":"414","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":37,"title":["A Practical Satellite-Derived Vegetation Drought Index for Arid and Semi-Arid Grassland Drought Monitoring"],"prefix":"10.3390","volume":"13","author":[{"given":"Sheng","family":"Chang","sequence":"first","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences (AIRCAS), Olympic Village Science Park, W. Beichen Road, Beijing 100101, China"}]},{"given":"Hong","family":"Chen","sequence":"additional","affiliation":[{"name":"China Aero Geophysical Survey and Remote Sensing Center for Nature Resources, Beijing 100083, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5546-365X","authenticated-orcid":false,"given":"Bingfang","family":"Wu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences (AIRCAS), Olympic Village Science Park, W. Beichen Road, Beijing 100101, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2001-2469","authenticated-orcid":false,"given":"Elbegjargal","family":"Nasanbat","sequence":"additional","affiliation":[{"name":"National Remote Sensing Center, Information and Research Institute of Meteorology, Hydrology and Environment (IRIMHE), Ulaanbaatar 15160, Mongolia"}]},{"given":"Nana","family":"Yan","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences (AIRCAS), Olympic Village Science Park, W. Beichen Road, Beijing 100101, China"}]},{"given":"Bulgan","family":"Davdai","sequence":"additional","affiliation":[{"name":"National Remote Sensing Center, Information and Research Institute of Meteorology, Hydrology and Environment (IRIMHE), Ulaanbaatar 15160, Mongolia"}]}],"member":"1968","published-online":{"date-parts":[[2021,1,25]]},"reference":[{"key":"ref_1","first-page":"342","article-title":"Sensitivity analysis of drought indices used in Shaanxi Province","volume":"29","author":"Li","year":"2009","journal-title":"J. Desert Res."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"124","DOI":"10.2991\/jracr.2012.2.2.5","article-title":"The meteorological disaster risk assessment based on the diffusion mechanism","volume":"2","author":"Guo","year":"2012","journal-title":"J. Risk Analy. 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