{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,5]],"date-time":"2026-03-05T06:32:39Z","timestamp":1772692359933,"version":"3.50.1"},"reference-count":59,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2018,11,20]],"date-time":"2018-11-20T00:00:00Z","timestamp":1542672000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Key R&amp;D Program of China","award":["2018YFC0406505"],"award-info":[{"award-number":["2018YFC0406505"]}]},{"name":"Henan Province Scientific and Technological Project","award":["162102410066 & 172102410075"],"award-info":[{"award-number":["162102410066 & 172102410075"]}]},{"name":"the Open Research Fund of the State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin at the China Institute of Water Resources and Hydropower Research","award":["IWHR-SKL-201701"],"award-info":[{"award-number":["IWHR-SKL-201701"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Due to the advantages of wide coverage and continuity, remotely sensed data are widely used for large-scale drought monitoring to compensate for the deficiency and discontinuity of meteorological data. However, few studies have focused on the capability of various remotely sensed drought indices (RSDIs) to represent the spatio\u2013temporal variations of meteorological droughts. In this study, five RSDIs, namely the Vegetation Condition Index (VCI), Temperature Condition Index (TCI), Vegetation Health Index (VHI), Modified Temperature Vegetation Dryness Index (MTVDI), and Normalized Vegetation Supply Water Index (NVSWI), were calculated using monthly Normalized Difference Vegetation Index (NDVI) and land surface temperature (LST) from the Moderate Resolution Imaging Spectroradiometer (MODIS). The monthly NDVI and LST data were filtered by the Savitzky\u2013Golay (S-G) filtering method. A meteorological station-based drought index represented by the Standardized Precipitation Evapotranspiration Index (SPEI) was compared with the RSDIs. Additionally, the dimensionless Skill Score (SS) method was adopted to identify the spatiotemporally optimal RSDIs for presenting meteorological droughts in the Yellow River basin (YRB) from 2000 to 2015. The results indicated that: (1) RSDIs revealed a decreasing drought trend in the overall YRB consistent with the SPEI except for in winter, and different variations of seasonal trends spatially; (2) the optimal RSDIs in spring, summer, autumn, and winter were VHI, TCI, MTVDI, and VCI, respectively, and the average correlation coefficient between the RSDIs and the SPEI was 0.577 (\u03b1 = 0.05); and (3) different RSDIs have time lags of zero\u2013three months compared with the meteorological drought index.<\/jats:p>","DOI":"10.3390\/rs10111834","type":"journal-article","created":{"date-parts":[[2018,11,21]],"date-time":"2018-11-21T11:23:27Z","timestamp":1542799407000},"page":"1834","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":41,"title":["Capability of Remotely Sensed Drought Indices for Representing the Spatio\u2013Temporal Variations of the Meteorological Droughts in the Yellow River Basin"],"prefix":"10.3390","volume":"10","author":[{"given":"Fei","family":"Wang","sequence":"first","affiliation":[{"name":"School of Water Conservancy and Environment, Zhengzhou University, Zhengzhou 450001, China"}]},{"given":"Zongmin","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Water Conservancy and Environment, Zhengzhou University, Zhengzhou 450001, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8794-1476","authenticated-orcid":false,"given":"Haibo","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Water Conservancy and Environment, Zhengzhou University, Zhengzhou 450001, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2570-3987","authenticated-orcid":false,"given":"Yong","family":"Zhao","sequence":"additional","affiliation":[{"name":"China Institute of Water Resources and Hydropower Research, the State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, Beijing 100038, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8054-7449","authenticated-orcid":false,"given":"Zhenhong","family":"Li","sequence":"additional","affiliation":[{"name":"School of Engineering, Newcastle University, Newcastle upon Tyne NE1 7RU, UK"}]},{"given":"Jiapeng","family":"Wu","sequence":"additional","affiliation":[{"name":"China Institute of Water Resources and Hydropower Research, the State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, Beijing 100038, China"}]}],"member":"1968","published-online":{"date-parts":[[2018,11,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"608","DOI":"10.1016\/j.jhydrol.2015.05.032","article-title":"Integrated index for drought assessment based on variable fuzzy set theory: A case study in the Yellow River Basin, China","volume":"527","author":"Huang","year":"2015","journal-title":"J. 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