{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,15]],"date-time":"2026-03-15T05:34:28Z","timestamp":1773552868360,"version":"3.50.1"},"reference-count":54,"publisher":"MDPI AG","issue":"19","license":[{"start":{"date-parts":[[2020,9,28]],"date-time":"2020-09-28T00:00:00Z","timestamp":1601251200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Science Foundation of China","doi-asserted-by":"publisher","award":["41901121"],"award-info":[{"award-number":["41901121"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100017054","name":"NSFC-Zhejiang Joint Fund for the Integration of Industrialization and Informatization","doi-asserted-by":"publisher","award":["U1609203"],"award-info":[{"award-number":["U1609203"]}],"id":[{"id":"10.13039\/100017054","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004608","name":"Jiangsu Provincial Natural Science Foundation","doi-asserted-by":"publisher","award":["BK20160023"],"award-info":[{"award-number":["BK20160023"]}],"id":[{"id":"10.13039\/501100004608","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Open Fund of the Key Laboratory of Coastal Zone Exploitation and Protection","award":["2019CZEPK03"],"award-info":[{"award-number":["2019CZEPK03"]}]},{"DOI":"10.13039\/100007834","name":"Natural Science Foundation of Ningbo","doi-asserted-by":"publisher","award":["2019A610105"],"award-info":[{"award-number":["2019A610105"]}],"id":[{"id":"10.13039\/100007834","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The successful launch of the Sentinel-2 constellation satellite, along with advanced cloud detection algorithms, has enabled the generation of continuous time series at high spatial and temporal resolutions, which is in turn expected to enable the classification of salt marsh vegetation over larger spatiotemporal scales. This study presents a critical comparison of vegetation index (VI) and curve fitting methods\u2014two key factors for time series construction that potentially influence vegetation classification performance. To accomplish this objective, the stability of five different VI time series, namely Normalized Difference Vegetation Index (NDVI), Soil-Adjusted Vegetation Index (SAVI), Enhanced Vegetation Index (EVI), Green Normalized Difference Vegetation Index (GNDVI), and Water-Adjusted Vegetation Index (WAVI), was compared empirically; the suitability between three curve fitting methods, namely Asymmetric Gaussian (AG), Double Logistic (DL), and Two-term Fourier (TF), and VI time series was measured using the coefficient of determination, and the salt marsh vegetation separability among different combinations of VI time series and curve fitting methods (i.e., VI time series-based curve fitting model) was quantified using overall the Jeffries\u2013Matusita distance. Six common types of salt marsh vegetation from three typical coastal sites in China were used to validate these findings, which demonstrate: (1) the SAVI performed best in terms of time series stability, while the EVI exhibited relatively poor time series stability with conspicuous outliers induced by the sensitivity to omitted clouds and shadows; (2) the DL method commonly resulted in the most accurate classification of different salt marsh vegetation types, especially when combined with the EVI time series, followed by the TF method; and (3) the SAVI\/NDVI-based DL\/TF model demonstrated comparable efficiency for classifying salt marsh vegetation. Notably, the SAVI\/NDVI-based DL model performed most strongly for high latitude regions with a continental climate, whilst the SAVI\/NDVI-based TF model appears to be better suited to mid- to low latitude regions dominated by a monsoonal climate.<\/jats:p>","DOI":"10.3390\/s20195551","type":"journal-article","created":{"date-parts":[[2020,9,28]],"date-time":"2020-09-28T08:02:58Z","timestamp":1601280178000},"page":"5551","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":25,"title":["Evaluation of Vegetation Index-Based Curve Fitting Models for Accurate Classification of Salt Marsh Vegetation Using Sentinel-2 Time-Series"],"prefix":"10.3390","volume":"20","author":[{"given":"Chao","family":"Sun","sequence":"first","affiliation":[{"name":"Department of Geography &amp; Spatial Information Techniques, Ningbo University, Ningbo 315211, China"},{"name":"Key Laboratory of Coastal Zone Exploitation and Protection, Ministry of Natural Resources, Nanjing 210023, China"},{"name":"Institute of East China Sea, Ningbo University, Ningbo 315211, China"}]},{"given":"Jialin","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Geography &amp; Spatial Information Techniques, Ningbo University, Ningbo 315211, China"},{"name":"Institute of East China Sea, Ningbo University, Ningbo 315211, China"}]},{"given":"Luodan","family":"Cao","sequence":"additional","affiliation":[{"name":"Department of Geography &amp; Spatial Information Techniques, Ningbo University, Ningbo 315211, China"},{"name":"Institute of East China Sea, Ningbo University, Ningbo 315211, China"}]},{"given":"Yongchao","family":"Liu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Coastal Zone Exploitation and Protection, Ministry of Natural Resources, Nanjing 210023, China"},{"name":"School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China"}]},{"given":"Song","family":"Jin","sequence":"additional","affiliation":[{"name":"Key Laboratory of Coastal Zone Exploitation and Protection, Ministry of Natural Resources, Nanjing 210023, China"},{"name":"School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China"}]},{"given":"Bingxue","family":"Zhao","sequence":"additional","affiliation":[{"name":"Key Laboratory of Coastal Zone Exploitation and Protection, Ministry of Natural Resources, Nanjing 210023, China"},{"name":"School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China"},{"name":"School of Geography and Planning, Chizhou University, Chizhou 247000, China"}]}],"member":"1968","published-online":{"date-parts":[[2020,9,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1890\/10-1510.1","article-title":"The value of estuarine and coastal ecosystem services","volume":"81","author":"Barbier","year":"2011","journal-title":"Ecol. 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