Trade-off or synergy? Dynamic analysis and policy insights on land use functions in China

可持续发展 业务 土地利用 环境资源管理 中国 溢出效应 生态系统服务 环境经济学 地理 经济 生态学 生态系统 考古 生物 微观经济学
作者
Chao Wei,Zhou Wu,Jian Xing,Gui Jin
出处
期刊:Environmental Impact Assessment Review [Elsevier BV]
卷期号:105: 107399-107399 被引量:5
标识
DOI:10.1016/j.eiar.2023.107399
摘要

Limited land resources and diverse utilization have resulted in complex trade-offs and synergies (TS) among land use functions (LUFs). Analyzing these TS and their spatio-temporal variations is crucial for developing effective land use policies to regulate and manage multiple LUFs, promoting efficient land resource utilization and fostering sustainable development in society, economy, and ecology. This study uses interdisciplinary research methods, including the projection pursuit model, Spearman's rank correlation analysis, and exploratory spatial data analysis, to investigate the characteristics of LUFs TS in 31 provincial administrative divisions in China from 2009 to 2020. Key findings include: (1) LUFs exhibited significant spatial heterogeneity and temporal variations. Most LUFs experienced distinct upgrading processes, except for SSF (Social Security Function), which requires specific attention.(2) LUFs TS were found to be common and consistent, with varying characteristics observed in different years. It is crucial to consider these characteristics during the process of functional regulation to enhance effectiveness. (3) We confirmed that LUFs, as a public service, show substantial spatial spillover effects, resulting in cross-regional LUFs TS. Regulatory strategies should harness the radiating and propelling effects of advantageous functions while maintaining equilibrium and coordination in regional development, ultimately achieving optimal overall benefits. Finally, we discuss the study findings in comparison with existing research and provide policy insights to promote the harmonized and sustainable development of LUFs. These findings aim to serve as a scientific foundation for land use planning and management in China and offer valuable insights for other regions.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
大个应助哈哈哈采纳,获得30
1秒前
吴梦瑜完成签到,获得积分10
1秒前
huy完成签到 ,获得积分10
1秒前
Kia发布了新的文献求助10
1秒前
天麻zyq发布了新的文献求助30
2秒前
2秒前
凉小远发布了新的文献求助30
2秒前
传统的斓完成签到,获得积分10
2秒前
suci发布了新的文献求助10
3秒前
栗爷完成签到,获得积分0
3秒前
孔乙己完成签到,获得积分10
3秒前
a龙完成签到,获得积分10
3秒前
俊俊坨完成签到,获得积分20
4秒前
科研通AI5应助qwerty采纳,获得10
4秒前
早点睡吧完成签到,获得积分10
5秒前
豆丁小猫完成签到,获得积分10
5秒前
xin完成签到 ,获得积分10
5秒前
科研通AI5应助YORLAN采纳,获得10
6秒前
6秒前
6秒前
希望天下0贩的0应助ding采纳,获得10
6秒前
传奇3应助King采纳,获得10
7秒前
LCCCC完成签到,获得积分10
7秒前
孙玮应助Eva采纳,获得10
8秒前
顾矜应助xing采纳,获得10
8秒前
瑶瑶酱完成签到,获得积分10
8秒前
9秒前
甜蜜唯雪完成签到,获得积分10
9秒前
饭饭完成签到 ,获得积分10
9秒前
高兴冬易发布了新的文献求助10
9秒前
不包含特殊字符完成签到,获得积分10
9秒前
天麻zyq完成签到,获得积分10
9秒前
Akim应助fengling采纳,获得30
9秒前
Naixichaohaohe完成签到,获得积分10
10秒前
怡然立轩关注了科研通微信公众号
10秒前
10秒前
111完成签到,获得积分10
10秒前
rania完成签到,获得积分20
10秒前
10秒前
高分求助中
Applied Survey Data Analysis (第三版, 2025) 800
Assessing and Diagnosing Young Children with Neurodevelopmental Disorders (2nd Edition) 700
Images that translate 500
引进保护装置的分析评价八七年国外进口线路等保护运行情况介绍 500
Algorithmic Mathematics in Machine Learning 500
Handbook of Innovations in Political Psychology 400
Mapping the Stars: Celebrity, Metonymy, and the Networked Politics of Identity 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 物理 生物化学 纳米技术 计算机科学 化学工程 内科学 复合材料 物理化学 电极 遗传学 量子力学 基因 冶金 催化作用
热门帖子
关注 科研通微信公众号,转发送积分 3841240
求助须知:如何正确求助?哪些是违规求助? 3383270
关于积分的说明 10528888
捐赠科研通 3103224
什么是DOI,文献DOI怎么找? 1709200
邀请新用户注册赠送积分活动 822985
科研通“疑难数据库(出版商)”最低求助积分说明 773764