面向对象的机载LiDAR数据建筑物提取

doi:10.3969/j.issn.0255-8297.2016.01.010

Abstract

Abstract: Based on airborne LiDAR data, an object-based method for building extraction with coarse-fine accuracies is proposed. A normalized digital surface model (nDSM) and the normalized difference (ND) are extracted from the LiDAR data. Special edge echo points are removed from the ND data using a morphological operator. Taking into consideration height and penetrability of the buildings, coarse profile of the buildings are extracted from ND and nDSM data using a threshold segmentation algorithm. A multi-resolution segmentation algorithm is then used to segment the candidate buildings by integrating intensity, and the nDSM/ND data. The segmentation result is further optimized by merging the adjacent objects with smaller brightness difference. Finally intensive buildings are extracted based on spectral and geometrical characteristics, and the spatial relations of objects. Experiment results show that the proposed method can obtain buildings with high precision, and provides a means for building extraction from airborne LiDAR data.

Key words: airborne LiDAR, building extraction, object-based method, multi-resolution segmentation

CLC Number:

TP237

FAN Jing-jing, ZHANG Hua, HAO Ming. Object-Based Building Extraction from Airborne LiDAR Data[J]. Journal of Applied Sciences, 2016, 34(1): 84-94.

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Object-Based Building Extraction from Airborne LiDAR Data

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