Building classification using airborne lidar data with satellite SAR data

Tatsuya Yamamoto, Masafumi Nakagawa

研究成果: Conference contribution

抄録

In general, airborne photogrammetry and LiDAR measurements are applied to geometrical data acquisition for automated map generation and revision. However, attribute data acquisition and classification depend on manual editing works including ground surveys. On the other hand, SAR data have a possibility to automate the attribute data acquisition and classification. Thus, we focus on an integration of LiDAR and SAR data to achieve a frequent map update with attribute data acquisition. In this study, we use airborne LiDAR and satellite SAR data to classify buildings. Firstly, we generate a digital surface model (DSM) from point cloud acquired with airborne LiDAR. Secondary, the DSM is registered with a normalized radar cross section (NRCS) image calculated from SAR data. Thirdly, buildings are extracted from the DSM. Finally, the buildings are classified into several clusters in the DSM. We clarified that a combination of airborne LiDAR and satellite SAR data can extract and classify buildings in urban area.

本文言語English
ホスト出版物のタイトル35th Asian Conference on Remote Sensing 2014, ACRS 2014: Sensing for Reintegration of Societies
出版社Asian Association on Remote Sensing
出版ステータスPublished - 2014
イベント35th Asian Conference on Remote Sensing 2014: Sensing for Reintegration of Societies, ACRS 2014 - Nay Pyi Taw, Myanmar
継続期間: 2014 10 272014 10 31

Other

Other35th Asian Conference on Remote Sensing 2014: Sensing for Reintegration of Societies, ACRS 2014
国/地域Myanmar
CityNay Pyi Taw
Period14/10/2714/10/31

ASJC Scopus subject areas

  • コンピュータ ネットワークおよび通信

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