Development of NOAA Remote Sensed Data Processing System for Academic Global Research

本研究的目的是开发一套NOAA卫星图像综合处理系统，该系统能够自动接收卫星图像数据并生成碳化温度图。为了加快向用户提供图像的速度，我们引入了一种并行处理卫星图像的方法。首先，我们并行化了辐射校正程序，它几乎可以独立地逐像素处理。得到线性加速。其次，将几何校正程序并行化。这个程序不像放射法那么简单。我们建立了一种新的椭圆模型来计算映射误差，从而获得高质量的图像。通过匹配半岛、海湾等特征点进行映射，可以并行处理。然后将原始地图分解为一定尺寸的网格，并进行变换，生成特定的坐标地图。网格尺寸是一个关键参数，我们通过在多个区域的多次实验最终得到了最优的网格尺寸。对修正误差进行了定量分析。所有程序都在共享内存多处理器系统上实现。我们可以在串行计算机上获得比目前使用的大型计算机更高的性能。

The objective of this research is to develop an integrated NOAA satellite imagery processing system which automatically receives the image data from the satellite and generates cariburated temperature map.In order to speed-up the image delivery service to the users, we introduced a parallel processing approach for sattelite image processing. First we parallelized the radiometric correction routine, which can be processed almost independently pixel by pixel.Linear speed up was obtained. Second the geometric correction routine was parallelized. This routine was not so easy as the radiometric one. We developed a novel elliptic model to caribulate the mapping error, through which we could obtain very high quality image. The mapping is performed by matching some characteristic points such as peninsula and gulf, which can be processed in parallel. After that the original map is decomposed into mesh of certain size and transformed to generate specific coordinated map. The size of mesh is a key parameter, which we finally obtained optimally through several experiments over a number of areas. The quantitative analysis of the correction error is also examined in detail. All the routine was implemented on the shared memory multi-processor system, sequent s81. We could attain higher performance on sequent than on mainframe computer which we have so far used.