A Review of Building Extraction From Remote Sensing Imagery: Geometrical Structures and Semantic Attributes

Qingyu Li, Lichao Mou, Yao Sun, Yuansheng Hua, Yilei Shi, Xiao Xiang Zhu

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

In the remote sensing community, extracting buildings from remote sensing imagery has triggered great interest. While many studies have been conducted, a comprehensive review of these approaches that are applied to optical and synthetic aperture radar (SAR) imagery is still lacking. Therefore, we provide an in-depth review of both early efforts and recent advances, which are aimed at extracting geometrical structures or semantic attributes of buildings, including building footprint generation, building facade segmentation, roof segment and superstructure segmentation, building height retrieval, building-type classification, building change detection, and annotation data correction. Furthermore, a list of corresponding benchmark datasets is given. Finally, challenges and outlooks of existing approaches as well as promising applications are discussed to enhance comprehension within this realm of research.

Original languageEnglish
Article number4702315
Pages (from-to)1-15
Number of pages15
JournalIEEE Transactions on Geoscience and Remote Sensing
Volume62
DOIs
StatePublished - 2024

Keywords

  • Building extraction
  • deep learning
  • optical imagery
  • review
  • synthetic aperture radar (SAR)

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