{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,12]],"date-time":"2026-06-12T16:03:57Z","timestamp":1781280237757,"version":"3.54.1"},"reference-count":102,"publisher":"MDPI AG","issue":"22","license":[{"start":{"date-parts":[[2021,11,17]],"date-time":"2021-11-17T00:00:00Z","timestamp":1637107200000},"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>The conventional Land Surface Temperature (LST)\u2013Normalized Difference Vegetation Index (NDVI) trapezoid model has been widely used to retrieve vegetation water stress. However, it has two inherent limitations: (1) its complex and computationally intensive parameterization for multi-temporal observations and (2) deficiency in canopy water content information. We tested the hypothesis that an improved water stress index could be constructed by the representation of canopy water content information to the LST\u2013NDVI trapezoid model. Therefore, this study proposes a new index that combines three indicators associated with vegetation water stress: canopy temperature through LST, canopy water content through Surface Water Content Index (SWCI), and canopy fractional cover through NDVI in one temporally transferrable index. Firstly, a new optical space of SWCI\u2013NDVI was conceptualized based on the linear physical relationship between shortwave infrared (SWIR) and soil moisture. Secondly, the SWCI\u2013NDVI feature space was parameterized, and an index d(SWCI, NDVI) was computed based on the distribution of the observations in the SWCI\u2013NDVI spectral space. Finally, standardized LST (LST\/long term mean of LST) was combined to d(SWCI, NDVI) to give a new water stress index, Temperature Vegetation Water Stress Index (TVWSI). The modeled soil moisture from the Australian Water Resource Assessment\u2014Landscape (AWRA-L) and Soil Water Fraction (SWF) from four FLUXNET sites across Victoria and New South Wales were used to evaluate TVWSI. The index TVWSI exhibited a high correlation with AWRA-L soil moisture (R2 of 0.71 with p &lt; 0.001) and the ground-based SWF (R2 of 0.25\u20130.51 with p &lt; 0.001). TVWSI predicted soil moisture more accurately with RMSE of 21.82 mm (AWRA-L) and 0.02\u20130.04 (SWF) compared to the RMSE ranging 28.98\u201336.68 mm (AWRA-L) and 0.03\u20130.05 (SWF) were obtained for some widely used water stress indices. The TVWSI could also be a useful input parameter for other environmental models.<\/jats:p>","DOI":"10.3390\/rs13224635","type":"journal-article","created":{"date-parts":[[2021,11,17]],"date-time":"2021-11-17T21:32:07Z","timestamp":1637184727000},"page":"4635","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Modeling Vegetation Water Stress over the Forest from Space: Temperature Vegetation Water Stress Index (TVWSI)"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5081-4924","authenticated-orcid":false,"given":"Rakesh Chandra","family":"Joshi","sequence":"first","affiliation":[{"name":"School of Ecosystem and Forest Sciences, Faculty of Science, The University of Melbourne, Baldwin Spencer Building, Parkville, VIC 3010, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5335-6209","authenticated-orcid":false,"given":"Dongryeol","family":"Ryu","sequence":"additional","affiliation":[{"name":"Department of Infrastructure Engineering, The University of Melbourne, Parkville, VIC 3010, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1755-7334","authenticated-orcid":false,"given":"Gary J.","family":"Sheridan","sequence":"additional","affiliation":[{"name":"School of Ecosystem and Forest Sciences, Faculty of Science, The University of Melbourne, Baldwin Spencer Building, Parkville, VIC 3010, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Patrick N. J.","family":"Lane","sequence":"additional","affiliation":[{"name":"School of Ecosystem and Forest Sciences, Faculty of Science, The University of Melbourne, Baldwin Spencer Building, Parkville, VIC 3010, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,11,17]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"660","DOI":"10.1016\/j.foreco.2009.09.001","article-title":"A global overview of drought and heat-induced tree mortality reveals emerging climate change risks for forests","volume":"259","author":"Allen","year":"2010","journal-title":"Forest Ecol. 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