Upscaling approach to land cover based on priority and semantic proximity rules
TAN Shiteng1,2, WANG Jicheng1, XU Zhu1, GONG Xunqiang1,2
1. Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu 611756, China;
2. Jiangxi Province Key Lab for Digital Land, East China Institute of Technology, Nanchang 330013, China
The upscaling methods for land cover classification data are still based on mode number selection or principle proportion choice; nevertheless, blocked at multiple modes, map information will be largely distorted under randomly choice. In order to maintain spatial information before and after generalization, this paper introduces land cover priority guidelines and semantic proximity norms to the upscaling method. A new upscaling method can be obtained by adding both rules to the aggregation processing. Firstly, through setting land cover priority guidelines and semantic proximity norms, the output category at the corresponding spatial location can be calculated on the coarse scale. The results show that, based on the majority aggregation method, and by adding the priority of the neighboring and semantic rules, the consistency of the spatial distribution of the feature can be better maintained after generalization, and the similarity of original maps is relatively high.
谭诗腾, 王继成, 徐柱, 龚循强. 基于优先级和语义邻近度的地表覆盖数据升尺度方法[J]. 国土资源遥感, 2016, 28(1): 50-56.
TAN Shiteng, WANG Jicheng, XU Zhu, GONG Xunqiang. Upscaling approach to land cover based on priority and semantic proximity rules. REMOTE SENSING FOR LAND & RESOURCES, 2016, 28(1): 50-56.
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