Multilayer perceptron and Markov Chain analysis based hybrid-approach for predicting land use land cover change dynamics with Sentinel-2 imagery
| Autor: | Hasnain Abbas, Wang Tao, Garee Khan, Abdulwahed Fahad Alrefaei, Javed Iqbal, Mohammed Fahad Albeshr, Isma Kulsoom |
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| Jazyk: | angličtina |
| Rok vydání: | 2023 |
| Předmět: | |
| Zdroj: | Geocarto International, Vol 38, Iss 1 (2023) |
| Druh dokumentu: | article |
| ISSN: | 1010-6049 1752-0762 10106049 |
| DOI: | 10.1080/10106049.2023.2256297 |
| Popis: | As urbanization accelerates, the degree of human impact on land use is increasing. land use land cover change (LULC) is acknowledged as crucial factor in environmental change. The best way to understand historical land use patterns, changes, drivers, and developments is through a rigorous assessment of LULC changes. In this study, we aim to identify LULC changes from 2015 to 2022, and predict changes for 2030. Sentinel-2 images were employed to analyze LULC change patterns and predict future trends. The Random Forest algorithm was used to classify the various LULC classes with high accuracy and reliability. Multilayer Perceptron and Markov Chain Analysis (MLP-MCA) based Hybrid-Approach was employed to predict the future dynamics of LULC change for 2030. The study revealed that built-up area expanded 90.64 km2 from 2015 to 2022 due to natural resource substitution. Predictions indicate that 58.84% of the study area will be transform into built-up by 2030. |
| Databáze: | Directory of Open Access Journals |
| Externí odkaz: |
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