• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

利用地球观测数据集对交通和土地变更进行环境影响评估:亚洲和欧洲城市的比较研究

Environmental impact assessment of transportation and land alteration using Earth observational datasets: Comparative study between cities in Asia and Europe.

作者信息

Mhana Khalid Hardan, Norhisham Shuhairy Bin, Katman Herda Yati Binti, Yaseen Zaher Mundher

机构信息

Department of Civil Engineering, College of Engineering, Universiti Tenaga Nasional (UNITEN), Putrajaya Campus, Jalan IKRAM-UNITEN, 43000 Kajang, Selangor, Malaysia.

Civil Engineering Department, College of Engineering, University Of Anbar, Iraq.

出版信息

Heliyon. 2023 Aug 28;9(9):e19413. doi: 10.1016/j.heliyon.2023.e19413. eCollection 2023 Sep.

DOI:10.1016/j.heliyon.2023.e19413
PMID:37809986
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10558544/
Abstract

Developments in the transportation field are emerging because of the growing worldwide demand and upgrading requirements. This study measured the transportation development, shortage distance, and decadal land transformation of Kuala Lumpur and Madrid using various remote sensing and GIS approaches. The kernel density estimation (KDE) tool was applied for road and railway density analysis, and hotspot information increased the knowledge about assessable areas. Landsat datasets were used (1991-2021) for land transformation and related analyses. The built-up land increased by 1327.27 and 404.09 km in Kuala Lumpur and Madrid, respectively. In the last thirty years, the temperature increased 6.45 °C in Kuala Lumpur and 4.15 °C in Madrid owing to urban expansion and road construction. Chamberi, Retiro, Moratalaz, Salama, Wangsa Maju, Titiwangsa, Bukit Bintang, and Seputeh have very high road densities. KDE measurements showed that the road densities in Kuala Lumpur (4498.34) and Madrid (9099.15) were high in the central parts of the city, and the railway densities were 348.872 and 2197.87, respectively. The observed P values were 0.99 and 0.96 for traffic signals and 0.98 and 0.99 for bus stops, respectively. The information provided by this study can support local planners, administrators, scientists, and researchers in understanding the global transportation issues that require implementation strategies for ensuring sustainable livelihoods.

摘要

由于全球需求不断增长和要求不断升级,交通领域正在出现新的发展。本研究使用各种遥感和地理信息系统方法,测量了吉隆坡和马德里的交通发展、短缺距离以及十年土地变化情况。核密度估计(KDE)工具被用于道路和铁路密度分析,热点信息增加了对可评估区域的了解。使用了1991年至2021年的陆地卫星数据集进行土地变化及相关分析。吉隆坡和马德里的建成区土地面积分别增加了1327.27平方公里和404.09平方公里。在过去三十年里,由于城市扩张和道路建设,吉隆坡的气温上升了6.45摄氏度,马德里的气温上升了4.15摄氏度。钱贝里、雷蒂罗、莫拉塔拉兹、萨拉马、旺沙玛朱、蒂蒂旺沙、武吉免登和士布爹的道路密度非常高。KDE测量结果显示,吉隆坡(4498.34)和马德里(9099.15)市中心的道路密度很高,铁路密度分别为348.872和2197.87。交通信号灯的观测P值分别为0.99和0.96,公交车站的观测P值分别为0.98和0.99。本研究提供的信息可以支持当地规划者、管理人员、科学家和研究人员了解需要实施确保可持续生计战略的全球交通问题。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b31/10558544/2ed703d8da69/gr14.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b31/10558544/9bb31cfa6278/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b31/10558544/b93d6d005974/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b31/10558544/df82a65eeebc/gr3a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b31/10558544/5524cbdbcce9/gr3b.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b31/10558544/19128d354d35/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b31/10558544/2368b124d4a4/gr5a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b31/10558544/4754686138cc/gr5b.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b31/10558544/2d595afa70ae/gr6a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b31/10558544/77afc5d34367/gr6b.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b31/10558544/7d90646dd62c/gr6c.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b31/10558544/e5a5293e66d1/gr6d.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b31/10558544/fb67e2d773d9/gr7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b31/10558544/3c265dde569a/gr8a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b31/10558544/3cf286b04f25/gr8b.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b31/10558544/50246a282d57/gr8c.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b31/10558544/3586aaecd938/gr8d.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b31/10558544/8dd0c3235b86/gr8e.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b31/10558544/612b9a01274c/gr9a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b31/10558544/e480f90a057d/gr9b.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b31/10558544/9492cb5047db/gr10.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b31/10558544/66eea0378183/gr11.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b31/10558544/cf117d3213bc/gr12.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b31/10558544/e1ed29f3f66f/gr13.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b31/10558544/2ed703d8da69/gr14.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b31/10558544/9bb31cfa6278/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b31/10558544/b93d6d005974/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b31/10558544/df82a65eeebc/gr3a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b31/10558544/5524cbdbcce9/gr3b.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b31/10558544/19128d354d35/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b31/10558544/2368b124d4a4/gr5a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b31/10558544/4754686138cc/gr5b.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b31/10558544/2d595afa70ae/gr6a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b31/10558544/77afc5d34367/gr6b.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b31/10558544/7d90646dd62c/gr6c.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b31/10558544/e5a5293e66d1/gr6d.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b31/10558544/fb67e2d773d9/gr7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b31/10558544/3c265dde569a/gr8a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b31/10558544/3cf286b04f25/gr8b.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b31/10558544/50246a282d57/gr8c.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b31/10558544/3586aaecd938/gr8d.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b31/10558544/8dd0c3235b86/gr8e.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b31/10558544/612b9a01274c/gr9a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b31/10558544/e480f90a057d/gr9b.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b31/10558544/9492cb5047db/gr10.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b31/10558544/66eea0378183/gr11.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b31/10558544/cf117d3213bc/gr12.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b31/10558544/e1ed29f3f66f/gr13.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b31/10558544/2ed703d8da69/gr14.jpg

相似文献

1
Environmental impact assessment of transportation and land alteration using Earth observational datasets: Comparative study between cities in Asia and Europe.利用地球观测数据集对交通和土地变更进行环境影响评估:亚洲和欧洲城市的比较研究
Heliyon. 2023 Aug 28;9(9):e19413. doi: 10.1016/j.heliyon.2023.e19413. eCollection 2023 Sep.
2
Analysis of urban heat islands with landsat satellite images and GIS in Kuala Lumpur Metropolitan City.利用陆地卫星图像和地理信息系统对吉隆坡都会区城市热岛进行分析。
Heliyon. 2023 Jul 22;9(8):e18424. doi: 10.1016/j.heliyon.2023.e18424. eCollection 2023 Aug.
3
Delineation of urban expansion influences urban heat islands and natural environment using remote sensing and GIS-based in industrial area.利用遥感和 GIS 技术在工业区划定城市扩展对城市热岛和自然环境的影响。
Environ Sci Pollut Res Int. 2022 Oct;29(48):73147-73170. doi: 10.1007/s11356-022-20821-x. Epub 2022 May 27.
4
Measurement and Prediction of Urban Land Traffic Accessibility and Economic Contact Based on GIS: A Case Study of Land Transportation in Shandong Province, China.基于 GIS 的城市土地交通可达性和经济联系的测量与预测——以中国山东省土地交通为例。
Int J Environ Res Public Health. 2022 Nov 11;19(22):14867. doi: 10.3390/ijerph192214867.
5
Satellite data for Singapore, Manila and Kuala Lumpur city growth analysis.用于新加坡、马尼拉和吉隆坡城市增长分析的卫星数据。
Data Brief. 2016 Apr 22;7:1576-83. doi: 10.1016/j.dib.2016.04.028. eCollection 2016 Jun.
6
Impact assessment of urban development patterns on land surface temperature by using remote sensing techniques: a case study of Lahore, Faisalabad and Multan district.利用遥感技术评估城市发展模式对地表温度的影响:以拉合尔、费萨拉巴德和木尔坦地区为例。
Environ Sci Pollut Res Int. 2020 Nov;27(32):39865-39878. doi: 10.1007/s11356-020-10050-5. Epub 2020 Aug 4.
7
Impact of urban land use and land cover change on urban heat island and urban thermal comfort level: a case study of Addis Ababa City, Ethiopia.城市土地利用与土地覆盖变化对城市热岛及城市热舒适度的影响:以埃塞俄比亚亚的斯亚贝巴市为例
Environ Monit Assess. 2022 Sep 7;194(10):736. doi: 10.1007/s10661-022-10414-z.
8
Megacities' environmental assessment for Iraq region using satellite image and geo-spatial tools.利用卫星图像和地理空间工具对伊拉克地区大城市进行环境评估。
Environ Sci Pollut Res Int. 2023 Mar;30(11):30984-31034. doi: 10.1007/s11356-022-24153-8. Epub 2022 Nov 28.
9
Understanding the linkages between spatio-temporal urban land system changes and land surface temperature in Srinagar City, India, using image archives from Google Earth Engine.利用谷歌地球引擎中的图像档案,了解印度斯利那加市时空城市土地系统变化与地表温度之间的联系。
Environ Sci Pollut Res Int. 2023 Oct;30(49):107281-107295. doi: 10.1007/s11356-023-28889-9. Epub 2023 Jul 26.
10
Residential green is associated with reduced annoyance to road traffic and railway noise but increased annoyance to aircraft noise exposure.居住环境绿化与道路交通和铁路噪声带来的烦恼减少相关,但与飞机噪声暴露带来的烦恼增加相关。
Environ Int. 2020 Oct;143:105885. doi: 10.1016/j.envint.2020.105885. Epub 2020 Jun 30.

本文引用的文献

1
Farasan Island of Saudi Arabia confronts the measurable impacts of global warming in 45 years.沙特阿拉伯法尔桑岛在 45 年内面临着全球变暖带来的可衡量的影响。
Sci Rep. 2022 Aug 22;12(1):14322. doi: 10.1038/s41598-022-18225-5.
2
Land use and land cover change and its impacts on dengue dynamics in China: A systematic review.土地利用和土地覆盖变化及其对中国登革热动态的影响:系统评价。
PLoS Negl Trop Dis. 2021 Oct 20;15(10):e0009879. doi: 10.1371/journal.pntd.0009879. eCollection 2021 Oct.
3
Thermal and ecological assessment based on land surface temperature and quantifying multivariate controlling factors in Bogura, Bangladesh.
基于地表温度的孟加拉国博古拉地区热生态评估及多元控制因素量化
Heliyon. 2021 Sep 17;7(9):e08012. doi: 10.1016/j.heliyon.2021.e08012. eCollection 2021 Sep.
4
A synthesis framework using machine learning and spatial bivariate analysis to identify drivers and hotspots of heavy metal pollution of agricultural soils.利用机器学习和空间二元分析的综合框架来识别农业土壤重金属污染的驱动因素和热点。
Environ Pollut. 2021 Oct 15;287:117611. doi: 10.1016/j.envpol.2021.117611. Epub 2021 Jun 17.
5
The application of geostatistical analysis and receptor model for the spatial distribution and sources of potentially toxic elements in soils.地质统计学分析和受体模型在土壤中潜在有毒元素的空间分布和来源中的应用。
Environ Geochem Health. 2021 Jan;43(1):407-421. doi: 10.1007/s10653-020-00729-6. Epub 2020 Sep 28.
6
Temporary reduction in fine particulate matter due to 'anthropogenic emissions switch-off' during COVID-19 lockdown in Indian cities.印度城市在新冠疫情封锁期间因“人为排放关停”导致细颗粒物暂时减少。
Sustain Cities Soc. 2020 Nov;62:102382. doi: 10.1016/j.scs.2020.102382. Epub 2020 Jul 13.
7
An index for discrimination of mangroves from non-mangroves using LANDSAT 8 OLI imagery.一种利用陆地卫星8号OLI影像区分红树林与非红树林的指数。
MethodsX. 2018 Sep 28;5:1129-1139. doi: 10.1016/j.mex.2018.09.011. eCollection 2018.
8
Effects of landscape composition and pattern on land surface temperature: An urban heat island study in the megacities of Southeast Asia.景观组成和格局对地表温度的影响:东南亚特大城市热岛研究。
Sci Total Environ. 2017 Jan 15;577:349-359. doi: 10.1016/j.scitotenv.2016.10.195. Epub 2016 Nov 7.
9
A new integrated GIS-based analysis to detect hotspots: A case study of the city of Sherbrooke.基于 GIS 的新热点检测综合分析:以谢布鲁克市为例。
Accid Anal Prev. 2019 Sep;130:62-74. doi: 10.1016/j.aap.2016.08.015. Epub 2016 Aug 24.
10
Dynamics of land use and land cover change (LULCC) using geospatial techniques: a case study of Islamabad Pakistan.运用地理空间技术研究土地利用与土地覆盖变化动态:以巴基斯坦伊斯兰堡为例
Springerplus. 2016 Jun 21;5(1):812. doi: 10.1186/s40064-016-2414-z. eCollection 2016.