Comparison of machine learning and parametric methods for the discrimination of urban land cover types
The aim of this study is to compare the performances of different machine learning and parametric techniques for differentiating highly mixed urban land cover classes in Ulaanbaatar, the capital city of Mongolia, using multisource data sets. For data sources, 17 features are chosen, including the or...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2024-01-01
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| Series: | Geocarto International |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/10106049.2024.2380372 |
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