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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| 主要な著者: | , , |
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| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
Nature Portfolio
2025-03-01
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| シリーズ: | Scientific Reports |
| 主題: | |
| オンライン･アクセス: | https://doi.org/10.1038/s41598-025-93689-9 |
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