FY-3A中分辨率光谱成像仪图像地理定位方法

Geolocation Approach for FY-3A MERSI Remote Sensing Image

风云三号A星(FY-3A)中分辨率光谱成像仪(MERSI)采用45°镜旋转扫描,形成垂直于卫星飞行轨迹的360°连续圆周扫描方式,多元探测器并扫的技术。该研究依据这种扫描特性,给出了适用于FY3A MERSI遥感图像地理定位的方法;定义了完善的坐标系及坐标系转换关系,根据MERSI观测几何、卫星空间位置和姿态、仪器空间位置和指向建立了探测器像元观测矢量与地面位置之间关系的模型;通过地形校正消除地形起伏带来的定位误差;在FY 3A地面应用系统中业务运行的同时,通过一定数量的地面控制点分析,将定位误差等效为遥感仪器安装误差,修正了MERSI的仪器指向角度。实验结果表明,使用该方法对MERSI遥感图像地理定位精度达到250 m像元级,满足MERSI图像的高精度定位要求。

Fengyun 3 series are second generation polar-orbiting meteorological satellites in China. The first sat- ellite of Fengyun 3 series, FY-3A, is a research and development satellite and is launched successfully at 1100 BT 27 May 2008. The Medium Resolution Spectral Imager （MERSI） is a main payload of FY-3A spacecraft and since June 2008, it has been acquiring daily global data in 20 spectral bands from the visible to the thermal infrared-15 with 1 km and 5 channels with 250 m spatial resolution at nadir. In order to sat- isfy the requirements of quantitative application, MERSI data need to be geolocated, which can provide ac- curate latitude and longitude information for follow-up remote sensing productions. The geolocation algo- rithm of MERSI data, which is adapted by National Satellite Meteorological Center （NSMC）, is intro- duced in details, as well as the error analysis. MERSI rotates a 45~ mirror to get 360~ views across the orbit direction. MERSI is a paddle broom e- lectro-optical instrument that uses the forward motion of the satellite to provide the along-track direction of scanning. MERSI simultaneously senses, in each band, 10 rows of 1 km detector pixels and 40 rows of 250 m detector pixels. The MERSI detectors are grouped on four focal planes. Detectors for each band are laid on the focal planes in the along-scan direction. MERSI swath is about 2000 km, and generates about 140 GB data per day. According to the characteristics above, parameter method is used for MERSI remote sensing data geo- location. This approach creates the spatial relationship model between the sensed data and the earth based coordinate system, according to MERSI scanning mode, sensing geometry, satellite/sensor＇s attitude and position. There are 10 coordinate systems and 9 rotated relationships involved in the model. Since 45 ~ mir- ror brings image rotation, there is a module removing the rotation in the model. When processing data, the line-of-sight vector from each detector of a band is calculated in the instru-ment coordinate system first. Then the line-of-sight and satellite position are rotated to the earth centered rotating coordinates. The intersection of the line-of-sight with the WGS-84 ellipsoid is calculated. An iter- ative search process is used to follow the line-of-sight from the instrument to the intersection of the terrain surface represented by a DEM. This geolocation approach for MERSI has been applied to FY-3A data pre- processing system. Five factors that influence the accuracy of results are analyzed. These factors include satellite posi- tion/velocity error, satellite attitude error, satellite-instrument installation error, instrument-inner geome- try error and instrument thermal distortion. Compared geolocation results with the true remote sensing image using the land-water mask, it shows that the error alone the orbit direction is about 0. 167 km and the error along the scanning direction is about 0. 058 km. This geoloeation approach for MERSI （250 m） achieves accuracy up to 1 pixel.