{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T23:23:08Z","timestamp":1776122588881,"version":"3.50.1"},"reference-count":70,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2017,12,25]],"date-time":"2017-12-25T00:00:00Z","timestamp":1514160000000},"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>Land cover changes significantly influence vegetation greenness in different regions. Dense Landsat time series stacks provide unique opportunity to analyze land cover change and vegetation greenness trends at finer spatial scale. In the past three decades, large reclamation activities have greatly changed land cover and vegetation growth of coastal areas. However, rarely has research investigated these frequently changed coastal areas. In this study, Landsat Normalized Difference Vegetation Index time series (1984\u20132016) data and the Breaks For Additive Seasonal and Trend algorithm were used to detect the intensity and dates of abrupt changes in a typical coastal area\u2014Hangzhou Bay, China. The prior and posterior land cover categories of each change were classified using phenology information through a Random Forest model. The impacts of land cover change on vegetation greenness trends of the inland and reclaimed areas were analyzed through distinguishing gradual and abrupt changes. The results showed that the intensity and date of land cover change were detected successfully with overall accuracies of 88.7% and 86.1%, respectively. The continuous land cover dynamics were retrieved accurately with an overall accuracy of 91.0% for ten land cover classifications. Coastal reclamation did not alleviate local cropland occupation, but prompted the vegetation greenness of the reclaimed area. Most of the inland area showed a browning trend. The main contributors to the greenness and browning trends were also quantified. These findings will help the natural resource management community generate better understanding of coastal reclamation and make better management decisions.<\/jats:p>","DOI":"10.3390\/rs10010032","type":"journal-article","created":{"date-parts":[[2017,12,26]],"date-time":"2017-12-26T03:06:38Z","timestamp":1514257598000},"page":"32","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":29,"title":["Examining Land Cover and Greenness Dynamics in Hangzhou Bay in 1985\u20132016 Using Landsat Time-Series Data"],"prefix":"10.3390","volume":"10","author":[{"given":"Dengqiu","family":"Li","sequence":"first","affiliation":[{"name":"State Key Laboratory of Subtropical Silviculture, Key Laboratory of Carbon Cycling in Forest Ecosystems and Carbon Sequestration of Zhejiang Province, School of Environmental & Resource Sciences, Zhejiang Agriculture and Forestry University, Lin\u2019an 311300, Hangzhou, China"}]},{"given":"Dengsheng","family":"Lu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Subtropical Silviculture, Key Laboratory of Carbon Cycling in Forest Ecosystems and Carbon Sequestration of Zhejiang Province, School of Environmental & Resource Sciences, Zhejiang Agriculture and Forestry University, Lin\u2019an 311300, Hangzhou, China"}]},{"given":"Ming","family":"Wu","sequence":"additional","affiliation":[{"name":"Wetland Ecosystem Research Station of Hangzhou Bay, Research Institute of Subtropical Forestry, Chinese Academy of Forestry, Fuyang 311400, Hangzhou, China"}]},{"given":"Xuexin","family":"Shao","sequence":"additional","affiliation":[{"name":"Wetland Ecosystem Research Station of Hangzhou Bay, Research Institute of Subtropical Forestry, Chinese Academy of Forestry, Fuyang 311400, Hangzhou, China"}]},{"given":"Jinhong","family":"Wei","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Subtropical Silviculture, Key Laboratory of Carbon Cycling in Forest Ecosystems and Carbon Sequestration of Zhejiang Province, School of Environmental & Resource Sciences, Zhejiang Agriculture and Forestry University, Lin\u2019an 311300, Hangzhou, China"}]}],"member":"1968","published-online":{"date-parts":[[2017,12,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Rai, R., Zhang, Y., Paudel, B., Li, S., and Khanal, N.R. 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