首页 >  2008, Vol. 12, Issue (4) : 1993-2002

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10.11834/jrs.20080470

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遥感影像空间尺度特性与最佳空间分辨率选择
1.中国地质大学(北京)信息工程学院,北京 100083;2.中国农业大学信息与电气工程学院,北京 100083
摘要:

尺度概念是理解地球系统复杂性的关键,尺度问题被认为是对地观测的主要挑战之一,而结合具体研究应用领域,由地学现象的尺度本身出发,选择所需遥感影像的最佳尺度和分辨率,是非常有现实意义的.本文在深入剖析了遥感影像的尺度特性和遥感影像尺度选择的意义的基础上,探讨了基于地统计学方法定量选择遥感影像最佳空间分辨率的方法.阐明了传统局部方差方法不能得到理想结果的原因:传统的局部方差方法的实质是基于变化地面面积计算影像局部方差的均值,而基于这样不同甚至是相差悬殊的地面面积进行局部方差计算,其结果必然不具有可比性.对此,本文提出了基于可变窗口与可变分辨率的改进局部方差方法,即依次降低空间分辨率时,高分辨率采用大窗口尺寸,低分辨率采用小窗口尺寸来维持计算窗口内的地面面积的一致,由此计算出的局部方差作比较来判定遥感影像最佳分辨率.进行了系列实验分析,得到了相关结论,分析得出这种基于地统计的方法来选择遥感影像最佳分辨率的方法,对遥感和GIS研究与地学应用具有一定的理论意义和指导意义.

Spatial Scale of Remote Sensing Image and Selection of Optimal Spatial Resolution
Abstract:

Scale is a key concept forunderstanding the complexity ofearth system. And it is regarded asone of themain challenges ofearth observation. It is crucial to select the optmi al spatial resolution ofremote sensing mi age according to its application field and its characteristics. Based on analyzing the scale characteristic of remote sensing mi ages, this paper analyses the scale selection and discusses geo-statistics based method of quantificationally selecting the optmi al spatial resolution of remote sensing mi age. Especially, this paper analyses traditional local variancemethod and its defects. As for local variancemethod, it is suggested tomeasure the relationship between the size of the objects in the scene and spatial resolution, and then calculate the mean value of the standard deviation by passing a n pixel by n pixelmoving window for each pixel on successively spatially degraded mi ages, and then takes the mean of all local variances of the successively spatially degraded mi ages as an indication of the spatial elementswithin the scene of the mi age, according to which the optmi al spatial resolution whose mean local variance ismaxmi um can be estmi ated. So the traditional local variancemethod computes the mean of all local variance on the different ground area, which results in that the local variance does not fall substantiallywith the successively degradation of spatial resolution of the mi age, consequently the computational results are non-comparable, and the traditionalmethod can notachieve satisfactory result. Breaking through the lmi itation, this paper proposes the modified local variance method based on variable window sizes and variable resolution to quantitatively select the optmi al spatial resolution of remote sensing mi ages, which are high spatial resolution\nmi ageswith largewindow size and low spatial resolution mi ageswith smallwindow size, so that the relevantground area is kept consistent. The actual process inevitably involves the ideal decmi alwindow size, which is proposed to be computed based on the spatial statistics theory. Consequently, the optmi al spatial resolution of remote sensing mi age can be computed by comparing themodifiedmean local variance. This paper takes three pieces of IKONOS mi ageswhich stand forbuilding district, farmland and forest individually as prmi ary expermi ental miage and themodified local variances are computed for the three kindsof landscape individually. The expermi ental results show that thisgeo-statisticsbasedmethod\nof quantificationally selecting the optmi al spatial resolution of remote sensing mi age has theoretical and instructional meaning: the spatial resolution of3—5m, 3—5m and 1—5m is respectively suitable for landscape of building district,farmland and forest; only the local variance based on variablewindow size and variable resolution can indicate the actual change of local variance with the degradation of spatial resolution of the mi age; local variance method adopts proper window size to reflect the change of landscape property, so it can reflect themicro-characters and is suitable for study on the fine scale landscape or the artificial landscape.

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