栅格化属性精度损失的评估方法及其尺度效应分析——以四川省1:25 万土地覆被数据为例

doi:10.11821/xb201105013

Abstract

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

BAI Yan, LIAO Shunbao, SUN Jiulin. Evaluating Methods and Scale Effects of Attribute Information Loss in Rasterization: A Case Study of 1:250 000 Land Cover Data of Sichuan[J].Acta Geographica Sinica, 2011, 66(5): 709-717.

References

[1] Liao Shunbao. Study on Data Resource System of Earth System Science. Beijing: Science Press, 2010: 59-63. [廖顺宝. 地球系统科学数据资源体系研究. 北京: 科学出版社, 2010: 59-63.]

[2] Bates P D. A simple raster-based model for flood inundation simulation. Journal of Hydrology, 2000, 236: 54-77.

[3] Demers M N. GIS Modeling in Raster. New York: John Wiley & Sons, 2002.

[4] Yang Cunjian, Zhang Zengxiang. Models of accuracy loss during rasterizing landuse vector data with multi-scale gridsize. Geographical Research, 2001, 20(4): 416-422. [杨存建, 张增祥. 矢量数据在多尺度栅格化中的精度损失模型探讨. 地理研究, 2001, 20(4): 416-422.]

[5] Chen Shupeng. The time-and-space analysis of population statistics. China Population, Resources and Environment,2002, 12(4): 3-7. [陈述彭. 人口统计的时空分析. 中国人口·资源与环境, 2002, 12(4): 3-7.]

[6] Chen Shupeng, Chen Xiaoqiu, Zhou Chenghu. Grid mapping and grid computing. Science of Surveying and Mapping,2002, 27(4): 1-6. [陈述彭, 陈晓秋, 周成虎. 网格地图与网格计算. 测绘科学, 2002, 27(4): 1-6.]

[7] Vander K. The vector to raster conversion: (Mis)use in geographical information systems. International Journal ofGeographical Information Systems, 1992, 6(2): 159-170.

[8] Carvers S J, Brunsdon C F. Vector to raster error and feature complexity: An empirical study using simulated data.International Journal of Geographical Information Systems, 1994, 8(3): 261-270.

[9] Chen Jianjun, Zhou Chenghu, Cheng Weiming. Area error analysis of vector to raster conversion of area feature inGIS. Acta Geodaetica et Cartographica Sinica, 2007, 36(3): 344-350. [陈建军, 周成虎, 程维明. GIS中面状要素矢量栅格化的面积误差分析. 测绘学报, 2007, 36(3): 344-350.]

[10] Zhao Lei. Study on scale effect of scaling with land use spatial data [D]. Beijing: China Agricultural University,2005. [赵磊. 土地利用空间数据转换的尺度效应研究[D]. 北京: 中国农业大学, 2005.]

[11] Switzer P. Estimation of the accuracy of qualitative maps//Davis J C, McCullaugh M J. Display and Analysis ofSpatial Data. New York: John Wiley & Sons, 1975: 380-392.

[12] Galton A. Granularity-sensitive spatial attributes. Spatial Cognition and Computation, 2003, 3(2/3): 97-118.

[13] Liu Mingliang, Tang Xianming, Liu Jiyuan et al. Research on scaling effect based on 1 km grid cell data. Journal ofRemote Sensing, 2001, 5(3): 183-190. [刘明亮, 唐先明, 刘纪远等. 基于1km格网的空间数据尺度效应研究. 遥感学报, 2001, 5(3): 183-190.]

[14] Cui Buli, Chang Xueli, Zuo Denghua et al. Rasterizing vector data and its scaling effect for a sand landscape. ActaEcologica Sinica, 2009, 29(5): 2463-2472. [崔步礼, 常学礼, 左登华等. 沙地景观中矢量数据栅格化方法及尺度效应.生态学报, 2009, 29(5): 2463-2472.]

[15] Zhang Zengxiang, Wang Xiao, Wang Changyao et al. National land cover mapping by remote sensing under the control of interpreted data. Journal of Geo-Information Science, 2009, 11(2): 216-224. [张增祥, 汪潇, 王长耀等. 基于框架数据控制的全国土地覆盖遥感制图研究. 地球信息科学学报, 2009, 11(2): 216-224.]

[16] Ling B, Butler R. Comparing effects of aggregation methods on statistical and spatial properties of simulated spatial data.Photogram metric Engineering & Remote Sensing, 1999, 65(1): 73-84.

[17] Zhou Chenghu, Ou Yang, Yang Liao et al. Vector polygon grid optimization model of the insurance product. Science inChina: Series D, 2006, 36(suppl.II): 157-163. [周成虎, 欧阳, 杨辽等. 矢量多边形栅格化的保积优化模型. 中国科学:D辑, 2006, 36(增刊II): 157-163.]

[18] Wu Guangchen, Zuo Jianzhang, Liu Yan et al. A high-effective algorithm for rasterization of vector data: Windingnumber algorithm. Science of Surveying and Mapping, 2009, 34(1): 50-52. [武广臣, 左建章, 刘艳等. 矢量数据栅格化的一种有效方法: 环绕数法. 测绘科学, 2009, 34(1):50-52.]

[19] Wang Xiaoli, Sun Qinghui, Jiang Chengshun. An optimization algorithm for transferring vector to raster data based onminimized area error. Acta Geodaetica et Cartographica Sinica, 2006, 35(3): 273-277. [王晓理, 孙庆辉, 江成顺. 面积误差最小约束下矢量数据向栅格数据转换的优化算法. 测绘学报, 2006, 35(3): 273-277.]

[20] Liao Shunbao, Bai Yan. A new grid-cell-based method for error evaluation of vector-to-raster conversion. ComputationalGeosciences, 2010, 14(4): 539-549.

[21] Bai Yan, Liao Shunbao. Implement method of vector data rasterization without attribute information loss. Journal ofGeo-Information Science, 2010, 12(3): 385-391. [白燕, 廖顺宝. 矢量数据属性信息无损栅格化的实现方法. 地球信息科学学报, 2010, 12(3): 385-391.]

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

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