ABSTRACT Extraction of urban objects, and analysis of two- and three-dimensional (2D and 3D) morphological parameters, as well as 2D and 3D landscape metrics in urban environments are valuable for updating GIS databases and for civic applications, urban planning, disaster risk assessment, and climate and sustainability studies. However, few studies have reported the extraction of 3D buildings at different scales in urban areas or developed a method for accuracy evaluation. This study aims at developing a method of multi-scale 3D building information extraction (MS3DB) to fill this research gap. Surface flatness and the variance in the normal direction were extracted from the point cloud data, and gray-level co-occurrence matrix was extracted from normalized digital surface models as labeling features, which were fused into a graph-cut the algorithm to determine building labeling. In addition, 2D and 3D building morphological parameters were extracted at the grid-scale, and a set of 3D building landscape metrics were designed at the city-block scale. Accuracy of the extraction of 3D building information was evaluated at the object, grid, and block scales. The model achieved high accuracy in extracting the building labels using data from the northern part of Brooklyn, New York, USA. The results show that the MS3DB method yields limited accuracy in extracting the building edges, whereas other parameters (e.g., area, volume, and planar area index) were extracted with high accuracy at the grid scale (R2 > 0.92). The block-scale landscape analysis shows the advantages of integrating 2D and 3D features (e.g., differences in the vertical landscape) in characterizing the structure of urban buildings and exhibits moderate accuracy (R2 > 0.79).

中文翻译：

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基于航拍激光雷达数据的城市建筑多尺度三维检测

摘要 城市对象的提取、二维和三维（2D 和 3D）形态参数的分析以及城市环境中的 2D 和 3D 景观指标对于更新 GIS 数据库和公民应用、城市规划、灾害风险都很有价值评估以及气候和可持续性研究。然而，很少有研究报告在城市地区提取不同尺度的 3D 建筑物或开发出一种精度评估方法。本研究旨在开发一种多尺度 3D 建筑信息提取 (MS3DB) 方法来填补这一研究空白。从点云数据中提取表面平整度和法线方向的方差，从归一化的数字表面模型中提取灰度共生矩阵作为标记特征，将其融合到图形切割算法中以确定建筑物标记。此外，在网格尺度上提取了 2D 和 3D 建筑形态参数，并在城市街区​​尺度上设计了一套 3D 建筑景观指标。在对象、网格和块尺度上评估 3D 建筑信息提取的准确性。该模型使用来自美国纽约布鲁克林北部的数据在提取建筑物标签方面取得了高精度。结果表明，MS3DB 方法在提取建筑物边缘时产生的精度有限，而其他参数（例如，面积、体积和平面面积指数）在网格尺度（R2 > 0.92）上以高精度提取。块尺度景观分析显示了整合 2D 和 3D 特征的优势（例如，