以位于云贵高原至广西丘陵倾斜面上的云南省富宁县为研究区,提出了适合研究区地形特点的地貌形态分类指标体系;基于 SRTM DEM 90 m 分辨率的地形数据,用均值变点分析法,确定8像元×8像元(0.5184 km^2)的格网为该县地形起伏...以位于云贵高原至广西丘陵倾斜面上的云南省富宁县为研究区,提出了适合研究区地形特点的地貌形态分类指标体系;基于 SRTM DEM 90 m 分辨率的地形数据,用均值变点分析法,确定8像元×8像元(0.5184 km^2)的格网为该县地形起伏度的最佳统计单元,据此提取了该县地形起伏度(0~707 m);最后,叠加分析了该县绝对海拔和地形起伏度数据,得到12种基本地貌形态,并得出结论:小起伏较低山、小起伏中山是该县最主要的地貌形态。展开更多
PU (phase unwrapping) is the key step and important problem in DEM (digital elevation model) extraction and the measurement of surface deformation of InSAR (Interferometric synthetic aperture radar). The CKFPUA ...PU (phase unwrapping) is the key step and important problem in DEM (digital elevation model) extraction and the measurement of surface deformation of InSAR (Interferometric synthetic aperture radar). The CKFPUA (conventional Kalman filter phase unwrapping algorithm) can obtain reliable results in the flat terrain areas, but it caused error transmission not making the accurate inversion of surface deformation information in the steep terrain. Considering this situation, so it needs to introduce topographic information for guiding phase unwrapping. Here the 90 m resolution DEM data have been used and it is obtained by SRTM (shuttle radar topography mission) measured jointly by NASA (National Aeronautics and Space Administration) and NIMA (National Imaging Mapping Agency) of U.S. Department of Defense. This paper presents a SD-KFPUA (Kalman filter phase unwrapping algorithm) based on SRTM DEM. With SRTM DEM directing InSAR image to implement phase unwrapping, the speed and accuracy are improved. By analyzing with the conventional Kalman filter phase unwrapping algorithms, it is shown that the proposed method can achieve good results in particular to improve unwrapping accuracy in the low coherence region.展开更多
文摘以位于云贵高原至广西丘陵倾斜面上的云南省富宁县为研究区,提出了适合研究区地形特点的地貌形态分类指标体系;基于 SRTM DEM 90 m 分辨率的地形数据,用均值变点分析法,确定8像元×8像元(0.5184 km^2)的格网为该县地形起伏度的最佳统计单元,据此提取了该县地形起伏度(0~707 m);最后,叠加分析了该县绝对海拔和地形起伏度数据,得到12种基本地貌形态,并得出结论:小起伏较低山、小起伏中山是该县最主要的地貌形态。
基金Acknowledgments The research is supported by the National Science Foundation of China (40874001) and National 863 plans projects of China (2009AA12Z147). The authors would like to express thanks to ESA (European Space Agency) for providing ENVISAT satellite data.
文摘PU (phase unwrapping) is the key step and important problem in DEM (digital elevation model) extraction and the measurement of surface deformation of InSAR (Interferometric synthetic aperture radar). The CKFPUA (conventional Kalman filter phase unwrapping algorithm) can obtain reliable results in the flat terrain areas, but it caused error transmission not making the accurate inversion of surface deformation information in the steep terrain. Considering this situation, so it needs to introduce topographic information for guiding phase unwrapping. Here the 90 m resolution DEM data have been used and it is obtained by SRTM (shuttle radar topography mission) measured jointly by NASA (National Aeronautics and Space Administration) and NIMA (National Imaging Mapping Agency) of U.S. Department of Defense. This paper presents a SD-KFPUA (Kalman filter phase unwrapping algorithm) based on SRTM DEM. With SRTM DEM directing InSAR image to implement phase unwrapping, the speed and accuracy are improved. By analyzing with the conventional Kalman filter phase unwrapping algorithms, it is shown that the proposed method can achieve good results in particular to improve unwrapping accuracy in the low coherence region.