DTM generation from aerial photo and Worldview-3 images by using different DSM filtering methods

Catur Aries Rokhmana; Ahmad Ridho Sastra

doi:10.1117/12.2547622

21 November 2019 DTM generation from aerial photo and Worldview-3 images by using different DSM filtering methods

Catur Aries Rokhmana, Ahmad Ridho Sastra

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Proceedings Volume 11311, Sixth Geoinformation Science Symposium; 113110J (2019) https://doi.org/10.1117/12.2547622
Event: Sixth Geoinformation Science Symposium, 2019, Yogyakarta, Indonesia

Abstract

The goal of this study is to analyze the suitability of filtering method towards the generation of Digital Terrain Model (DTM) from Digital Surface Model (DSM). In this case DSM was produced by optical images sensor with stereoscopic viewing. There are 2 kind of optical image that used which are Very High Resolution Satellite (VHRS) image Worldview-3 and Aerial Photograph from Drone mission. Furthermore, there are three different DSM filtering methods are used which are Elevation Threshold with Expand Window (ETEW), 2D Morphological Square (Morph 2D Filter), and Adaptive TIN (ATin). The ALDPAT v.1.0 software has used to implement those algorithm. In addition, the visual interpretation from their correspondent images are used to evaluate the quality of the filtering process. A good filtering result will remove the point that not represent a terrain. The missing of non-ground point due to the filtering process than filling by implementation the same interpolation algorithm. The ETEW and ATin filter algorithm are suitable for residential areas. While ATin filter algorithm give the best results in the vegetation area. An iterative filtering process should be implemented to make a non-terrain point completely remove. Further, an interpolation process should be made for filling the missing non-terrain point.

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Catur Aries Rokhmana and Ahmad Ridho Sastra "DTM generation from aerial photo and Worldview-3 images by using different DSM filtering methods", Proc. SPIE 11311, Sixth Geoinformation Science Symposium, 113110J (21 November 2019); https://doi.org/10.1117/12.2547622

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