Acta Geographica Sinica ›› 2011, Vol. 66 ›› Issue (5): 709-717.doi: 10.11821/xb201105013

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Evaluating Methods and Scale Effects of Attribute Information Loss in Rasterization: A Case Study of 1:250 000 Land Cover Data of Sichuan

BAI Yan1,2, LIAO Shunbao1, SUN Jiulin1   

  1. 1. State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China;
    2. Graduate University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2011-01-15 Revised:2011-03-01 Online:2011-05-20 Published:2011-05-20
  • Supported by:

    The Independent Research of the State Key Laboratory of Resource and Environmental Information System, No.O88RA100SA; The third innovative and cutting-edge projects of Institute of Geographic Sciences and Natural Resources Research, CAS, No.O66U0309SZ

Abstract: Taking land cover data of Sichuan at the scale of 1:250,000 in 2005 as a case study, this paper selects 16 spatial scales from 600 m to 30 km, uses rasterizing method based on the Rule of Maximum Area (RMA) in ArcGIS and two evaluation methods of attribute accuracy loss, which are Normal Analysis Method (NAM) and a new Method Based on Grid Cell (MBGC), respectively, and analyzes the scale effect of attribute (area) accuracy loss at 16 different scales by the two evaluating methods comparatively. The results are shown as follows. (1) At the same scale, mean attribute accuracy loss computed by Method Based on Grid Cell are significantly bigger than that computed using Normal Analysis Method. Moreover, this discrepancy is ranged between 1 km and 10 km, while the grid cell is larger than 10 km. Mean attribute accuracy loss computed by these two evaluation methods is stable, even tended to be parallel. (2) Method Based on Grid Cell can not only estimate RMA rasterization attribute accuracy loss accurately, but can express the spatial distribution of rasterization attribute loss objectively. (3) The suitable scale domain for RMA rasterization of land cover data of Sichuan at the scale of 1: 250,000 in 2005 is better, equal or less than 800 m, in which the data volume is favorable, and the attribute accuracy loss is less than 2.5%.

Key words: rasterization, attribute accuracy loss, evaluation, normal analysis method, method based on grid cell, scale effect, Sichuan Province