Abstract
Airborne laser scanning (ALS) has proven to be a strong basis for 3D building reconstruction. While ALS data allows for a highly automated processing workflow, a major drawback is often in the point spacing. As a consequence, the precision of roof plane and ridge line parameters is usually significantly better than the precision of gutter lines. To cope with this problem, the paper presents an approach for geometric refinement of building models reconstructed from ALS data using monoscopic aerial images. The core idea of the proposed modeling method is to obtain refined roof edges by intersecting roof planes accurately and reliably extracted from 3D point clouds with viewing planes assigned with building edges detected in a high resolution aerial image. In order to minimize ambiguities that may arise during the integration of modeling cues, the ALS data is used as the master providing initial information about building shape and topology. We evaluate the performance of our algorithm by comparing the results of 3D reconstruction executed using only laser scanning data and reconstruction enhanced by image information. The assessment performed within a framework of the International Society for Photogrammetry and Remote Sensing (ISPRS) benchmark shows an increase in the final quality indicator up to 8.7%.
Highlights
Accurate and timely updated 3D building models are a core element of urban scene reconstruction.Virtual models serve as an important information source to support various domains such as urban planning, disaster management, navigation and tourism
With regard to the data type used in the modeling process, the algorithms can be classified into three groups: (i) based on airborne laser scanning (ALS)
To validate the presented refinement approach, we used data provided by International Society for Photogrammetry and Remote Sensing (ISPRS) WGIII/4 2012–2016 [1]
Summary
Accurate and timely updated 3D building models are a core element of urban scene reconstruction. Virtual models serve as an important information source to support various domains such as urban planning, disaster management, navigation and tourism. A permanently increasing spectrum of applications urgently demands advanced methods for efficient and automated reconstruction algorithms providing up-to-date products. Despite worldwide intensive efforts to improve the modeling process, reconstruction of highly accurate building models still remains a challenging task (e.g., [1,2]). Due to the needs for efficient modeling covering large areas, the base information for building extraction mainly comes from airborne data. With regard to the data type used in the modeling process, the algorithms can be classified into three groups: (i) based on airborne laser scanning (ALS)
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