Exploring urban land surface temperature with geospatial and regression modelling techniques in Uttarakhand using SVM, OLS and GWR models
Given the climate change challenges, Uttarakhand has become crucial for examining land dynamics and regional climate interactions. This study employed a Support Vector Machine (SVM) for land use and land cover mapping for 2024, achieving 94% accuracy and a Kappa coefficient of 0.90, indicating robus...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2024-01-01
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| Series: | Evolving Earth |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2950117224000086 |
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