已入深夜,您辛苦了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!祝你早点完成任务,早点休息,好梦!

Interannual changes of urban wetlands in China’s major cities from 1985 to 2022

湿地 中国 环境科学 地理 水文学(农业) 自然地理学 土木工程 工程类 岩土工程 考古 生态学 生物
作者
Ming Wang,Dehua Mao,Yeqiao Wang,Huiying Li,Jianing Zhen,Hengxing Xiang,Yongxing Ren,Mingming Jia,Kaishan Song,Zongming Wang
出处
期刊:Isprs Journal of Photogrammetry and Remote Sensing 卷期号:209: 383-397 被引量:26
标识
DOI:10.1016/j.isprsjprs.2024.02.011
摘要

With global climate change and accelerating urbanization, accurate and timely extent information on urban wetlands is extremely important for sustainable urban development and conservation of ecosystem services, supporting the implementation and evaluation of the United Nations Sustainable Development Goals (SDGs). China has experienced the most dramatic urbanization process in recent decades, but accurate and comprehensive information for urban wetland changes in China's major cities are still unavailable. In this study, using 137,779 Landsat images available on the Google Earth Engine platform, we developed a novel approach (MWC-CCDC) integrating historical maximum wetness composition (MWC) and continuous change detection and classification (CCDC), and generated the first annual 30-m resolution urban wetland maps for 71 major cities with populations over 0.5 million across China from 1985 to 2022. The resultant annual urban wetland distribution dataset in China, named China_Urban_Wetland (CUW), achieved over 82.81 % overall classification accuracy. According to the CUW, cities in the Yangtze River basin, Pearl River Delta, and Hangzhou Bay cover the majority of urban wetland area in China's 71 major cities. Wuhan had the largest urban wetland area (168.00 km2), followed by Nanjing (103.19 km2). Jiujiang has the highest wetland coverage rate at 27.23 %, followed by Wuhan (20.68 %) and Xiangyang (18.89 %). Between 1985 and 2022, 52 of 71 cities lost wetland area, with Tianjin having the largest percentage loss (79.40 %), followed by Urumqi (74.86 %) and Guiyang (67.55 %). In contrast, Hohhot experienced the largest increase (90.63 %), followed by Beihai (89.21 %) and Xi'an (71.34 %). In about one-third the cities, urban wetland landscape patterns are becoming more fragmented and less connected. Such consistent annual assessments of urban wetlands is expected to benefit the implementation and evaluation of urban-related targets in the SDGs.
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
省级中药饮片完成签到 ,获得积分10
刚刚
朱云发布了新的文献求助10
1秒前
xuz发布了新的文献求助10
2秒前
xuz发布了新的文献求助10
3秒前
Ccccn完成签到,获得积分10
3秒前
3秒前
xuz发布了新的文献求助10
5秒前
xuz发布了新的文献求助10
5秒前
xuz发布了新的文献求助10
6秒前
隐形曼青应助聪明夏波采纳,获得10
7秒前
7秒前
7秒前
xuz发布了新的文献求助10
7秒前
福斯卡完成签到 ,获得积分10
8秒前
9秒前
Bien完成签到,获得积分10
9秒前
Peiyu发布了新的文献求助10
10秒前
我是老大应助lld采纳,获得10
11秒前
12秒前
xuz发布了新的文献求助10
12秒前
xuz发布了新的文献求助10
12秒前
12秒前
13秒前
未夕晴完成签到,获得积分10
16秒前
遇上就这样吧完成签到,获得积分0
16秒前
yang发布了新的文献求助10
16秒前
可可钳发布了新的文献求助10
17秒前
17秒前
wanwuzhumu发布了新的文献求助10
17秒前
556完成签到 ,获得积分10
18秒前
shaangu623完成签到,获得积分10
20秒前
堡主发布了新的文献求助10
20秒前
mirrovo完成签到 ,获得积分10
22秒前
Kinkrit完成签到 ,获得积分10
23秒前
23秒前
寻道图强举报周政求助涉嫌违规
23秒前
拉长的迎曼完成签到 ,获得积分10
30秒前
李爱国应助wanwuzhumu采纳,获得10
31秒前
NexusExplorer应助堡主采纳,获得10
31秒前
Peiyu完成签到,获得积分10
32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
Binary Alloy Phase Diagrams, 2nd Edition 8000
Building Quantum Computers 800
Translanguaging in Action in English-Medium Classrooms: A Resource Book for Teachers 700
Natural Product Extraction: Principles and Applications 500
Exosomes Pipeline Insight, 2025 500
Red Book: 2024–2027 Report of the Committee on Infectious Diseases 500
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5663955
求助须知:如何正确求助?哪些是违规求助? 4855706
关于积分的说明 15106735
捐赠科研通 4822347
什么是DOI,文献DOI怎么找? 2581405
邀请新用户注册赠送积分活动 1535549
关于科研通互助平台的介绍 1493834