摘要
着重阐述了地表空间信息尺度转换的必要性和方法。首先从尺度转换成因分析入手,介绍了两种普适性的尺度转换模型,即泰勒级数展开模型和计算几何模型,并对这两个模型的适用性进行了分析。借助叶面积指数的反演,针对林地、农田、水体3种不同下垫面的试验样区进行了模型的分析比较。结果表明,在拥有小尺度(高分辨率)数据时,泰勒级数模型能够很好的刻画尺度效应,使得尺度效应改正后的相对误差小于1%,获取更为准确的地表参数反演值。遥感尺度转换方法、技术为获取不同尺度的地学信息,为资源调查和环境灾害监测等相关领域的应用提供真实可靠的多尺度数据支持。
With the development of quantitative remote sensing, the scaling problems attract more and more attention. The discrepancy between observation scale, model scale and land surface process scale may lead to different conclusions. Now, how to effectively scale remotely sensed information at different scales already becomes one of the most important research focuses of remote sensing. The aim of our research is to compare and analyze two general scaling methods, the Taylor Series Expansion Model （TSM） and the Computational Geometry Model （CGM） , and apply them to the scaling of leaf area index （LAI）. Firstly, the necessity and importance of scaling are analyzed. Secondly, based on the research of description for the same object using different scale data, the mechanism of scaling effects is presented. Then, the two general models, TSM and CGM, are briefly introduced and their advantages and disadvantages are discussed in detail. Finally, through the retrieval of leaf area index, the two models are comprehensively compared and analyzed in three distinct landscapes. The result shows that the relative scaling error increases with the heterogeneity of land surface. The relative scaling error is 2% in the relatively homogeneous woodland; however, it arises up to 7% in crop-water mixed areas. Apparently, the TSM can better characterize the scale effect and obtain more accurate surface parameters when both small scale （high resolution） data and large scale （low resolution） data are available. The relative scaling error can be reduced to less than 1% for all these test landscapes when TSM is used in scaling. In contrast, CGM can not produce rational result and the relative error is still large. It may be due to using inappropriate weights or data ranges in the model. More study about CGM is needed. On the whole, it is necessary to select the suitable scaling model according to the practical applications. The scaling makes the remote sensing products at different scales comparable and the surface parameter retrieval results more accurate. Scaling technique will provide a powerful technical support for applications in resources survey, environment and disaster monitoring, and other relevant fields.
出处
《遥感学报》
EI
CSCD
北大核心
2009年第2期183-189,共7页
NATIONAL REMOTE SENSING BULLETIN
基金
国家重点基础研究发展计划项目"地表时空变化特征参数的遥感定量描述与尺度转换"(编号:2007CB714402)
中国科学院知识创新工程方向性项目(KGCX3-SYW-401)
国家杰出青年科学基金项目(编号:40425012)
