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Algorithm for image fusion based on DEM and remote sensing image

机译：基于DEM和遥感图像的图像融合算法

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Terrain roughness and vegetation growth are important influence factors of environment. But it is very difficult to describe the terrain roughness in remote sensing image. Although with the launch of TERRA, Moderate resolution Imaging Spectroradiometer (MODIS), with abundant information, quickly acquiring data and wide range of coverage, is a new data for classication of land area. Considering terrain is still very important problem. This study considered the characteristics of Zhejiang land planting. The digital slope image derived from the DEM map and multitemporal MODIS were used for the purpose of improving the classification accuracy of MODIS in large hilly region. Two methods have been employed till now. One is visual interpretation using digital images, and the other is the automated extraction of landform characteristics from DEM. Thus,the results obtained from the first method are difficult for future use. As to the second method, it is difficult to get detailed classifications for example, to distinguish a valley plain from an open plain by using DEM alone due to the complex nature in landform characteristics. In fact, DEM and digital image contain different, yet complementary, information related to landform features. Therefore, a new method to integrate landform information of both DEM and MODIS and NOAA-AVHRR image by digitizing signing lines in MODIS and NOAA-AVHRR image is presented in this paper. With this approach, different results of basic landforms were successfully classified and mapped automatically in Zhejiang Province. In addition, the spatial variability of accuracy in classification was also evaluated by sampling points based on an application of Globe positioning system (GPS).
机译：地形粗糙度和植被生长是影响环境的重要因素。但是很难描述遥感图像中的地形粗糙度。尽管随着TERRA的推出，中分辨率成像分光光度计（MODIS）具有丰富的信息，快速获取数据和广泛的覆盖范围，却是用于土地面积分类的新数据。考虑地形仍然是非常重要的问题。本研究考虑了浙江土地种植的特点。为了提高大丘陵区MODIS的分类精度，采用了由DEM图和多时相MODIS得到的数字斜率图像。迄今为止，已经采用了两种方法。一种是使用数字图像的视觉解释，另一种是从DEM中自动提取地形特征。因此，从第一种方法获得的结果难以将来使用。至于第二种方法，由于地貌特征的复杂性，很难仅通过DEM来获得详细的分类，例如，将山谷平原与开放平原区分开。实际上，DEM和数字图像包含与地形特征有关的不同但互补的信息。因此，本文提出了一种通过数字化MODIS和NOAA-AVHRR图像中的符号线来整合DEM和MODIS和NOAA-AVHRR图像的地形信息的新方法。通过这种方法，成功地对浙江省不同的基本地貌结果进行了自动分类和制图。此外，还基于全球定位系统（GPS）的应用通过采样点评估了分类准确性的空间变异性。

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