| 地理空间数据的尺度转换 |
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| 引用本文： | 胡云锋,徐芝英,刘越,艳燕.地理空间数据的尺度转换[J].地球科学进展,2013,28(3):297-304. |
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| 作者姓名： | 胡云锋 徐芝英 刘越 艳燕 |
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| 作者单位： | 1. 中国科学院地理科学与资源研究所,北京,100101
2. 中国科学院地理科学与资源研究所,北京 100101;中国科学院大学,北京 100049 |
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| 基金项目： | 国家重点基础研究发展计划项目"大尺度土地利用变化对全球气候的影响"，国家自然科学基金项目"内蒙古中东部地区土地利用变化及其对土壤侵蚀的影响"，中国科学院知识创新工程重要方向项目"生态服务功能的梯度消耗与环境响应" |
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| 摘 要： | 尺度一般是指空间范围的大小,地理空间数据的尺度转换是尺度研究的重要问题之一。针对地理信息系统(GIS)技术支持下的地理空间数据尺度转换问题,首先回顾了尺度转换的理论基础,即等级理论、分形理论、区域化随机变量理论、地理学第一定律等理论的基本内涵;然后总结了地理学不同研究领域内主要的尺度转换方法,重点分析了重采样法、变异函数法、分形分维法及小波分析法的基本原理、模型方法与典型应用案例;最后介绍了地理空间数据尺度转换效应研究的进展。基于上述总结和分析认为:构建一套无级变换的、系统的尺度转换方法,整合不同学科领域的数据与过程模型、形成数据模型同化的技术体系,这是地理空间数据尺度转换研究的重要课题。
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| 关 键 词： | 尺度 尺度效应 转换理论 转换方法 |
A Review of the Scaling Issues of Geospatial Data |
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| Hu Yunfeng,Xu Zhiying,Liu Yue,Yan Yan.A Review of the Scaling Issues of Geospatial Data[J].Advance in Earth Sciences,2013,28(3):297-304. |
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| Authors: | Hu Yunfeng Xu Zhiying Liu Yue Yan Yan |
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| Institution: | 1.Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing100101, China;
2.University of Chinese Academy of Sciences, Beijing100049, China |
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| Abstract: | As scale is one of the three lenses from which geographers observe and recognize the world, it is of great importance to propose this concept in geographical research. All the natural or cultural phenomena cannot be scientifically observed and modelled without correct scales, thus scaling and scaling effects becoming one of the key problems in geography, ecology, hydrology and meteorology in recent decades. As a core issue in the scale problem, scaling of geospatial data serves as a necessary process in the scale researches. There are level theory, fractal theory, regional variable theory, Tobler’s first law of geography and so on, supporting as the basic theoretical framework in the scaling researches. Many effective scaling approaches reference to geospatial data have been developed, and different methods applied in different areas. In GIS area, vector data can be generalized by such methods as exaggeration, simplification, selection, displacement and other generalizing operations; raster data can be scaled with resampling, fourier analysis, wavelet analysis and fractal analysis, while the scaling methods of remote sensing image can be divided into three kinds, the scaling methods based on pixel, the methods based on imaging mechanism, and the image fusion methods. In this paper, we illustrate the mechanism and applications of four major geospatial scaling methods, i.e. resampling methods, geostatistical methods, fractal analysis and wavelet transformation. Scaling effects are also an important scaling issues, with many researchers involved in the study of geospatial variations of scaling, developing evaluation criteria of scaling, etc. Though there exist some effective scaling methods, few accuracy analysis of scaling has been developed in evaluating resulting data, and researches into scaling theories, methodologies and scaling effects still need to be deepen. Therefore, it is natural trend to develop a theoretical and methodological scaling research frame, as well as to integrated multi scale spatial data with process models of different areas. |
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| Keywords: | Scale Scaling Scaling theories Scaling methods |
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