A New GIS-Based Model for Karst Dolines Mapping Using LiDAR; Application of a Multidepth Threshold Approach in the Yucatan Karst, Mexico
Dolines are important features strongly influencing the outcomes of groundwater vulnerability maps, subsidence risk and land use studies. Their relationship with subsurface features like epikarst, stresses the importance of doline mapping for environmental and hydrological management strategies. Cur...
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-05-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/11/10/1147 |
| _version_ | 1798025733540413440 |
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| author | Miguel Moreno-Gómez Rudolf Liedl Catalin Stefan |
| author_facet | Miguel Moreno-Gómez Rudolf Liedl Catalin Stefan |
| author_sort | Miguel Moreno-Gómez |
| collection | DOAJ |
| description | Dolines are important features strongly influencing the outcomes of groundwater vulnerability maps, subsidence risk and land use studies. Their relationship with subsurface features like epikarst, stresses the importance of doline mapping for environmental and hydrological management strategies. Current methodologies to map dolines from elevation models apply morphometric attributes on depressions, including a depth threshold, to filter depressed areas and to define dolines. However, the use of a single threshold tends to overlook dolines located in already depressed areas. In this work a new geographic information systems (GIS)-based methodology is proposed to identify karst depressions within digital elevation models, applying a multidepth threshold approach. The method statistically classifies depression intervals to identify dolines at variable depths. The method was tested in the Yucatan karst, displaying a final accuracy of 63% after testing different parameters. The results are affected by false positives due to the impossibility of verifying by imagery 190 possible dolines in areas of dense vegetation. Nevertheless, out of 655 estimated dolines, 464 match those located by imagery giving sensitivity and precision values of 85% and 71%, respectively. Comparing this methodology against single threshold outcomes, improvement is evident in doline mapping. Notwithstanding, its application and performance with lower and higher resolution elevation models must be investigated. |
| first_indexed | 2024-04-11T18:24:39Z |
| format | Article |
| id | doaj.art-e522a289c6a04a7791bd0049aa5e4b95 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-04-11T18:24:39Z |
| publishDate | 2019-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-e522a289c6a04a7791bd0049aa5e4b952022-12-22T04:09:41ZengMDPI AGRemote Sensing2072-42922019-05-011110114710.3390/rs11101147rs11101147A New GIS-Based Model for Karst Dolines Mapping Using LiDAR; Application of a Multidepth Threshold Approach in the Yucatan Karst, MexicoMiguel Moreno-Gómez0Rudolf Liedl1Catalin Stefan2Research Group INOWAS, Department of Hydrosciences, Technische Universität Dresden, 01069 Dresden, GermanyInstitute for Groundwater Management, Department of Hydrosciences, Technische Universität Dresden, 01069 Dresden, GermanyResearch Group INOWAS, Department of Hydrosciences, Technische Universität Dresden, 01069 Dresden, GermanyDolines are important features strongly influencing the outcomes of groundwater vulnerability maps, subsidence risk and land use studies. Their relationship with subsurface features like epikarst, stresses the importance of doline mapping for environmental and hydrological management strategies. Current methodologies to map dolines from elevation models apply morphometric attributes on depressions, including a depth threshold, to filter depressed areas and to define dolines. However, the use of a single threshold tends to overlook dolines located in already depressed areas. In this work a new geographic information systems (GIS)-based methodology is proposed to identify karst depressions within digital elevation models, applying a multidepth threshold approach. The method statistically classifies depression intervals to identify dolines at variable depths. The method was tested in the Yucatan karst, displaying a final accuracy of 63% after testing different parameters. The results are affected by false positives due to the impossibility of verifying by imagery 190 possible dolines in areas of dense vegetation. Nevertheless, out of 655 estimated dolines, 464 match those located by imagery giving sensitivity and precision values of 85% and 71%, respectively. Comparing this methodology against single threshold outcomes, improvement is evident in doline mapping. Notwithstanding, its application and performance with lower and higher resolution elevation models must be investigated.https://www.mdpi.com/2072-4292/11/10/1147karstdolines mappingLiDARYucatan |
| spellingShingle | Miguel Moreno-Gómez Rudolf Liedl Catalin Stefan A New GIS-Based Model for Karst Dolines Mapping Using LiDAR; Application of a Multidepth Threshold Approach in the Yucatan Karst, Mexico Remote Sensing karst dolines mapping LiDAR Yucatan |
| title | A New GIS-Based Model for Karst Dolines Mapping Using LiDAR; Application of a Multidepth Threshold Approach in the Yucatan Karst, Mexico |
| title_full | A New GIS-Based Model for Karst Dolines Mapping Using LiDAR; Application of a Multidepth Threshold Approach in the Yucatan Karst, Mexico |
| title_fullStr | A New GIS-Based Model for Karst Dolines Mapping Using LiDAR; Application of a Multidepth Threshold Approach in the Yucatan Karst, Mexico |
| title_full_unstemmed | A New GIS-Based Model for Karst Dolines Mapping Using LiDAR; Application of a Multidepth Threshold Approach in the Yucatan Karst, Mexico |
| title_short | A New GIS-Based Model for Karst Dolines Mapping Using LiDAR; Application of a Multidepth Threshold Approach in the Yucatan Karst, Mexico |
| title_sort | new gis based model for karst dolines mapping using lidar application of a multidepth threshold approach in the yucatan karst mexico |
| topic | karst dolines mapping LiDAR Yucatan |
| url | https://www.mdpi.com/2072-4292/11/10/1147 |
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