The forecast and low‐carbon performance of land use in rapid urbanization area under the low‐carbon oriented spatial planning: Evidence from Hangzhou, China

土地利用 城市化 土地利用、土地利用的变化和林业 空间规划 碳纤维 地理 环境科学 温室气体 土地利用规划 自然资源经济学 环境保护 环境规划 经济 经济增长 工程类 计算机科学 生态学 土木工程 算法 复合数 生物
作者
Weicheng Gu,Weifeng Qi,Mingyu Zhang
出处
期刊:Transactions in Gis [Wiley]
卷期号:28 (6): 1617-1638
标识
DOI:10.1111/tgis.13199
摘要

Abstract The introduction of the carbon peak and carbon‐neutral targets by many countries' central governments has put low‐carbon‐oriented spatial planning at the forefront of discussions. However, few studies have focused on the balance of carbon emission reduction and economic goals in spatial planning, and the governance influence on land use change simulation. This study addresses this gap by conducting an empirical analysis in the rapidly urbanizing area of Hangzhou, China, taking into consideration low‐carbon constraints and economic development demands. Using the stochastic impacts by regression on population, affluence, and technology (STRIPAT) model and linear programming–Markov, we simulate the governance decision‐making process to calculate the optimal land‐use structures under both low‐carbon and baseline scenario, then simulated land use patterns by using artificial‐neural‐network‐based cellular automata (ANN‐CA). The results showed 12.35% and 2.5% growth in urban and forest land, and 9.69% and 6.4% decline in farm and rural land under the low‐carbon scenario. 92.31% of urban land change occur in the downtown districts and suburbs; while 59.77% of farm land change and 95.53% of forest land change occur in the exurban districts. The low‐carbon performance of land use was reflected in carbon storage release, carbon emission capability change, and low‐carbon capability. The most common conversion of land use categories under the low‐carbon scenario was between farm and forest land, and between rural and urban land, which resulted in less carbon storage release and carbon emissions compared with the baseline scenario. Furthermore, under the low‐carbon scenario, the compactness of construction land increased by 2 × 10 −5 , while its fragmentation decreased by 0.0027. This study sheds light on the impact of low‐carbon‐oriented land use planning on urban land expansion, providing empirical evidence for city governments in rapid urbanization areas to improve land use efficiency.
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
彩色甜瓜完成签到 ,获得积分10
1秒前
zmy完成签到,获得积分10
2秒前
薛伟锋完成签到,获得积分10
2秒前
icreat发布了新的文献求助10
3秒前
呼呼发布了新的文献求助10
3秒前
3秒前
4秒前
4秒前
4秒前
慕青应助小费采纳,获得10
4秒前
5秒前
Hello应助yy采纳,获得10
5秒前
大个应助yy采纳,获得10
5秒前
5秒前
华仔应助yy采纳,获得10
5秒前
科目三应助yy采纳,获得10
5秒前
6秒前
害羞大雁完成签到,获得积分10
6秒前
8秒前
材料学渣发布了新的文献求助10
9秒前
hamster666发布了新的文献求助10
9秒前
愉快书琴发布了新的文献求助10
10秒前
夜轩岚发布了新的文献求助30
10秒前
10秒前
DXR完成签到,获得积分10
11秒前
刘承昭发布了新的文献求助10
12秒前
小Q完成签到,获得积分10
14秒前
一只叶文洁喵完成签到,获得积分10
14秒前
xzy发布了新的文献求助10
15秒前
Ava应助啊哈采纳,获得10
15秒前
小Q发布了新的文献求助10
20秒前
Orange应助淇淇采纳,获得10
21秒前
22秒前
酷波er应助许清禾采纳,获得10
22秒前
Darjeeling完成签到,获得积分10
23秒前
脑洞疼应助刘承昭采纳,获得10
24秒前
24秒前
yinjiajun完成签到 ,获得积分10
24秒前
abab完成签到 ,获得积分10
26秒前
李健应助沉静从阳采纳,获得10
27秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Reducing Compassion Fatigue, Secondary Traumatic Stress and Burnout 600
China Pluperfect I: Epistemology of Past and Outside in Chinese Art 520
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Mammalian Synthetic Biology 500
Auslegungsgeschichte 500
Cosmos as Art Object: Studies in Plato's Timaeus and Other Dialogues 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7639066
求助须知:如何正确求助?哪些是违规求助? 9212206
关于积分的说明 19761593
捐赠科研通 7205836
什么是DOI,文献DOI怎么找? 3275955
关于科研通互助平台的介绍 2437529
邀请新用户注册赠送积分活动 2273219