UAV-based doline mapping in Brazilian karst: A cave heritage protection reconnaissance
Dolines are depressions in the soluble ground that indicates the degree of karstification. They may also act as connection points (vulnerability spots) between the surface and underground for the transmission of runoff, sediments, and pollutants. The delineation of these spots (dolines) is a crucial...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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De Gruyter
2023-10-01
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| Series: | Open Geosciences |
| Subjects: | |
| Online Access: | https://doi.org/10.1515/geo-2022-0535 |
| _version_ | 1797653339446444032 |
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| author | Ferreira Cristiano Fernandes Hussain Yawar Uagoda Rogério Silva Tiago Castro Cicerelli Rejane Ennes |
| author_facet | Ferreira Cristiano Fernandes Hussain Yawar Uagoda Rogério Silva Tiago Castro Cicerelli Rejane Ennes |
| author_sort | Ferreira Cristiano Fernandes |
| collection | DOAJ |
| description | Dolines are depressions in the soluble ground that indicates the degree of karstification. They may also act as connection points (vulnerability spots) between the surface and underground for the transmission of runoff, sediments, and pollutants. The delineation of these spots (dolines) is a crucial step in environmental management through land use planning to protect the karst underground, which is rich in flora and fauna. This requirement can benefit from a cost-effective, accessible, and non-invasion high-resolution investigation generating digital elevation models (DEMs) from unmanned aerial vehicle (UAV) imagery and automated object detection techniques. This study examines the capabilities of UAV-based DEM in detecting dolines across 50 km2 in the environmentally protected area of river Vermelho (APANRV – Área de Proteção Ambiental das Nascentes do Rio Vermelho). Initially, an automatic objects (doline and no-doline) detection algorithm was applied to the DEM, followed by a visual inspection to differentiate doline from possible dolines in orthomosaic photos, topographic profiles, and shaded UAV-based relief (digital terrain model; DTM and DSM). For the redundancy checking, a cluster analysis with four tests was conducted. The objects generated from the best clusters and morphological analysis were gathered in the same base for visual inspection. Out of a total of 933 objects identified, 41% were obtained from the DSM base, 25% from the perimeter-to-area ratio, and 34% through convergence between the two-analyses. Subsequently, the resulting doline typologies are discussed in reference to their proximity to hydrogeological features and their impacts on underground vulnerability. The findings aligned with the previous research as dolines were highly concentrated near sites where carbonates come in contact with siliciclastic sediments. |
| first_indexed | 2024-03-11T16:43:13Z |
| format | Article |
| id | doaj.art-4d5ba797226c420ba42ca5bcb8036b4c |
| institution | Directory Open Access Journal |
| issn | 2391-5447 |
| language | English |
| last_indexed | 2024-03-11T16:43:13Z |
| publishDate | 2023-10-01 |
| publisher | De Gruyter |
| record_format | Article |
| series | Open Geosciences |
| spelling | doaj.art-4d5ba797226c420ba42ca5bcb8036b4c2023-10-23T07:50:19ZengDe GruyterOpen Geosciences2391-54472023-10-0115111510.1515/geo-2022-0535UAV-based doline mapping in Brazilian karst: A cave heritage protection reconnaissanceFerreira Cristiano Fernandes0Hussain Yawar1Uagoda Rogério2Silva Tiago Castro3Cicerelli Rejane Ennes4Nacional Center for Research and Conservation of Caves, CECAV – Instituto Chico Mendes de Conservação da Biodiversidade, ICMBio, Brasília, 70635-800, BrazilEarth Sciences Department, Sapienza University of Rome and CERI, Research Centre for Geological Risk, P.le Aldo Moro n. 5, I-00185Rome, ItalyDepartment of Geography, University of Brasilia, Brasilia, 70910-900, BrazilNacional Center for Research and Conservation of Caves, CECAV – Instituto Chico Mendes de Conservação da Biodiversidade, ICMBio, Brasília, 70635-800, BrazilInstitute of Geosciences, University of Brasilia, Brasilia, 70910-900, BrazilDolines are depressions in the soluble ground that indicates the degree of karstification. They may also act as connection points (vulnerability spots) between the surface and underground for the transmission of runoff, sediments, and pollutants. The delineation of these spots (dolines) is a crucial step in environmental management through land use planning to protect the karst underground, which is rich in flora and fauna. This requirement can benefit from a cost-effective, accessible, and non-invasion high-resolution investigation generating digital elevation models (DEMs) from unmanned aerial vehicle (UAV) imagery and automated object detection techniques. This study examines the capabilities of UAV-based DEM in detecting dolines across 50 km2 in the environmentally protected area of river Vermelho (APANRV – Área de Proteção Ambiental das Nascentes do Rio Vermelho). Initially, an automatic objects (doline and no-doline) detection algorithm was applied to the DEM, followed by a visual inspection to differentiate doline from possible dolines in orthomosaic photos, topographic profiles, and shaded UAV-based relief (digital terrain model; DTM and DSM). For the redundancy checking, a cluster analysis with four tests was conducted. The objects generated from the best clusters and morphological analysis were gathered in the same base for visual inspection. Out of a total of 933 objects identified, 41% were obtained from the DSM base, 25% from the perimeter-to-area ratio, and 34% through convergence between the two-analyses. Subsequently, the resulting doline typologies are discussed in reference to their proximity to hydrogeological features and their impacts on underground vulnerability. The findings aligned with the previous research as dolines were highly concentrated near sites where carbonates come in contact with siliciclastic sediments.https://doi.org/10.1515/geo-2022-0535photogrammetrydemdoline typologyvulnerability-spots |
| spellingShingle | Ferreira Cristiano Fernandes Hussain Yawar Uagoda Rogério Silva Tiago Castro Cicerelli Rejane Ennes UAV-based doline mapping in Brazilian karst: A cave heritage protection reconnaissance Open Geosciences photogrammetry dem doline typology vulnerability-spots |
| title | UAV-based doline mapping in Brazilian karst: A cave heritage protection reconnaissance |
| title_full | UAV-based doline mapping in Brazilian karst: A cave heritage protection reconnaissance |
| title_fullStr | UAV-based doline mapping in Brazilian karst: A cave heritage protection reconnaissance |
| title_full_unstemmed | UAV-based doline mapping in Brazilian karst: A cave heritage protection reconnaissance |
| title_short | UAV-based doline mapping in Brazilian karst: A cave heritage protection reconnaissance |
| title_sort | uav based doline mapping in brazilian karst a cave heritage protection reconnaissance |
| topic | photogrammetry dem doline typology vulnerability-spots |
| url | https://doi.org/10.1515/geo-2022-0535 |
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