Simulation and projection of land use and land cover using remote sensing data and CA–Markov model case study
Land use and appearance have a significant effect on our surroundings and natural assets. This study investigates how land usage has changed over the last twenty years using a statistical independence assessment and CA (Cellular Automata) Markov process in predicting forthcoming Land Use and Land Co...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2025-12-01
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| Series: | Geocarto International |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/10106049.2025.2450441 |
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| Summary: | Land use and appearance have a significant effect on our surroundings and natural assets. This study investigates how land usage has changed over the last twenty years using a statistical independence assessment and CA (Cellular Automata) Markov process in predicting forthcoming Land Use and Land Cover (LULC) alterations. The Talcher region has experienced notable transformations in LULC over the recent decades. Markovian algorithm’s efficiency and validation utilized two images from 2000 and 2010, while validation of CA-Markov predictions relied on a ground-based land cover image from 2020. Once the model was checked and found to be accurate, we used it to predict how land use might change in 2025. Scrutinizing maps shown in satellite images, the people’s activities and the environment altered towns and cities in the area. It suggests an expansion of areas, by 2025. The study will help in planning cities and policy decisions. |
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| ISSN: | 1010-6049 1752-0762 |