Estimation of Building Heights in Peru from High-Resolution Stereo Optical Satellite Imagery

Estimating building heights is essential for urban planning, building resilience, and disaster risk assessment. This study introduces a method for deriving building heights using stereo pairs of high-resolution optical satellite images. A 3D point cloud was generated through stereo matching of two optical satellite images, and a high-resolution digital surface model was constructed to estimate building heights. In the absence of detailed building outlines, building height was calculated by subtracting the elevation outside the lot outline from that within the lot outline. Estimated building heights were then converted to floor numbers for evaluation. Validation involved comparing estimated floor numbers with manually counted floor numbers from field surveys and a 3D model generated from UAV imagery. Results indicated that 42% of buildings had accurately estimated floor numbers, and 82% were within a one-floor error margin. This approach offers a rapid, cost-effective solution for height estimation, especially in areas lacking detailed cadastral or LiDAR data.

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Publication Details

Journal
Journal of Disaster Research
Published
2025-12-01
DOI
https://doi.org/10.20965/jdr.2025.p1023
Primary Topic
Remote Sensing and LiDAR Applications
Type
article
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article

Estimation of Building Heights in Peru from High-Resolution Stereo Optical Satellite Imagery

Miguel Estrada, Wen Liu, Fernando García, M. Matsuoka et al.
Journal of Disaster Research
Remote Sensing and LiDAR Applications
article

Estimation of Building Heights in Peru from High-Resolution Stereo Optical Satellite Imagery

Miguel Estrada, Wen Liu, Fernando García, M. Matsuoka, Bruno Adriano, Jorge Morales, Hiroyuki Miura, Miguel Diaz, Mamoru Kamegawa
article en

Abstract

Estimating building heights is essential for urban planning, building resilience, and disaster risk assessment. This study introduces a method for deriving building heights using stereo pairs of high-resolution optical satellite images. A 3D point cloud was generated through stereo matching of two optical satellite images, and a high-resolution digital surface model was constructed to estimate building heights. In the absence of detailed building outlines, building height was calculated by subtracting the elevation outside the lot outline from that within the lot outline. Estimated building heights were then converted to floor numbers for evaluation. Validation involved comparing estimated floor numbers with manually counted floor numbers from field surveys and a 3D model generated from UAV imagery. Results indicated that 42% of buildings had accurately estimated floor numbers, and 82% were within a one-floor error margin. This approach offers a rapid, cost-effective solution for height estimation, especially in areas lacking detailed cadastral or LiDAR data.

Journal of Disaster ResearchVol. 20(6)
Hiroshima University (JP), Chiba University (JP), Tohoku University (JP), National University of Engineering (PE)
Openalex Percentile: Top 64%
Remote Sensing and LiDAR Applications
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Estimation of Building Heights in Peru from High-Resolution Stereo Optical Satellite Imagery — Miguel Estrada, Wen Liu, et al. · Journal of Disaster Research (2025) | TGRS Research Map | TGRS