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Impact analysis of different spatial resolution DEM on object-oriented landslide extraction from high resolution remote sensing images

机译:不同空间分辨率DEM对高分辨率遥感影像面向对象滑坡提取的影响分析

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Information extraction of landslides is a critical issue for the disaster hazard analysis. Although DEM (Digital Elevation Model) is an important feature for landslide recognition, it's difficult to obtain the high-resolution DEM in study areas in practical application. In order to analyze the impact of DEM resolution on landslide extraction and to determine the resolution to the meet application requirements, we resample the DEM data into five groups on different spatial resolution and then adopt the object-oriented method to extract the landslides information to combine with high-resolution images. The experimental results show that, when the DEM resolution is greater than 30 meters, we can obtain better recognition and classification results for the landslide with area greater than 5000m2. When the resolution is less than 30 meters, it is difficult to distinguish between landslide types, but by adjusting parameter values we can still achieve the detection of landslides. This research has certain guiding significance and reference value for the selection of DEM spatial resolution on the landslides information extraction.
机译:信息提取滑坡是灾害风险分析的关键问题。尽管DEM(数字高程模型)是滑坡识别的重要特征,但在实际应用中很难获得研究区域的高分辨率DEM。为了分析DEM分辨率对滑坡提取的影响并确定分辨率是否满足应用要求,我们将DEM数据重新采样为五个具有不同空间分辨率的组,然后采用面向对象的方法提取滑坡信息以进行组合与高分辨率的图像。实验结果表明,当DEM分辨率大于30米时,对于面积大于5000m 2 的滑坡可以获得更好的识别和分类结果。当分辨率小于30米时,很难区分滑坡类型,但是通过调整参数值,我们仍然可以实现滑坡的检测。该研究对滑坡信息提取中DEM空间分辨率的选择具有一定的指导意义和参考价值。

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