Study on Landscape Sensitivity and Diversity Analysis in Yucheng City

Abstract : Landsat ETM image located in Yucheng city in 2002 was interpreted by RS image extraction technology and classification method. Moreover, landscape ecology theories were applied as well as ArcGIS and Fragstats4 to choose the reasonable landscape indices including Contagion Index (CONTAG), Patch Density (PD), Landscape Shape Index (LSI), Perimeter Area Fractal Dimension (PAFRAC), Shannon’s Diversity Index (SHDI), Shannon’s Evenness Index (SHEI). The study results showed that correlation between the landscape index was significant at the 0.01 confidence level, the relationship rule was revealed between ecological index based on statistics model. The typical scale effect was selected, including 5 m, 10 m, 15 m, 20 m, 25 m, 30 m, 40 m, 50 m, 60 m, 70 m, 80 m, 90 m, 100 m, 110 m, 120 m, 150 m, 180 m and 210 m. The series results were clarified by PD, LSI, PAFRAC, CONTAG, SHDI and SHEI in response to the different scales, or 18 different scales. The detailed results showed that the decreasing trend was presented from 5 m scale to 210 m scale for each index. Furthermore, we also analyzed the scale effects for different landscape index. Finally, based on image by the change of LSI, PAFRAC, SHAPE-MN and AI on 30 m pixel scale, we emphatically analyzed the LSI, PAFRAC, SHAPE-MN, AI of 12 landscapes. Further, according to the new classification, for the 12 landscapes in Yucheng city, they are Arable-land, Grassland, Traffic and Transmission Land Use, Residential land, Public management and service land, Commercial service land, Garden plot land, Mine and storage land, Woodland, Water and water facility land, Special land and other land we explored and explained the ecological significance of different landscapes in the case city, Especially, landscape sensitivity, fragmentation and complexity of landscape spatial pattern and diversity.
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Xuexia Yuan, Yujian Yang, Yong Zhang. Study on Landscape Sensitivity and Diversity Analysis in Yucheng City. 9th International Conference on Computer and Computing Technologies in Agriculture (CCTA), Sep 2015, Beijing, China. pp.48-59, ⟨10.1007/978-3-319-48354-2_5⟩. ⟨hal-01614174⟩

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