Show simple item record

2021-07-02Zeitschriftenartikel DOI: 10.18452/23081
Monitoring and Modeling the Patterns and Trends of Urban Growth Using Urban Sprawl Matrix and CA-Markov Model
dc.contributor.authorFahad Baqa, Muhammad
dc.contributor.authorChen, Fang
dc.contributor.authorLu, Linlin
dc.contributor.authorQureshi, Salman
dc.contributor.authorTariq, Aqil
dc.contributor.authorWang, Siyuan
dc.contributor.authorJing, Linhai
dc.contributor.authorHamza, Salma
dc.contributor.authorLi, Qingting
dc.date.accessioned2021-07-15T11:42:38Z
dc.date.available2021-07-15T11:42:38Z
dc.date.issued2021-07-02none
dc.identifier.other10.3390/land10070700
dc.identifier.urihttp://edoc.hu-berlin.de/18452/23744
dc.description.abstractUnderstanding the spatial growth of cities is crucial for proactive planning and sustainable urbanization. The largest and most densely inhabited megapolis of Pakistan, Karachi, has experienced massive spatial growth not only in the core areas of the city, but also in the city’s suburbs and outskirts over the past decades. In this study, the land use/land cover (LULC) in Karachi was classified using Landsat data and the random forest algorithm from the Google Earth Engine cloud platform for the years 1990, 2000, 2010, and 2020. Land use/land cover classification maps as well as an urban sprawl matrix technique were used to analyze the geographical patterns and trends of urban sprawl. Six urban classes, namely, the primary urban core, secondary urban core, sub-urban fringe, scatter settlement, urban open space, and non-urban area, were determined for the exploration of urban landscape changes. Future scenarios of LULC for 2030 were predicted using a CA–Markov model. The study found that the built-up area had expanded in a considerably unpredictable manner, primarily at the expense of agricultural land. The increase in mangroves and grassland and shrub land proved the effectiveness of afforestation programs in improving vegetation coverage in the study area. The investigation of urban landscape alteration revealed that the primary urban core expanded from the core districts, namely, the Central, South, and East districts, and a new urban secondary core emerged in Malir in 2020. The CA–Markov model showed that the total urban built-up area could potentially increase from 584.78 km2 in 2020 to 652.59 km2 in 2030. The integrated method combining remote sensing, GIS, and an urban sprawl matrix has proven invaluable for the investigation of urban sprawl in a rapidly growing city.eng
dc.language.isoengnone
dc.publisherHumboldt-Universität zu Berlin
dc.rights(CC BY 4.0) Attribution 4.0 Internationalger
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjecturban sprawleng
dc.subjectLandsateng
dc.subjectCA–Markov modeleng
dc.subjectSDG 11eng
dc.subjecturban sustainable developmenteng
dc.subject.ddc630 Landwirtschaft und verwandte Bereichenone
dc.titleMonitoring and Modeling the Patterns and Trends of Urban Growth Using Urban Sprawl Matrix and CA-Markov Modelnone
dc.typearticle
dc.subtitleA Case Study of Karachi, Pakistannone
dc.identifier.urnurn:nbn:de:kobv:11-110-18452/23744-2
dc.identifier.doihttp://dx.doi.org/10.18452/23081
dc.type.versionpublishedVersionnone
local.edoc.container-titleLandnone
local.edoc.pages17none
local.edoc.type-nameZeitschriftenartikel
local.edoc.institutionMathematisch-Naturwissenschaftliche Fakultätnone
local.edoc.container-typeperiodical
local.edoc.container-type-nameZeitschrift
local.edoc.container-publisher-nameMDPInone
local.edoc.container-publisher-placeBaselnone
local.edoc.container-volume10none
local.edoc.container-issue7none
dc.description.versionPeer Reviewednone
local.edoc.container-articlenumber700none
dc.identifier.eissn2073-445X

Show simple item record