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Terrain classification of ladar data for bare earth determination

机译:雷达数据的地形分类,用于确定地球

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Terrain classification, or bare earth extraction, is an important component to LADAR data analysis. The terrain classification approach presented in this effort utilizes an adaptive lower envelope follower (ALEF) with an adaptive gradient operation for accommodations of local topography and roughness. In order to create a more robust capability, the ALEF was modified to become a strictly data driven process that facilitates a quick production of the data product without the subjective component associated with user inputs. This automated technique was tested on existing LADAR surveys over Wyoming's Powder River Basin and the John Starr Memorial Forest in Mississippi, both locations with dynamic topographic features. The results indicate a useful approach in terms of operational time and accuracy of the final bare earth recovery with the advantage of being fully data driven
机译:地形分类或裸露提取是LADAR数据分析的重要组成部分。在这项工作中提出的地形分类方法利用自适应下包络线跟随器(ALEF)和自适应梯度运算来适应局部地形和粗糙度。为了创建更强大的功能,将ALEF修改为严格的数据驱动过程,以促进快速生产数据产品而无需与用户输入相关的主观组件。这项自动技术已经在怀俄明州的粉末河盆地和密西西比州的约翰·斯塔尔纪念森林上进行了现有的LADAR测量,这两个位置都具有动态地形特征。结果表明,在操作时间和最终裸露恢复的准确性方面,这是一种有用的方法,它具有完全由数据驱动的优势

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