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The characterization of digital surface model from stereo imagery over vegetated areas

机译:植物区立体图像数字型材模型的表征

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Some researches in the field of surveying and mapping showed that it held potentials to derive vegetation height from stereo imagery. However, most of current researches were conducted on aerial images or spaceborne images with very high resolutions (about 0.5 m). The resolution of stereo sensors with global coverage is always not so high. The characteristics of digital surface models (DSMs) should be affected by image resolutions because the DSM from stereo imagery was directly determined by the cloud of common points from the pair of stereo images while the automatic recognition of common points depended on the image textures. More stereo imagery has been and will be acquired by ALOS/PRISM and Chinese ZY03 with the resolution of about 2~4 m. Therefore, the characteristics of DSM from high stereo imagery at the resolution of 2-4 m over vegetated areas should be investigated. In this study, an automatic procedure for the extraction of DSM from stereo imagery and a method for the estimation of vegetation height from DSM were proposed. The experiments results showed that the method for the automatic extraction of DSM worked well and the estimation of vegetation height was valid at sparse forest.
机译:测量和映射领域的一些研究表明,它持有潜在的巨大从立体图像衍生植被高度。然而,大多数当前研究在空中图像或具有非常高的分辨率(约0.5μm)的空中图像或星载图像上进行。具有全球覆盖率的立体声传感器的分辨率总是不那么高。数字表面模型(DSMS)的特征应该受到图像分辨率的影响,因为来自立体图像的DSM由来自一对立体图像的共同点的云直接确定,而在自动识别公共点依赖于图像纹理。更加立体声的图像已被Alos / Prism和ChineseZy03获得,分辨率约为2〜4米。因此,应研究高位立体图像的DSM的特点,应在植被区域2-4米的分辨率下进行。在该研究中,提出了一种从立体图像提取DSM的自动过程和估计来自DSM的植被高度的方法。实验结果表明,自动提取DSM的方法井井井,植被高度的估计在稀疏森林中是有效的。

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