Scopus:
Modeling and simulating land use/cover change using artificial neural network from remotely sensing data

dc.contributor.authorBuğday E.
dc.contributor.authorErkan Buğday S.
dc.date.accessioned2023-04-12T01:53:55Z
dc.date.available2023-04-12T01:53:55Z
dc.date.issued2019-04-01
dc.description.abstractIncreasing population, mobility and requirements of human beings have significant effects on the dynamics of land use and land cover. Today, these impacts need to be understood and analyzed for the applicability of decision support systems, which are an important tool in the management of natural resources, urban and rural areas. The aim of this study is to detect the temporal and spatial changes of land cover and human population, in northwest Turkey. For this purpose, using satellite images of 1997-2007 and 2017 years’ land cover was estimated for 2027 by ANN (Artificial Neural Network) approach. Kappa values are 93%, 87% and 95% for 1997, 2007 and 2017 respectively. As a result, learning success was 80.6%, and correctness validation value was 90.1% for 2027 simulation. In parallel, the spatial analysis of the population was conducted for 2000-2007-2017. Using the exponential rate of change; the population was predicted to increase by concentrating on the urban area and the rural areas surrounding the urban (with a rate of 2.019%) for 2027. According to the results; rural population, urban population, forest, and built-up areas is estimated to increase by 4.14%, 5.58%, 2.72%, and 0.77% respectively from 2017 to 2027, while the agricultural and water area is estimated to decrease by 3.47% and 0.02% respectively. Consequently, the observation of population movements and the use of the ANN approach in simulations could be suggested for the success of planning in forest and land management.
dc.identifier.doi10.1590/01047760201925022634
dc.identifier.issn01047760
dc.identifier.scopus2-s2.0-85073458110
dc.identifier.urihttps://hdl.handle.net/20.500.12597/5054
dc.relation.ispartofCerne
dc.rightstrue
dc.subjectComputational intelligence | Forecasting | Human population | Landscape
dc.titleModeling and simulating land use/cover change using artificial neural network from remotely sensing data
dc.typeArticle
dspace.entity.typeScopus
oaire.citation.issue2
oaire.citation.volume25
person.affiliation.nameÇankiri Karatekin Üniversitesi
person.affiliation.nameKastamonu University
person.identifier.orcid0000-0002-3054-1516
person.identifier.orcid0000-0003-2989-2551
person.identifier.scopus-author-id57208015627
person.identifier.scopus-author-id57193562608
relation.isPublicationOfScopus5c2c02f8-cd4d-4f92-b629-8126f61b88a8
relation.isPublicationOfScopus.latestForDiscovery5c2c02f8-cd4d-4f92-b629-8126f61b88a8

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