Automatic Building Extraction with Multi-sensor Data Using Rule-based Classification

Uzar M.

EUROPEAN JOURNAL OF REMOTE SENSING, vol.47, pp.1-18, 2014 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 47
  • Publication Date: 2014
  • Doi Number: 10.5721/eujrs20144701
  • Journal Name: EUROPEAN JOURNAL OF REMOTE SENSING
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.1-18
  • Keywords: LiDAR, intensity, building extraction, segmentation, rule-based classification, fuzzy logic, LIDAR DATA, FUSION, IMAGERY
  • Yıldız Technical University Affiliated: No

Abstract

This paper presents a new approach for automatic building extraction using a rule-based classification method with a multi-sensor system that includes light detection and ranging (LiDAR), a digital camera, and a GPS/IMU positioned on the same platform. The LiDAR data (elevation and intensity) and ortho-image are used to develop a rule set defined by parameter analyses during the segmentation and fuzzy classification processes to improve the building extraction results. The proposed approach was tested using the data derived from a multi-sensor system in Sivas, Turkey. Moreover, analyses of completeness (81.71%) and correctness (87.64%) were performed by automatic comparison of the extracted buildings and reference data.