Generation of a Digital Terrain Model (DTM) Fusioning WV-2 Images and RTK-derived Topobathymetric Data

Main Article Content

Elton Vicente Escobar-Silva
https://orcid.org/0000-0002-9437-9351
Cláudia Maria de Almeida
https://orcid.org/0000-0002-6523-3169
Rômulo Marques-Carvalho
https://orcid.org/0000-0002-9232-9043
João Vitor Roque Guerrero
https://orcid.org/0000-0002-5393-3803
Cleber Gonzales de Oliveira
https://orcid.org/0000-0003-4733-3462

Abstract

Digital terrain models (DTMs) are digital elevation models (DEMs) that represent the bare ground surface. They are created by multiple sources, including satellite remote sensing, aerial photography, and ground-based surveys, and are often combined with other data sources to create highly detailed models. As the demand for accurate and detailed information about the Earth's surface continues to grow, DTMs have become an increasingly important tool for researchers in different fields. This study aims to create a DTM with a spatial resolution of 0.50 m for São Caetano do Sul, São Paulo, Brazil, integrated with a topobathymetric map of three water courses running along the borders of the study area. For the conventional DTM generation, a WV-2 stereo pair was used. A total of 55 ground control points (GCPs) were collected using the GNSS-RTK method, being 60% used for model building and 40% employed for validation. The topobathymetric survey was accomplished using a GNSS-RTK device placed along the analyzed open streams. For validation purposes, we used bias and MAE metrics. Overall, the methodology presented in this article provides a useful approach for generating high-resolution DTMs that can be used in a range of applications, especially in urban hydrodynamic studies.

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How to Cite
ESCOBAR-SILVA, E. V.; ALMEIDA, C. M. de; MARQUES-CARVALHO, R.; GUERRERO, J. V. R.; OLIVEIRA, C. G. de. Generation of a Digital Terrain Model (DTM) Fusioning WV-2 Images and RTK-derived Topobathymetric Data. Revista Brasileira de Cartografia, [S. l.], v. 76, 2024. DOI: 10.14393/rbcv76n0a-70372. Disponível em: https://seer.ufu.br/index.php/revistabrasileiracartografia/article/view/70372. Acesso em: 22 jul. 2024.
Section
Remote Sensing

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