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An investigation of past and future LULC using multilayer perceptron-Markov chain techniques: a case study of a Himalayan smart city (2005–2040).

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Title: An investigation of past and future LULC using multilayer perceptron-Markov chain techniques: a case study of a Himalayan smart city (2005–2040).
Authors: Pant, Subhanshu1 (AUTHOR) subhanshupant@gmail.com, Agrawal, Sonam1 (AUTHOR) sonam@mnnit.ac.in, Kumar, Vivek1 (AUTHOR) vgupta491@gmail.com
Source: Environment, Development & Sustainability. Jul2026, Vol. 28 Issue 7, p16329-16356. 28p.
Subject Terms: *Multilayer perceptrons, *Markov processes, *Smart cities, *Land use, *Topography, *Urban growth, *Cities & towns
Geographic Terms: Dehra Dūn (India), India
Abstract: This study focuses on the Dehradun tehsil of India for urban growth modeling. It is one of the cities under 100 smart city plans by the Government of India. Land Use Land Cover (LULC) mapping is carried out for different years, i.e., 2005, 2009, 2013, 2017 and 2021. The LULC analysis shows that the built-up was 12.04% in 2005 and has continuously increased, reaching 26.53% in 2021. As per the change detection outputs, the maximum built-up gain of 5099 hectare occurred between 2005 and 2013, mainly at the loss of agriculture and forest. A Multilayer Perceptron (MLP) neural network was used to perform transition potential modeling. Four driving variables (slope, DEM, evidence likelihood and distance from road) and five LULC transitions (water to built-up, forest to built-up, agriculture to built-up, barren to built-up and forest to agriculture) were considered to generate transition potential. The transition potentials generated through MLP helped to predict LULC using the Markov Chain. The predicted LULC of 2021 was validated against the actual LULC for the same year. Finally, LULC for the years 2030 and 2040 was predicted. They forecasted a rise in commercial, industrial and residential area at the expense of forest cover and agricultural lands. The findings of this study could be valuable for government agencies, urban planners and respective departments. [ABSTRACT FROM AUTHOR]
Database: Energy & Power Source
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Header DbId: enr
DbLabel: Energy & Power Source
An: 194936977
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
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Items – Name: Title
  Label: Title
  Group: Ti
  Data: An investigation of past and future LULC using multilayer perceptron-Markov chain techniques: a case study of a Himalayan smart city (2005–2040).
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  Label: Authors
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  Data: <searchLink fieldCode="AR" term="%22Pant%2C+Subhanshu%22">Pant, Subhanshu</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> subhanshupant@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Agrawal%2C+Sonam%22">Agrawal, Sonam</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> sonam@mnnit.ac.in</i><br /><searchLink fieldCode="AR" term="%22Kumar%2C+Vivek%22">Kumar, Vivek</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> vgupta491@gmail.com</i>
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  Data: <searchLink fieldCode="JN" term="%22Environment%2C+Development+%26+Sustainability%22">Environment, Development & Sustainability</searchLink>. Jul2026, Vol. 28 Issue 7, p16329-16356. 28p.
– Name: Subject
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  Data: *<searchLink fieldCode="DE" term="%22Multilayer+perceptrons%22">Multilayer perceptrons</searchLink><br />*<searchLink fieldCode="DE" term="%22Markov+processes%22">Markov processes</searchLink><br />*<searchLink fieldCode="DE" term="%22Smart+cities%22">Smart cities</searchLink><br />*<searchLink fieldCode="DE" term="%22Land+use%22">Land use</searchLink><br />*<searchLink fieldCode="DE" term="%22Topography%22">Topography</searchLink><br />*<searchLink fieldCode="DE" term="%22Urban+growth%22">Urban growth</searchLink><br />*<searchLink fieldCode="DE" term="%22Cities+%26+towns%22">Cities & towns</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22Dehra+Dūn+%28India%29%22">Dehra Dūn (India)</searchLink><br /><searchLink fieldCode="DE" term="%22India%22">India</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: This study focuses on the Dehradun tehsil of India for urban growth modeling. It is one of the cities under 100 smart city plans by the Government of India. Land Use Land Cover (LULC) mapping is carried out for different years, i.e., 2005, 2009, 2013, 2017 and 2021. The LULC analysis shows that the built-up was 12.04% in 2005 and has continuously increased, reaching 26.53% in 2021. As per the change detection outputs, the maximum built-up gain of 5099 hectare occurred between 2005 and 2013, mainly at the loss of agriculture and forest. A Multilayer Perceptron (MLP) neural network was used to perform transition potential modeling. Four driving variables (slope, DEM, evidence likelihood and distance from road) and five LULC transitions (water to built-up, forest to built-up, agriculture to built-up, barren to built-up and forest to agriculture) were considered to generate transition potential. The transition potentials generated through MLP helped to predict LULC using the Markov Chain. The predicted LULC of 2021 was validated against the actual LULC for the same year. Finally, LULC for the years 2030 and 2040 was predicted. They forecasted a rise in commercial, industrial and residential area at the expense of forest cover and agricultural lands. The findings of this study could be valuable for government agencies, urban planners and respective departments. [ABSTRACT FROM AUTHOR]
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RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1007/s10668-024-05614-1
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 28
        StartPage: 16329
    Subjects:
      – SubjectFull: Multilayer perceptrons
        Type: general
      – SubjectFull: Markov processes
        Type: general
      – SubjectFull: Smart cities
        Type: general
      – SubjectFull: Land use
        Type: general
      – SubjectFull: Topography
        Type: general
      – SubjectFull: Urban growth
        Type: general
      – SubjectFull: Cities & towns
        Type: general
      – SubjectFull: Dehra Dūn (India)
        Type: general
      – SubjectFull: India
        Type: general
    Titles:
      – TitleFull: An investigation of past and future LULC using multilayer perceptron-Markov chain techniques: a case study of a Himalayan smart city (2005–2040).
        Type: main
  BibRelationships:
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      – PersonEntity:
          Name:
            NameFull: Pant, Subhanshu
      – PersonEntity:
          Name:
            NameFull: Agrawal, Sonam
      – PersonEntity:
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            NameFull: Kumar, Vivek
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            – D: 01
              M: 07
              Text: Jul2026
              Type: published
              Y: 2026
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              Value: 1387585X
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              Value: 28
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              Value: 7
          Titles:
            – TitleFull: Environment, Development & Sustainability
              Type: main
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