Land use optimization modelling with ecological priority perspective for large-scale spatial planning

土地利用 计算机科学 蚁群优化算法 比例(比率) 过程(计算) 环境资源管理 土地覆盖 环境科学 生态学 地理 人工智能 地图学 生物 操作系统
作者
Weilin Wang,Limin Jiao,Qiqi Jia,Jiafeng Liu,Wenjing Mao,Zhibang Xu,Wende Li
出处
期刊:Sustainable Cities and Society [Elsevier]
卷期号:65: 102575-102575 被引量:49
标识
DOI:10.1016/j.scs.2020.102575
摘要

Land-use optimization model provides an effective means of finding solutions to mitigate ecological impacts resulting from land use and land cover changes (LUCCs). However, current land-use optimization models usually underestimate the control/ effectiveness of ecological indicators in the model's operation process. How to incorporate ecological indicators into the land-use simulation to optimize multiple land-use patterns is scarce and worth discussing. In our study, we proposed a Future Land use Optimization model for Ecological protection (FLOE) by integrating a cellular automata (CA) model, ant colony optimization (ACO) algorithm, and ecological protection for optimizing land-use patterns from an ecological priority perspective. Firstly, we discuss the coupling pattern in incorporating ecological indicators into models to support the use of models for design and verification in large-scale land-use optimization. Secondly, the proposed FLOE model improves the effectiveness of ecological indicators in the land-use optimization process and better meets the predetermined optimization objectives in a dynamic feedback mechanism. The LUCCs of the Yangtze River Economic Belt (YREB) during 2010–2015 were selected to validate the applicability of the proposed FLOE model. The validation results show that compared to actual LUCCs, the proposed model can significantly reduce ecosystem function loss. Moreover, the proposed model was also applied to the land use optimization from 2010 to 2030 in YREB. The optimization results show a 31.23 % reduction in the total ecosystem function loss than land-use simulation without ecological optimization. The study is expected to provide a reference for land use optimization modelling with ecological conservation in methodology and offers important implications for the formulation and management of large-scale spatial planning.
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
更新
大幅提高文件上传限制,最高150M (2024-4-1)

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
元锦程完成签到,获得积分10
刚刚
HopeStar完成签到,获得积分10
1秒前
嗯呐应助麻薯头头采纳,获得10
2秒前
4秒前
8秒前
123的小王子完成签到,获得积分20
8秒前
ASZXDW发布了新的文献求助10
8秒前
想吃泡芙完成签到 ,获得积分10
10秒前
11秒前
聪慧勒发布了新的文献求助30
12秒前
就是躺应助卷卷采纳,获得10
13秒前
15秒前
时尚的初柔完成签到,获得积分10
16秒前
小白完成签到 ,获得积分10
21秒前
qqesk完成签到,获得积分20
25秒前
28秒前
田様应助科研通管家采纳,获得10
32秒前
iNk应助科研通管家采纳,获得10
32秒前
酷波er应助科研通管家采纳,获得10
32秒前
华仔应助科研通管家采纳,获得10
32秒前
华仔应助科研通管家采纳,获得10
33秒前
FashionBoy应助科研通管家采纳,获得10
33秒前
完美世界应助科研通管家采纳,获得10
33秒前
Leelelele应助科研通管家采纳,获得20
33秒前
香蕉觅云应助科研通管家采纳,获得10
33秒前
研友_X89o6n完成签到,获得积分10
33秒前
34秒前
Duolalala完成签到,获得积分10
34秒前
1111完成签到,获得积分10
35秒前
36秒前
欧阳半仙发布了新的文献求助10
39秒前
未改完成签到,获得积分10
39秒前
高挑的向真完成签到,获得积分10
41秒前
桐月十六完成签到 ,获得积分10
42秒前
42秒前
43秒前
充电宝应助Leone采纳,获得10
44秒前
44秒前
HUCAI完成签到,获得积分10
44秒前
48秒前
高分求助中
Kinetics of the Esterification Between 2-[(4-hydroxybutoxy)carbonyl] Benzoic Acid with 1,4-Butanediol: Tetrabutyl Orthotitanate as Catalyst 1000
The Young builders of New china : the visit of the delegation of the WFDY to the Chinese People's Republic 1000
Rechtsphilosophie 1000
Bayesian Models of Cognition:Reverse Engineering the Mind 888
Handbook of Qualitative Cross-Cultural Research Methods 600
Very-high-order BVD Schemes Using β-variable THINC Method 568
Chen Hansheng: China’s Last Romantic Revolutionary 500
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 基因 遗传学 催化作用 物理化学 免疫学 量子力学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 3137706
求助须知:如何正确求助?哪些是违规求助? 2788609
关于积分的说明 7787778
捐赠科研通 2444975
什么是DOI,文献DOI怎么找? 1300139
科研通“疑难数据库(出版商)”最低求助积分说明 625814
版权声明 601043