地理科学进展 ›› 2012, Vol. 31 ›› Issue (12): 1574-1582.doi: 10.11820/dlkxjz.2012.12.002

• 模型与方法 • 上一篇    下一篇

空间尺度转换数据精度评价的准则和方法

徐芝英1,2, 胡云锋1, 刘越1,2, 艳燕1   

  1. 1. 中国科学院地理科学与资源研究所, 北京100101;
    2. 中国科学院研究生院, 北京100049
  • 收稿日期:2012-05-01 修回日期:2012-08-01 出版日期:2012-12-25 发布日期:2012-12-25
  • 通讯作者: 胡云锋(1974-),男,副研究员,主要从事资源环境遥感与地理信息技术应用研究。E-mail:huyf@ireis.ac.cn E-mail:huyf@ireis.ac.cn
  • 作者简介:徐芝英(1987-),女,硕士研究生,主要从事空间尺度转换研究。E-mail:xuzyhappy11@gmail.com
  • 基金资助:

    科技部973 计划项目(2010CB950904);国家自然科学基金项目(40971223);国家科技支撑计划项目(2008BAH31B04)。

A Review on the Accuracy Analysis of Spatial Scaling Data

XU Zhiying1,2, HU Yunfeng1, LIU Yue1,2, YAN Yan1   

  1. 1. Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China;
    2. Graduate University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2012-05-01 Revised:2012-08-01 Online:2012-12-25 Published:2012-12-25

摘要: 空间尺度问题是地理学、生态学和水文学等多个学科的基础科学问题之一。空间数据尺度转换是将数据从一个空间尺度转换到另一个空间尺度的过程, 它是尺度科学研究的重要内容之一。对尺度转换后的成果数据深入分析, 提炼尺度转换成果数据精度评价的原则、指标以及模型方法, 这对正确选择和应用尺度转换成果数据具有重要意义。在详细评述尺度和尺度转换研究概念、内容和主要进展的基础上, 本文主要从数据处理、地图学角度出发, 提出了空间数据尺度转换精度评价的3 项基本准则, 即保持构成信息守恒、保持面积信息守恒、保持区域空间格局和形态信息守恒。继而据此将当前常见的指标进行了梳理和归并;根据上述准则和指标, 结合GIS 方法、常规统计方法、地统计方法等, 给出了上述评价指标的计算模型及其应用方法和典型案例。最后指出, 在实际应用中需结合研究目标, 针对性选择尺度转换效应函数, 通过开展模型模拟和对比分析, 最终确定合适的尺度转换方法。

关键词: 尺度, 尺度转换, 精度评价, 数学模型, 准则

Abstract: Scale is like a lens through which geographers observe and study the world. Scale dependence is one of the key studies and a challenge in geography, ecology, hydrology and meteorology in recent decades. One of the core scale issues is spatial scaling. Different scaling methods produce different resulting data with different degree of information loss. Thus, quantitative and qualitative assessment of scaling accuracy for spatial data is critical for correctly understanding and using scales. In the scaling research the basic theoretical frameworks include level theory, fractal theory, regional variable theory and first law of geography. In eco-geographical fields, scaling methods mainly are: spatial allometry, the dynamic model-based scaling method, wavelet analysis, autocorrelation analysis, fractal methods, semi-variogram method, and so forth. For the last ten years, remote sensing, GIS, and large-scale computer simulation technology have become more and more important in scaling research. As an important part of scaling process, accuracy analysis qualitatively or quantitatively evaluates the resulting data, based on the rules such as spatial composition, area precision, spatial pattern, patch characteristics, etc. Certain evaluation models and methods also involve type area statistics, landscape metrics, geostatistics, wavelets analysis, etc., with several indexes. In addition, comparing the simulation results of scaling data is also an important method in accuracy analysis. Although there are several methods of scaling accuracy analysis, few researchers have tried to develop a systematic methodology to evaluate resulting data. Therefore, it is an inevitable trend in scaling research to improve or even develop a new methodology for scaling accuracy analysis.

Key words: accuracy assessment, mathematic model, principle, scale, scaling transformation