Adaptive Slope Filtering of Airborne LiDAR Data in Urban Areas for Digital Terrain Model (DTM) Generation

Junichi Susaki

doi:10.3390/rs4061804

Abstract

A filtering algorithm is proposed that accurately extracts ground data from airborne light detection and ranging (LiDAR) measurements and generates an estimated digital terrain model (DTM). The proposed algorithm utilizes planar surface features and connectivity with locally lowest points to improve the extraction of ground points (GPs). A slope parameter used in the proposed algorithm is updated after an initial estimation of the DTM, and thus local terrain information can be included. As a result, the proposed algorithm can extract GPs from areas where different degrees of slope variation are interspersed. Specifically, along roads and streets, GPs were extracted from urban areas, from hilly areas such as forests, and from flat area such as riverbanks. Validation using reference data showed that, compared with commercial filtering software, the proposed algorithm extracts GPs with higher accuracy. Therefore, the proposed filtering algorithm effectively generates DTMs, even for dense urban areas, from airborne LiDAR data.

Highlights

Three-dimensional (3D) urban building models are used in various applications, and the data necessary for modeling, such as building height estimates, can be generated by using airborne light detection and ranging (LiDAR)
Airborne LiDAR measures laser light reflected from the surface of objects, and a digital surface model (DSM) is generated by interpolating the discrete LiDAR data
During preprocessing of the 3D models, ground points (GPs) in the LiDAR data are separated from non-GPs

Summary

Introduction

Three-dimensional (3D) urban building models are used in various applications, and the data necessary for modeling, such as building height estimates, can be generated by using airborne light detection and ranging (LiDAR). Airborne LiDAR measures laser light reflected from the surface of objects, and a digital surface model (DSM) is generated by interpolating the discrete LiDAR data. During preprocessing of the 3D models, ground points (GPs) in the LiDAR data are separated from non-GPs. During preprocessing of the 3D models, ground points (GPs) in the LiDAR data are separated from non-GPs This process is called filtering, and a digital terrain model (DTM) can be generated by Remote Sens. 2012, 4 interpolating the extracted GPs. The heights of objects, such as trees and buildings, are estimated by examining the differences between the DSM and the DTM. The accuracy of DTM estimation, affects the accuracy of the building models

Methods

Discussion

Conclusion