Leveraging machine learning for analyzing the nexus between land use and land cover change, land surface temperature and biophysical indices in an eco-sensitive region of Brahmani-Dwarka interfluve
This present study aims to evaluate land use and land cover changes using five machine-learning algorithms in Google Earth Engine. The performance of these machine learning algorithms was evaluated using user accuracy, producer accuracy, overall accuracy, and kappa coefficient. Additionally, it seek...
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2024-12-01
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| Series: | Results in Engineering |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590123024011095 |
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