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Vegetation Mapping for Regional Ecological Research and Management: A Case of the Loess Plateau in China
Chinese Geographical Science ( IF 3.4 ) Pub Date : 2020-06-01 , DOI: 10.1007/s11769-020-1120-5 Yuanxin Liu , Yihe Lyu , Yingfei Bai , Buyun Zhang , Xiaolin Tong
Chinese Geographical Science ( IF 3.4 ) Pub Date : 2020-06-01 , DOI: 10.1007/s11769-020-1120-5 Yuanxin Liu , Yihe Lyu , Yingfei Bai , Buyun Zhang , Xiaolin Tong
Vegetation maps are fundamental for regional-scale ecological research. However, information is often not sufficiently up to date for such research. The Loess Plateau is a key area for vegetation restoration projects and a suitable area for regional ecological research. To carry out regional vegetation mapping based on the principles of hierarchical classification, object-oriented methods, visual interpretation, and accuracy assessment, this study integrated land cover, high-resolution remote sensing images, background environmental data, bioclimate zoning data, and field survey data from the Loess Plateau. To further clarify the implications of vegetation mapping, we compared the deviation of the 2015 vegetation map of the Loess Plateau (VMLP) and the widely used vegetation map of China (VMC) (1 : 1 000 000) for the expressed vegetation information and the evaluation of ecosystem services. The results indicated that 1) the vegetation of the Loess Plateau could be divided into 9 vegetation type groups and 18 vegetation types with classification accuracies of 87.76% and 83.97%, respectively; 2) the distribution of vegetation had obvious zonal regularity; 3) a deviation of 29.56 × 10 4 km 2 occurred when the vegetation coverage area was quantified with the VMC; 4) the vegetation classification accuracy affected the ecosystem service assessment, the total water yield of the Loess Plateau calculated by the VMC and other required parameters was overestimated by 2.2 × 10 6 mm in 2015. Because vegetation mapping is a basic and important activity, that requires greater attention, this study provides supporting data for subsequent multivariate vegetation mapping and vegetation management for conservation and restoration.
更新日期：2020-06-01
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