Technology and Methodology |
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Object-based Point Clouds Classification of the Vegetation and Building Overlapped Area |
XU Hong-gen1,2, WANG Jian-chao1, ZHENG Xiong-wei1, WU Fang1, LI Qian1 |
1. China Aero Geophysical Survey and Remote Sensing Center for Land and Resources, Beijing 100083, China;
2. Wuhan Center of Geological Survey, Wuhan 430205, China |
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Abstract This paper proposes an object-oriented point clouds classification method for solving the difficult classification problem for the overlapping between vegetation and buildings based on reviewing current status of LiDAR point clouds classification approaches. In the proposed method, the point clouds are firstly separated into ground points and non-ground points through adaptive TIN filter method, and the DTM is obtained. Second, a triangle network is constructed for non-ground points higher than DTM. The non-ground point clouds could be divided into multi-objects by removing longer edges (edge between ground and object). Then, the object is judged to decide whether it belongs to vegetation or building according to its information entropy of triangle network slope. Finally, for objects difficult to be distinguished from other objects, the overlapped area between vegetation and buildings is extended by geometric shape of buildings, so that the accuracy of point clouds classification of the overlapped area could be improved. The experiment results show good classification performance for buildings and vegetation, and the accuracy reaches 87%.
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Keywords
water erosion desertification
the three gorges
remote sensing
dynamic monitoring
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Issue Date: 03 June 2012
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[1] Filin S,Pfeifer N.Segmentation of Airborne Laser Scanning Data Using a Slope Adaptive Neighborhood[J].ISPRS Journal of Photogrammetry and Remote Sensing,2006,60(2):71-80.[2] Vosselman G,Dijkman S.3D Building Model Reconstruction from Point Clouds and Ground Plans[J].International Aachives of Photogrammetry Remote Sensing and Spatial Information Sciences,2001,34(3/w4):37-44.[3] Höfle B,Geist T,Rutzinger M,et al.Glacier Surface Segmentation Using Airborne Laser Scanning Point Cloud and Intensity Data[J].Remote Sensing and Spatial Information Sciences,2007(3/w52):195-200.[4] Miliaresis G,Kokkas N.Segmentation and Object-based Classification for the Extraction of the Building Class from LiDAR DEMs[J].Computers & Geosciences,2007,33(8):1076-1087.[5] Lodha S K,Kreps E J,Helmbold D P,et al.Aerial LiDAR Data Classification Using Support Vector Machines(SVM)[C]//Proceedings of the Conference on 3DPVT,2006,3(4):567-574.[6] Chen Q,Gong P,Baldocchi D,et al.Filtering Airborne Laser Scanning Data with Morphological Methods[J].Photogrammetric Engineering and Remote Sensing,2007,73(2):175.[7] Zhang K Q,Chen S C,Whitman D,et al.A Progressive Morphological Filter for Removing Nonground Measurements from Airborne LiDAR Data[J].IEEE Transactions on Geoscience and Remote Sensing,2003,41(4):872-882.[8] Kraus K,Rieger W.Processing of Laser Scanning Data for Wooded Areas[J].Fritsch and Spiller,Editors,Photogrammetric Week,1999,99:221-231.[9] Lee H S,Younan N H.DTM Eextraction of LiDAR Returns Via Adaptive Processing[J].IEEE Transactions on Geoscience and Remote Sensing,2003,41(9):2063-2069.[10] Axelsson P.DEM Generation from Laser Scanner Data Using Adaptive TIN Models[J].International Archives of Photogrammetry and Remote Sensing,2000,33(B4/1;PART 4):110-117.[11] Elmqvist M,Jungert E,Lantz F,et al.Terrain Modelling and Analysis Using Laser Scanner Data[J].IAPRS,2001,34(3/w4):219-224.[12] 张靖,李乐林,江万寿.基于等高线簇分析的复杂建筑物模型重建方法[J].地球信息科学学报,2010,12(5):641-648. |
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