光学学报, 2017, 37 (5): 0528002, 网络出版: 2017-05-05   

基于自定义投影网格的多角度多源遥感数据空间位置精确配准

Accurate Spatial Co-Registration of Multi-Angle Multi-Source Remote Sensing Data Based on Self-Defined Projection Grids
作者单位
1 吉林大学地球探测科学与技术学院, 吉林 长春 130026
2 吉林省防雷减灾中心, 吉林 长春 130062
摘要
提出了一种基于自定义投影网格的多角度、多源遥感数据空间位置精确配准方法。以美国地球观测卫星(EOS)上搭载的多角度成像光谱辐射仪(MISR) L2级产品与中分辨率成像光谱仪(MODIS) L3级产品的空间位置精确配准为例, 分析比较了软件ENVI、HEG、MRT及所提方法对两种产品进行投影变换时的数据处理能力。将欧洲空间局环境卫星ENVISAT的先进沿轨扫描辐射计(AATSR)数据与MISR L2级产品及MODIS L3级产品数据进行配准, 对所提方法进行验证。所提方法解决了常用遥感软件不能直接将MISR L2级产品数据与其他遥感数据进行空间位置精确配准的问题, 且对科学数据仅进行一次重采样, 避免了反复重采样可能造成的信息损失。对于类似多角度遥感数据的空间位置精确配准, 所提方法的基本思路和目标同样有效。
Abstract
An accurate spatial co-registration method for multi-angle multi-source remote sensing data based on self-defined projection grids is proposed. Taking the accurate spatial co-registration between the multi-angle imaging spectroradiometer (MISR) L2 products and moderate-resolution imaging spectroradiometer (MODIS) L3 products carried on American earth observation satellite (EOS) as an example, the data processing abilities of ENVI, HEG, MRT softwares and the proposed method when the reprojection is performed on two kinds of products are compared and analyzed. In order to verify the proposed method, the advanced along track scanning radiometer (AATSR) data from the environmental satellite ENVISAT of European Space Agency are co-registered with the MISR and MODIS data. The proposed method solves the problem that MISR L2 product data cannot be directly and accurately registered with other remote sensing data by using common remote sensing data processing softwares, which only resamples once and can avoid the possible information loss caused by repeated resamples. The basic ideas and objectives of the proposed method are also applicable to the spatial accurate co-registration of other similar multi-angle remote sensing data.

李健, 陈圣波, 王羽飞, 于岩. 基于自定义投影网格的多角度多源遥感数据空间位置精确配准[J]. 光学学报, 2017, 37(5): 0528002. Li Jian, Chen Shengbo, Wang Yufei, Yu Yan. Accurate Spatial Co-Registration of Multi-Angle Multi-Source Remote Sensing Data Based on Self-Defined Projection Grids[J]. Acta Optica Sinica, 2017, 37(5): 0528002.

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