Evaluating the change and trend of construction land in Changsha City based GeoSOS-FLUS model and machine learning methods
Abstract This study systematically analyzes the land use changes in Changsha City from 2000 to 2023. Three classification models—Random Forest (RF), Gradient Boosting Decision Tree (GBDT), and Artificial Neural Network (ANN) were employed to evaluate the accuracy of land use classification. The RF m...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-03-01
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| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-93689-9 |
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