SAPNA KINATTINKARA (2021) Assessment and Predicting of LULC by Kappa Analysis and CA Markov model using RS and GIS Techniques in Udham Singh Nagar District, India. Assessment and Predicting of LULC by Kappa Analysis and CA Markov model using RS and GIS Techniques in Udham Singh Nagar District, India. ISSN 2693-5015

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Abstract

In this study an attempt to generate the LULC maps and investigate change detection analysis over a period of 22
years using Landsat satellite images of 1994, 2000, and 2016 and to predict the LULCC for the year 2016-2032
using CA Markov model in Udham Singh Nagar district, Uttarkhand. Satellite images of Landsat 5 TM, Landsat 7
ETM+, and Landsat 8 OLI sensor of nominal spatial resolution 30m were used. Supervised image classifications
with the help of parallel pipe algorithm were used in this study. The validity of the Cellular Automata Markov
model were used to predict future (16 years) LULC of 2032. The estimation includes two modules to predict the
future land use pattern of the study area such as MARKOV and CA-MARKOV model/modules. Commonly, the
accuracy of the classification results is assessed by the error matrix calculation. The result of overall change
detection indicates agriculture, forest, water body and fallow land are decreased by 121.75 Km2 (14%), 44.70 Km2
(5%), 38.91 Km2 (4.5%) and 230.71 (26.5%); settlement and river sand are increased by 379.89 Km2 (44%) and
56.18 Km2 (6%). The study has an overall classification accuracy 76.84%, and standard kappa coefficient value (K)
of 0.722. The model predicts the future change detection in agriculture 32%, forest 38%, fallow land 5%, settlement
20%, water body 3%, and river sand is 2%. This study is very effective for future LULC prediction that is helpful in
urban development planning and the field of management of natural resources

Item Type: Article
Uncontrolled Keywords: Accuracy assessment, CA MARKOV model, GIS, LULC, Uttarkhand
Divisions: PSG College of Arts and Science > Department of Environmental Science
Depositing User: Mr Team Mosys
Date Deposited: 11 Sep 2024 09:39
Last Modified: 11 Sep 2024 09:39
URI: https://ir.psgcas.ac.in/id/eprint/2254

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