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Conference papers

Dynamic Analysis of Urban Landscape Patterns of Vegetation Coverage Based on Multi-temporal Landsat Dataset

Abstract : Dynamic monitoring of vegetation coverage changes, especially on a relatively large temporal scale, have important practical significance in urban planning and environmental protection. The objective of this study is to dynamically investigate the urban landscape patterns of vegetation coverage based on remote sensing techniques. Multi-temporal Landsat images of 1990, 2000 and 2013 were firstly used to produce three vegetation coverage maps of Hefei City, Anhui Province, China with five grades using the NDVI (Normalized Difference Vegetation Index) dimidiate pixel model. Subsequently, a total of eight landscape pattern indictors in FRAGSTATS 4.2 were selected to analyze the dynamic characteristics of area, quantity and density for the study area with different vegetation coverage grades. The results showed that (1) the dominant vegetation coverage of 1990, 2000 and 2013 were the high vegetation coverage, the moderate vegetation coverage and the moderate-to-high vegetation coverage, respectively. The acreage of non-vegetation coverage increased by 1.89 %, while the high vegetation coverage decreased by 10.48 % from 1990 to 2013; (2) the quantity and density of patches decreased by 33.42 % and 33.41 % during 1990–2013. Shannon’s diversity index and Shannon’s evenness index increased from 0.92 in 1990 to 0.97 in 2000, and then declined to 0.96 in 2013; and (3) the contagion index had an upward trend and conversely the aggregation index showed no significant changes, but both of them were close to 1 during 1990–2013. In comparison with natural influences, the primary driving forces causing the changes were ascribed to human factors including the rapid population growth and fast-growing urban areas.
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Dong Liang, Ling Teng, Linsheng Huang, Xinhua Xie, Yan Zuo, et al.. Dynamic Analysis of Urban Landscape Patterns of Vegetation Coverage Based on Multi-temporal Landsat Dataset. 9th International Conference on Computer and Computing Technologies in Agriculture (CCTA), Sep 2015, Beijing, China. pp.300-316, ⟨10.1007/978-3-319-48357-3_30⟩. ⟨hal-01557852⟩



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