Logo do repositório
 
Publicação

Modelling urban sprawl using remotely sensed data

2017-04-07Artigo científico Acesso aberto
Ver registo simples
dc.contributor.authorPadmanaban, Rajchandar
dc.contributor.authorBhowmik, Avit K.
dc.contributor.authorCabral, Pedro
dc.contributor.authorZamyatin, Alexander
dc.contributor.authorAlmegdadi, Oraib
dc.contributor.authorWang, Shuangao
dc.contributor.institutionNOVA Information Management School (NOVA IMS)
dc.contributor.institutionInformation Management Research Center (MagIC) - NOVA Information Management School
dc.contributor.pblMDPI - Multidisciplinary Digital Publishing Institute
dc.date.accessioned2017-12-28T23:10:17Z
dc.date.available2017-12-28T23:10:17Z
dc.date.issued2017-04-07
dc.descriptionPadmanaban, R., Bhowmik, A. K., Cabral, P., Zamyatin, A., Almegdadi, O., & Wang, S. (2017). Modelling urban sprawl using remotely sensed data: A case study of Chennai city, Tamilnadu. Entropy, 19(4), 1-14. [163]. https://doi.org/10.3390/e19040163
dc.description.abstractUrban sprawl (US), propelled by rapid population growth leads to the shrinkage of productive agricultural lands and pristine forests in the suburban areas and, in turn, adversely affects the provision of ecosystem services. The quantification of US is thus crucial for effective urban planning and environmental management. Like many megacities in fast growing developing countries, Chennai, the capital of Tamilnadu and one of the business hubs in India, has experienced extensive US triggered by the doubling of total population over the past three decades. However, the extent and level of US has not yet been quantified and a prediction for future extent of US is lacking. We employed the Random Forest (RF) classification on Landsat imageries from 1991, 2003, and 2016, and computed six landscape metrics to delineate the extent of urban areas within a 10 km suburban buffer of Chennai. The level of US was then quantified using Renyi's entropy. A land change model was subsequently used to project land cover for 2027. A 70.35% expansion in urban areas was observed mainly towards the suburban periphery of Chennai between 1991 and 2016. The Renyi's entropy value for year 2016 was 0.9, exhibiting a two-fold level of US when compared to 1991. The spatial metrics values indicate that the existing urban areas became denser and the suburban agricultural, forests and particularly barren lands were transformed into fragmented urban settlements. The forecasted land cover for 2027 indicates a conversion of 13,670.33 ha (16.57% of the total landscape) of existing forests and agricultural lands into urban areas with an associated increase in the entropy value to 1.7, indicating a tremendous level of US. Our study provides useful metrics for urban planning authorities to address the social-ecological consequences of US and to protect ecosystem services.en
dc.description.versionpublishersversion
dc.description.versionpublished
dc.format.extent7580854
dc.identifier.doi10.3390/e19040163
dc.identifier.issn1099-4300
dc.identifier.otherPURE: 3260902
dc.identifier.otherPURE UUID: 6e0ed6b2-1127-4161-afe6-381fda170a24
dc.identifier.otherScopus: 85024484929
dc.identifier.otherWOS: 000400579500027
dc.identifier.otherORCID: /0000-0001-8622-6008/work/46764244
dc.identifier.urihttp://www.scopus.com/inward/record.url?scp=85024484929&partnerID=8YFLogxK
dc.identifier.urlhttps://www.scopus.com/pages/publications/85024484929
dc.language.isoeng
dc.peerreviewedyes
dc.subjectChennai
dc.subjectLand change modelling
dc.subjectRandom forest classification
dc.subjectRemote sensing
dc.subjectRenyi's entropy
dc.subjectSpatial metrics
dc.subjectSustainability
dc.subjectUrban growth model
dc.subjectUrban sprawl
dc.subjectGeneral Physics and Astronomy
dc.subjectSDG 15 - Life on Land
dc.titleModelling urban sprawl using remotely sensed dataen
dc.title.subtitleA case study of Chennai city, Tamilnaduen
dc.typejournal article
degois.publication.firstPage1
degois.publication.issue4
degois.publication.lastPage14
degois.publication.titleEntropy
degois.publication.volume19
dspace.entity.typePublication
rcaap.rightsopenAccess

Ficheiros

Principais
A mostrar 1 - 1 de 1
Miniatura
Nome:
PCabral_2017_e19040163.pdf
Tamanho:
7.23 MB
Formato:
Adobe Portable Document Format
Ver/Abrir

Coleções

NIMS: MagIC - Artigos em revista internacional com arbitragem científica (Peer-Review articles in international journals)