Systematic approach for precise correction and landcover classification of satellite images

在崎岖地形上的卫星图像中，我们可以发现一些地形效应与大气效应纠缠在一起。如果不对这些影响进行校正，就很难对卫星图像进行土地覆盖分类和自然环境的多时相监测。为了在计算机上再现这些地形效应，需要具有与卫星图像相同的地图投影和空间分辨率的数字高程模型(DEM)。本文根据遥感原理，对卫星影像进行了系统化处理，并将其应用于陆地卫星TM影像。利用模拟的太阳直接辐射图像，利用提出的几何校正方法，实现了卫星图像在DEM上的自动叠加。基于卫星水平辐射物理模型的地形效应校正方法也被发展到太阳高度较高的卫星图像上。我们还提出将土地覆盖建模为一个镶嵌的空间结构，并首先对图像进行空间分割。然后，将混合像素确定为邻域内具有确定端元的边界像素。

In satellite images over rugged terrain, we can find some topographic effects entangled with atmospheric effects. Without correcting these effects, it is difficult to evaluate the satellite images for land cover classification and multi-temporal monitoring of natural environment. In order to reproduce these topographic effects in computer, we need digital elevation model(DEM) with the same map projection and spatial resolution as the satellite image concerned. The DEM is also required for accurate ortho-rectification of the satellite Image.In this research project, we systemize satellite image processing based on the principles of remote sensing, which is applied to Landsat TM images. The satellite images are automatically laid over the DEM by using the proposing geometric correction method which utilizes the simulated direct solar irradiance image. Advanced methods for topographic effect correction based on a physical model of satellite level radiance is also developed to a satellite image with high solar elevation.We also propose to model land cover as a tesselated spatial structure and apply the spatial segmentation to the image first. Then, mixed pixels are determined as the boundary pixels with definite end members found in neighborhood.