Accuracy assessment of automatically derived digital elevation models from aster data in mountainous terrain

被引:58
|
作者
Eckert, S [1 ]
Kellenberger, T [1 ]
Itten, K [1 ]
机构
[1] Univ Zurich, Dept Geog, RSL, CH-8057 Zurich, Switzerland
关键词
D O I
10.1080/0143116042000298306
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
The Advanced Spaceborne Thermal Emission and Reflection Radiometer ( ASTER) aboard the Terra satellite was designed to generate along-track stereo images. The data are available at low cost, providing a feasible opportunity for generating digital elevation models (DEMs) in areas where little or no elevation data are yet available. This study evaluates the accuracy of DEMs extracted from ASTER data covering mountainous terrain. For an assessment of the achieved accuracies in the Andean study site, comparisons were made to similar topographical conditions in Switzerland, where reference data were available. All raw DEMs were filtered and interpolated by the post-processing tools included with PCI Geomatica, the software package used. After carefully checking the DEM quality, further post-processing was undertaken to eliminate obvious artefacts such as peaks and sinks. Accuracy was tested by comparing the DEMs in the Swiss Alps to three reference models. The achieved results of the generated DEMs are promising, considering the extreme terrain. Given accurate and well-distributed ground control points (GCPs), it is possible to generate DEMs with a root mean square (RMS) error between 15m and 20m in hilly terrain and about 30m in mountainous terrain. The DEMs are very accurate in nearly flat regions and on smooth slopes with southern expositions: errors are generally within +/- 10m in those cases. Larger errors do appear in forested, snow covered or shady areas and at steep cliffs and deep valleys with extreme errors of a few hundred metres. The evaluation showed that the quality of the DEMs is sufficient for enabling atmospheric, topographic and geometric correction to various satellite datasets and for deriving additional products.
引用
收藏
页码:1943 / 1957
页数:15
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