Exploring spatio-temporal heterogeneity of rural settlement patterns on carbon emission across more than 2800 Chinese counties using multiple supervised machine learning models
文献类型：期刊论文
| 作者 | Huang, Xinxin1; Liu, Yansui1,3; Stouffs, Rudi2 |
| 刊名 | JOURNAL OF ENVIRONMENTAL MANAGEMENT
 |
| 出版日期 | 2025 |
| 卷号 | 373页码:123932 |
| 关键词 | Sustainable development Rural revitalization Rural settlement Landscape index Carbon emission |
| ISSN号 | 0301-4797 |
| DOI | 10.1016/j.jenvman.2024.123932 |
| 产权排序 | 1 |
| 文献子类 | Article |
| 英文摘要 | China, the world's largest carbon emitter, plays a pivotal role in achieving carbon neutrality. This study systematically analyzes the impact of landscape indices on carbon emissions from rural settlements across more than 2800 counties using eight supervised machine learning models. To assess variable influences under diverse conditions, we also employed the SHapley Additive exPlanations (SHAP) and Accumulated Local Effects (ALE) methods. From 2000 to 2020, carbon emissions in China increased significantly, with the highest regional growth in the Northeast, surging by 259.52% to 10.199 million tons per year. After identifying the Gradient Boosted Regression Trees (GBRT) model as most effective, our findings reveal that the Mean Patch Area (MPA) index had a greater influence on emissions compared to Patch Density (PD), Edge Density (ED), and Aggregation Index (AI). Each index demonstrated unique impact characteristics and varied trends across different regions. These findings are crucial for crafting targeted environmental policies and advancing sustainable development goals. |
| URL标识 | 查看原文 |
| WOS关键词 | LAND-COVER CHANGE ; DRIVING FACTORS ; CO2 EMISSIONS ; SINK ; URBANIZATION ; EFFICIENCY ; IMPACT |
| WOS研究方向 | Environmental Sciences & Ecology |
| 语种 | 英语 |
| WOS记录号 | WOS:001400421300001 |
| 出版者 | ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/211360]  |
| 专题 | 区域可持续发展分析与模拟院重点实验室_外文论文 |
| 通讯作者 | Liu, Yansui |
| 作者单位 | 1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China; 2.Natl Univ Singapore, Dept Architecture, Singapore 117566, Singapore 3.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100190, Peoples R China; |
| 推荐引用方式 GB/T 7714 | Huang, Xinxin,Liu, Yansui,Stouffs, Rudi. Exploring spatio-temporal heterogeneity of rural settlement patterns on carbon emission across more than 2800 Chinese counties using multiple supervised machine learning models[J]. JOURNAL OF ENVIRONMENTAL MANAGEMENT,2025,373:123932. |
| APA | Huang, Xinxin,Liu, Yansui,&Stouffs, Rudi.(2025).Exploring spatio-temporal heterogeneity of rural settlement patterns on carbon emission across more than 2800 Chinese counties using multiple supervised machine learning models.JOURNAL OF ENVIRONMENTAL MANAGEMENT,373,123932. |
| MLA | Huang, Xinxin,et al."Exploring spatio-temporal heterogeneity of rural settlement patterns on carbon emission across more than 2800 Chinese counties using multiple supervised machine learning models".JOURNAL OF ENVIRONMENTAL MANAGEMENT 373(2025):123932. |
入库方式： OAI收割
来源：地理科学与资源研究所
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