Classifying Slope Unit by Combining Terrain Feature Lines Based on Digital Elevation Models
In recent years, applications and analyses based on slope units have become increasingly widespread. Compared with grid units, slope units can better represent terrain features and boundaries and allow a more complete view of the morphology of the Earth’s surface. Maps based on slope units also offe...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-01-01
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| Series: | Land |
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| Online Access: | https://www.mdpi.com/2073-445X/12/1/193 |
| _version_ | 1797439844569317376 |
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| author | Hao Wang Guanghui Hu Junfei Ma Hong Wei Sijin Li Guoan Tang Liyang Xiong |
| author_facet | Hao Wang Guanghui Hu Junfei Ma Hong Wei Sijin Li Guoan Tang Liyang Xiong |
| author_sort | Hao Wang |
| collection | DOAJ |
| description | In recent years, applications and analyses based on slope units have become increasingly widespread. Compared with grid units, slope units can better represent terrain features and boundaries and allow a more complete view of the morphology of the Earth’s surface. Maps based on slope units also offer significant improvements for disaster prediction and the analysis of slope land resources. Therefore, we need a reasonable method of slope unit classification. Although some methods have been proposed for slope unit classification, they have been too focused on morphological variations and have not fully considered the importance of geomorphology, and the geomorphological and physical significance of slope partitioning remain unclear. Therefore, we propose a novel slope unit classification method by combining terrain feature lines (CTFL) derived from the meaning of geomorphology ontology that use several terrain feature lines, such as geomorphic water division lines, valley shoulder lines, slope toe lines, and shady/sunny slope boundary lines, to classify slopes. The Jiuyuangou and Lushan study areas were selected to test the CTFL method. Compared with the traditional hydrological method, the CTFL method can effectively overcome topographic abruptness and distortions, improve the uniformity of slope and aspect within individual units, and increase the accuracy of slope unit applications and analyses. This work fully considers the importance of geomorphology and is conducive to future studies of slope unit division. |
| first_indexed | 2024-03-09T11:59:35Z |
| format | Article |
| id | doaj.art-70c9aeb01fce4e9f86199028146abdf1 |
| institution | Directory Open Access Journal |
| issn | 2073-445X |
| language | English |
| last_indexed | 2024-03-09T11:59:35Z |
| publishDate | 2023-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Land |
| spelling | doaj.art-70c9aeb01fce4e9f86199028146abdf12023-11-30T23:05:38ZengMDPI AGLand2073-445X2023-01-0112119310.3390/land12010193Classifying Slope Unit by Combining Terrain Feature Lines Based on Digital Elevation ModelsHao Wang0Guanghui Hu1Junfei Ma2Hong Wei3Sijin Li4Guoan Tang5Liyang Xiong6School of Geography, Nanjing Normal University, Nanjing 210023, ChinaSchool of Geography, Nanjing Normal University, Nanjing 210023, ChinaSchool of Geography, Nanjing Normal University, Nanjing 210023, ChinaSchool of Geography, Nanjing Normal University, Nanjing 210023, ChinaSchool of Geography, Nanjing Normal University, Nanjing 210023, ChinaSchool of Geography, Nanjing Normal University, Nanjing 210023, ChinaSchool of Geography, Nanjing Normal University, Nanjing 210023, ChinaIn recent years, applications and analyses based on slope units have become increasingly widespread. Compared with grid units, slope units can better represent terrain features and boundaries and allow a more complete view of the morphology of the Earth’s surface. Maps based on slope units also offer significant improvements for disaster prediction and the analysis of slope land resources. Therefore, we need a reasonable method of slope unit classification. Although some methods have been proposed for slope unit classification, they have been too focused on morphological variations and have not fully considered the importance of geomorphology, and the geomorphological and physical significance of slope partitioning remain unclear. Therefore, we propose a novel slope unit classification method by combining terrain feature lines (CTFL) derived from the meaning of geomorphology ontology that use several terrain feature lines, such as geomorphic water division lines, valley shoulder lines, slope toe lines, and shady/sunny slope boundary lines, to classify slopes. The Jiuyuangou and Lushan study areas were selected to test the CTFL method. Compared with the traditional hydrological method, the CTFL method can effectively overcome topographic abruptness and distortions, improve the uniformity of slope and aspect within individual units, and increase the accuracy of slope unit applications and analyses. This work fully considers the importance of geomorphology and is conducive to future studies of slope unit division.https://www.mdpi.com/2073-445X/12/1/193terrain featuresgeomorphologyhomogeneitysloping land resourcesDEM |
| spellingShingle | Hao Wang Guanghui Hu Junfei Ma Hong Wei Sijin Li Guoan Tang Liyang Xiong Classifying Slope Unit by Combining Terrain Feature Lines Based on Digital Elevation Models Land terrain features geomorphology homogeneity sloping land resources DEM |
| title | Classifying Slope Unit by Combining Terrain Feature Lines Based on Digital Elevation Models |
| title_full | Classifying Slope Unit by Combining Terrain Feature Lines Based on Digital Elevation Models |
| title_fullStr | Classifying Slope Unit by Combining Terrain Feature Lines Based on Digital Elevation Models |
| title_full_unstemmed | Classifying Slope Unit by Combining Terrain Feature Lines Based on Digital Elevation Models |
| title_short | Classifying Slope Unit by Combining Terrain Feature Lines Based on Digital Elevation Models |
| title_sort | classifying slope unit by combining terrain feature lines based on digital elevation models |
| topic | terrain features geomorphology homogeneity sloping land resources DEM |
| url | https://www.mdpi.com/2073-445X/12/1/193 |
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