{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T02:20:51Z","timestamp":1760235651804,"version":"build-2065373602"},"reference-count":54,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2021,9,19]],"date-time":"2021-09-19T00:00:00Z","timestamp":1632009600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2018YFB0504500"],"award-info":[{"award-number":["2018YFB0504500"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["42001314"],"award-info":[{"award-number":["42001314"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Open Research Fund of the State Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University","award":["20R02"],"award-info":[{"award-number":["20R02"]}]},{"name":"Fundamental Research Funds for the Central Universities, China University of Geosciences, Wu-han","award":["111-G1323520290"],"award-info":[{"award-number":["111-G1323520290"]}]},{"DOI":"10.13039\/501100001859","name":"Swedish National Space Agency","doi-asserted-by":"publisher","award":["Dnr 96\/16"],"award-info":[{"award-number":["Dnr 96\/16"]}],"id":[{"id":"10.13039\/501100001859","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Leaf mass per area (LMA) is a key plant functional trait closely related to leaf biomass. Estimating LMA in fresh leaves remains challenging due to its masked absorption by leaf water in the short-wave infrared region of reflectance. Vegetation indices (VIs) are popular variables used to estimate LMA. However, their physical foundations are not clear and the generalization ability is limited by the training data. In this study, we proposed a hybrid approach by establishing a three-dimensional (3D) VI matrix for LMA estimation. The relationship between LMA and VIs was constructed using PROSPECT-D model simulations. The three-VI space constituting a 3D matrix was divided into cubical cells and LMA values were assigned to each cell. Then, the 3D matrix retrieves LMA through the three VIs calculated from observations. Two 3D matrices with different VIs were established and validated using a second synthetic dataset, and two comprehensive experimental datasets containing more than 1400 samples of 49 plant species. We found that both 3D matrices allowed good assessments of LMA (R2 = 0.76 and 0.78, RMSE = 0.0016 g\/cm2 and 0.0017 g\/cm2, respectively for the pooled datasets), and their results were superior to the corresponding single Vis, 2D matrices, and two machine learning methods established with the same VI combinations.<\/jats:p>","DOI":"10.3390\/rs13183761","type":"journal-article","created":{"date-parts":[[2021,9,21]],"date-time":"2021-09-21T22:35:20Z","timestamp":1632263720000},"page":"3761","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Optimized Estimation of Leaf Mass per Area with a 3D Matrix of Vegetation Indices"],"prefix":"10.3390","volume":"13","author":[{"given":"Yuwen","family":"Chen","sequence":"first","affiliation":[{"name":"School of Geography and Information Engineering, China University of Geoscience, Wuhan 430074, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jia","family":"Sun","sequence":"additional","affiliation":[{"name":"School of Geography and Information Engineering, China University of Geoscience, Wuhan 430074, China"},{"name":"Department of Physical Geography and Ecosystem Science, Lund University, 22100 Lund, Sweden"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7783-5725","authenticated-orcid":false,"given":"Lunche","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Geography and Information Engineering, China University of Geoscience, Wuhan 430074, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shuo","family":"Shi","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wei","family":"Gong","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shaoqiang","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Geography and Information Engineering, China University of Geoscience, Wuhan 430074, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3011-1775","authenticated-orcid":false,"given":"Torbern","family":"Tagesson","sequence":"additional","affiliation":[{"name":"Department of Physical Geography and Ecosystem Science, Lund University, 22100 Lund, Sweden"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,9,19]]},"reference":[{"key":"ref_1","first-page":"212","article-title":"Spectranomics: Emerging science and conservation opportunities at the interface of biodiversity and remote sensing","volume":"8","author":"Asner","year":"2016","journal-title":"Glob. 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