Cellular Automata and Markov Chain Based Urban Growth Prediction

Year 2021, Volume: 8 Issue: 3, 337 - 343, 05.09.2021

Shrushti Jadawala Shital H. Shukla Poonam S. Tiwari

https://doi.org/10.30897/ijegeo.781574

Cited By: 3

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.

Keywords

Land Use Land Cover Change (LULCC), Landsat, Multispectral, Thematic Mapper (TM), Enhanced Thematic Mapper Plus (ETM+), Operational Land Imager (OLI), Thermal Infrared Sensors (TIRS), Accuracy Assessment

Supporting Institution

Indian Institute of Remote Sensing (IIRS), Indian Space Research Organisation (ISRO), Department of Space, Government of India, Dehradun

Project Number

1

Thanks

special thanks to my guide Poonam S. Tiwari for constant support, also to this IJEGEO for helping to publish paper, to my head of department Shital Shukla.

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