{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,26]],"date-time":"2025-12-26T07:14:21Z","timestamp":1766733261706,"version":"build-2065373602"},"reference-count":56,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2021,5,28]],"date-time":"2021-05-28T00:00:00Z","timestamp":1622160000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["31971577 and 41971415"],"award-info":[{"award-number":["31971577 and 41971415"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Anhui Province University Natural Science Foundation and Chuzhou University Talent Foundation Project","award":["KJ2020A0717 and 2020qd31"],"award-info":[{"award-number":["KJ2020A0717 and 2020qd31"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Vegetation measures are crucial for assessing changes in the ecological environment. Fractional vegetation cover (FVC) provides information on the growth status, distribution characteristics, and structural changes of vegetation. An in-depth understanding of the dynamic changes in urban FVC contributes to the sustainable development of ecological civilization in the urbanization process. However, dynamic change detection of urban FVC using multi-temporal remote sensing images is a complex process and challenge. This paper proposed an improved FVC estimation model by fusing the optimized dynamic range vegetation index (ODRVI) model. The ODRVI model improved sensitivity to the water content, roughness degree, and soil type by minimizing the influence of bare soil in areas of sparse vegetation cover. The ODRVI model enhanced the stability of FVC estimation in the near-infrared (NIR) band in areas of dense and sparse vegetation cover through introducing the vegetation canopy vertical porosity (VCVP) model. The verification results confirmed that the proposed model had better performance than typical vegetation index (VI) models for multi-temporal Landsat images. The coefficient of determination (R2) between the ODRVI model and the FVC was 0.9572, which was 7.4% higher than the average R2 of other typical VI models. Moreover, the annual urban FVC dynamics were mapped using the proposed improved FVC estimation model in Hefei, China (1999\u20132018). The total area of all grades FVC decreased by 33.08% during the past 20 years in Hefei, China. The areas of the extremely low, low, and medium grades FVC exhibited apparent inter-annual fluctuations. The maximum standard deviation of the area change of the medium grade FVC was 13.35%. For other grades of FVC, the order of standard deviation of the change ratio was extremely low FVC &gt; low FVC &gt; medium-high FVC &gt; high FVC. The dynamic mapping of FVC revealed the influence intensity and direction of the urban sprawl on vegetation coverage, which contributes to the strategic development of sustainable urban management plans.<\/jats:p>","DOI":"10.3390\/rs13112126","type":"journal-article","created":{"date-parts":[[2021,5,31]],"date-time":"2021-05-31T03:45:29Z","timestamp":1622432729000},"page":"2126","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Annually Urban Fractional Vegetation Cover Dynamic Mapping in Hefei, China (1999\u20132018)"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3218-8146","authenticated-orcid":false,"given":"Yuliang","family":"Wang","sequence":"first","affiliation":[{"name":"College of Forestry, Nanjing Forestry University, Nanjing 210037, China"},{"name":"School of Computer and Information Engineering, Chuzhou University, Chuzhou 239000, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5689-5091","authenticated-orcid":false,"given":"Mingshi","family":"Li","sequence":"additional","affiliation":[{"name":"College of Forestry, Nanjing Forestry University, Nanjing 210037, China"},{"name":"Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China"}]}],"member":"1968","published-online":{"date-parts":[[2021,5,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1001","DOI":"10.1016\/j.scitotenv.2019.03.251","article-title":"Biome diversity in South Asia-How can we improve vegetation models to understand global change impact at regional level?","volume":"671","author":"Kumar","year":"2019","journal-title":"Sci. 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