Dergiler / International Journal of Environment and Geoinformatics / 2026 / Volume: 8 Issue: 3

Cellular Automata and Markov Chain Based Urban Growth Prediction

Shrushti Jadawala(Department of Earth Sciences, Gujarat University)0000-0002-1312-3195
Shital H. Shukla(Department of Earth Sciences, School of Science, Gujarat University)
Poonam S. Tiwari(Indian Institute of Remote Sensing, Indian Space Research Organization, Department of Space, Government of India)
Sayfa
—
Yayın Tarihi
2021-09-05
🏛️Bu makalenin bibliyografik verileri ve tam metin bağlantısı DergiPark üzerinden sağlanmıştır.
DergiPark Kaydı ↗
✨

Yapay Zeka Hızlı Bakış & Çıkarımlar

AI Insight
⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

The study result reveals an increasing and decreasing trend in Land use and Land cover respectively.

📌 3 Maddede Bu Makale

🎯
Amaç & Hipotez:Remote sensing and Geographic Information System (GIS); plays a vital role for studying Land Use Land Cover (LULC) and identifying the main factors for useful outcomes.
📊
Temel Bulgular & Veri:It is located at 23.2156° N & 72.6369° E in Gujarat.
💡
Sonuç & Katkı:The study result reveals an increasing and decreasing trend in Land use and Land cover respectively.
🔬Tür:Research Article
📍Kapsam:2000 Verileri
⚙️Değişkenler:Land Use Land Cover Change (LULCC) · Landsat · Multispectral

Abstract

Remote sensing and Geographic Information System (GIS); plays a vital role for studying Land Use Land Cover (LULC) and identifying the main factors for useful outcomes. Assessment of the urban growth pattern is extremely essential as sprawl is seen as one of the potential threats for urban planning. The project has been carried out for the Land Use Land Cover classification of Gandhinagar district of Gujarat state. Gandhinagar city has experienced wide change in LULC in last few decades. It is located at 23.2156° N & 72.6369° E in Gujarat. LULC mapping of Gandhinagar was carried out using LANDSAT Multispectral, TM, ETM+, and OLI/TIRS images for the years 1972, 1977, 1987, 1994, 2000, 2008, 2015 and 2019. Landsat data covers Gandhinagar’s vegetation, Water Bodies, Open Area, Agriculture, and Settlement. The area of interest of Gandhinagar was generated from Landsat data using the digitized boundary of Gandhinagar district. The main objective of this project is to generate LULC using different classification method of remotely sensed data of LANDSAT. In this study Supervised classification method was used to generate level 1 classification. It was done on remotely sensed data in ERDAS Imagine 2014 using semi-automatic classification which includes several classes like Settlement, Agriculture, Vegetation, Water Bodies, Open Area, etc. Moreover, after LULC one new thing was done i.e. accuracy assessment which was necessary to do for accurate result. The study result reveals an increasing and decreasing trend in Land use and Land cover respectively.

🔖

Bu Makaleye Atıf Yap

Jadawala, S., Shukla, S. H., Tiwari, P. S. (2021). Cellular Automata and Markov Chain Based Urban Growth Prediction. International Journal of Environment and Geoinformatics, Volume: 8 Issue: 3. https://doi.org/10.30897/ijegeo.781574

📄 Tam Metin PDF Okuyucu

📄

PDF görüntüleyici hazırlanıyor...

Kaynakça (17)

  1. JafarNouri · AlirezaGharagozlou · Reza Arjmandi · ShahrzadFaryadi · MahsaAdl, 2012. Predicting Urban Land Use Changes Using a CA–Markov Model. Arab J SciEng DOI 10.1007/s13369-014-1119-2….
  2. Kshama Gupta, 2013. Unprecedented Growth of Dehradun Urban Area: A Spatio- Temporal Analysis. International Journal of Advancement in Remote Sensing, GIS and Geography. ….
  3. ThomosHouet and Thomos R. Loveland, 2009. Exploring subtle land use and land cover changes:. a framework for future landscape studies. Landscape Ecology, volume 25,issue 2,pp 249-266.
  4. Mukanda D Behera, Santosh N Borate, Sudhindra N Panda, Priti R Behera and Partha S Roy, 2012. Modelling and analysing the watershed dynamics using Cellular Automata [CA]- Markov model- A geo information based approach. J. Earth syst. SCi.121, No. 4, and pp.1011-1024. ….
  5. Pedro Cabral and Alexander Zamyatin, 2008. Markov Processes In Modeling Land Use And Land Cover Changes In Sintra-Cascais, Portugal. Dyna, Año 76, Nro. 158, pp. 191- 198. Medellín, Junio de 2009. ISSN 0012-7353. ….
  6. Pontius Jr R.G., and Schneider L.C, (2001), Landcover change model validation by an ROC method for the Ipswich watershed, Massachusetts, USA, Agriculture, Ecosystems and Environment, 85,pp 239248. ….
  7. Pontius Jr R.G., Huffaker D., and Denman K, (2004), Useful techniques of validation for spatially explicit land change models. Ecological modeling, 179,pp 445461. …………
  8. R. E. J. Boerner, Brent G. DeMars, Peter N. Leicht, 1996. Spatial patterns of mycorrhizal infectiveness of soils long a successional chronosequence. Mycorrhiza, volume 6, Issue 2,pp 79-90./….
  9. SamerehFalahatkar, Ali Reza Soffianian, SayedJamaleddinKhajeddin, Hamid Reza Ziaee, MozhganAhmadi Nadoushan,2011. Integration of Remote Sensing data and GIS [16] for prediction of land cover map. International Journal of Geomatics and Geosciences Volume 1, No 4.
  10. SandeepMaithani, 2010. Cellular automata based Model of Urban spatial growth. Indian Soc Remote Sens, 604-610.
  11. Thomas Houet, Laurence Hubert-Moy, 2007. Modeling and projecting land-use and land-cover changes with Cellular Automaton in considering landscape trajectories. HAL Id: halshs-00195847
  12. JafarNouri · AlirezaGharagozlou · Reza Arjmandi · ShahrzadFaryadi · MahsaAdl, 2012. Predicting Urban Land Use Changes Using a CA–Markov Model. Arab J SciEng DOI 10.1007/s13369-014-1119-2….
  13. Kshama Gupta, 2013. Unprecedented Growth of Dehradun Urban Area: A Spatio- Temporal Analysis. International Journal of Advancement in Remote Sensing, GIS and Geography. ….
  14. ThomosHouet and Thomos R. Loveland, 2009. Exploring subtle land use and land cover changes:. a framework for future landscape studies. Landscape Ecology, volume 25,issue 2,pp 249-266.
  15. R. E. J. Boerner, Brent G. DeMars, Peter N. Leicht, 1996. Spatial patterns of mycorrhizal infectiveness of soils long a successional chronosequence. Mycorrhiza, volume 6, Issue 2,pp 79-90./….
  16. SamerehFalahatkar, Ali Reza Soffianian, SayedJamaleddinKhajeddin, Hamid Reza Ziaee, MozhganAhmadi Nadoushan,2011. Integration of Remote Sensing data and GIS [16] for prediction of land cover map. International Journal of Geomatics and Geosciences Volume 1, No 4.
  17. SandeepMaithani, 2010. Cellular automata based Model of Urban spatial growth. Indian Soc Remote Sens, 604-610.