ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume V-2-2020
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-2-2020, 351–356, 2020
https://doi.org/10.5194/isprs-annals-V-2-2020-351-2020
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-2-2020, 351–356, 2020
https://doi.org/10.5194/isprs-annals-V-2-2020-351-2020

  03 Aug 2020

03 Aug 2020

STATE OF THE ART IN DIGITAL SURFACE MODELLING FROM MULTI-VIEW HIGH-RESOLUTION SATELLITE IMAGES

Y. Han1, S. Wang1, D. Gong2, Y. Wang3, Y. Wang4, and X. Ma5 Y. Han et al.
  • 1School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China
  • 2State Key Laboratory of Geo-information Engineering, Xi'an, China
  • 3Wuhan Geomatics Institute, Wuhan, China
  • 4School of Geographic and Oceanographic Science, Nanjing University, Nanjing, China
  • 5Xi'an Geovis Spatial Data Technology Co., Ltd, Xi'an, China

Keywords: Multi-view Satellite Images, Digital Surface Model Generation, Pair Selection, Dense Image Matching, DSM Fusion

Abstract. Data from the optical satellite imaging sensors running 24/7, is collecting in embarrassing abundance nowadays. Besides more suitable for large-scale mapping, multi-view high-resolution satellite images (HRSI) are cheaper when comparing to Light Detection And Ranging (LiDAR) data and aerial remotely sensed images, which are more accessible sources for digital surface modelling and updating. Digital Surface Model (DSM) generation is one of the most critical steps for mapping, 3D modelling, and semantic interpretation. Computing DSM from this dataset is relatively new, and several solutions exist in the market, both commercial and open-source solutions, the performances of these solutions have not yet been comprehensively analyzed. Although some works and challenges have focused on the DSM generation pipeline and the geometric accuracy of the generated DSM, the evaluations, however, do not consider the latest solutions as the fast development in this domain. In this work, we discussed the pipeline of the considered both commercial and opensource solutions, assessed the accuracy of the multi-view satellite image-based DSMs generation methods with LiDAR-derived DSM as the ground truth. Three solutions, including Satellite Stereo Pipeline (S2P), PCI Geomatica, and Agisoft Metashape, are evaluated on a WorldView-3 multi-view satellite dataset both quantitatively and qualitatively with the LiDAR ground truth. Our comparison and findings are presented in the experimental section.