Assessment of urban growth patterns on forest and water resources changes using remote sensing and machine learning techniques
文献类型：期刊论文
| 作者 | Phommavong, Ketsana3; Yan, Jianguo1,3; Shah, Shoukat Ali2,3 |
| 刊名 | JOURNAL OF WATER AND CLIMATE CHANGE
 |
| 出版日期 | 2025-10-01 |
| 卷号 | 16期号:11页码:3308–3328 |
| 关键词 | deforestation machine learning remote sensing urbanization water change |
| ISSN号 | 2040-2244 |
| DOI | 10.2166/wcc.2025.048 |
| 产权排序 | 2 |
| 英文摘要 | The landscape of Laos has changed significantly in terms of forest and water resources due to intensive human activities, including agricultural expansion and urbanization. In this study, remote sensing and machine learning models are used to analyze deforestation and surface water reduction to provide a detailed overview of environmental changes in Laos. The results show a complex development: the forest area increased from 90,506 km(2) in 1990 to 103,671 km(2) in 1995, which can be attributed to targeted reforestation measures. By 2020, however, the forest area had fallen to 76,811 km(2), which represents an alarming trend of forest loss. An analysis of the period shows two distinct phases of forest change: rapid deforestation from 1990 to 2005 and a slower decline from 2005 to 2020, probably due to conservation measures. Surface water, which is crucial for the ecological balance, also increases slightly, from 843.22 km(2) in 1990 to 852.94 km(2) in 2020, indicating a slight increase over the last three decades. The study uses random forest and support vector regression to examine the link between forest degradation and river basin changes, highlighting the need for sustainable resource management in Laos to tackle environmental issues. |
| 资助项目 | Outstanding Youth Science Foundation Project in Xinjiang Uygur Autonomous Region of China[2025D01E62] ; Open project of the Key Laboratory in Xinjiang Uygur Autonomous Region of China[2023D04058] ; Chinese Academy of Sciences Foundation of the young scholars of western[2020-XBQNXZ-019] ; National Natural Science Foundation of China[42241116] ; The 2022 Project of the Xinjiang Uygur Autonomous Region of China |
| WOS研究方向 | Water Resources |
| 语种 | 英语 |
| WOS记录号 | WOS:001603571600001 |
| 出版者 | IWA PUBLISHING |
| 资助机构 | Outstanding Youth Science Foundation Project in Xinjiang Uygur Autonomous Region of China ; Open project of the Key Laboratory in Xinjiang Uygur Autonomous Region of China ; Chinese Academy of Sciences Foundation of the young scholars of western ; National Natural Science Foundation of China ; The 2022 Project of the Xinjiang Uygur Autonomous Region of China |
| 源URL | [http://ir.xao.ac.cn/handle/45760611-7/8293]  |
| 专题 | 研究单元未命名 |
| 通讯作者 | Yan, Jianguo |
| 作者单位 | 1.Chinese Acad Sci, Xinjiang Astron Observ, Urumqi 830011, Peoples R China 2.Wuhan Univ, Chinese Antarctic Ctr Surveying & Mapping, Wuhan 430079, Peoples R China 3.Wuhan Univ, State Key Lab Informat Engn Surveying, Mapping & Remote Sensing, Wuhan 430079, Peoples R China |
| 推荐引用方式 GB/T 7714 | Phommavong, Ketsana,Yan, Jianguo,Shah, Shoukat Ali. Assessment of urban growth patterns on forest and water resources changes using remote sensing and machine learning techniques[J]. JOURNAL OF WATER AND CLIMATE CHANGE,2025,16(11):3308–3328. |
| APA | Phommavong, Ketsana,Yan, Jianguo,&Shah, Shoukat Ali.(2025).Assessment of urban growth patterns on forest and water resources changes using remote sensing and machine learning techniques.JOURNAL OF WATER AND CLIMATE CHANGE,16(11),3308–3328. |
| MLA | Phommavong, Ketsana,et al."Assessment of urban growth patterns on forest and water resources changes using remote sensing and machine learning techniques".JOURNAL OF WATER AND CLIMATE CHANGE 16.11(2025):3308–3328. |
入库方式： OAI收割
来源：新疆天文台
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