Modelling urban future: integrating CA-ANN model for comprehensive understanding of land use, land cover changes, and temperature dynamics in Lucknow City, India
Rapid urbanization and associated land use/land cover (LULC) changes significantly affect urban environments, intensifying urban heat islands (UHIs) and environmental challenges. This study presents a spatiotemporal analysis of LULC and land surface temperature (LST) changes in Lucknow City, India,...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2025-06-01
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| Series: | Geology, Ecology, and Landscapes |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/24749508.2025.2524207 |
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| author | Danish Khan Nizamuddin Khan |
| author_facet | Danish Khan Nizamuddin Khan |
| author_sort | Danish Khan |
| collection | DOAJ |
| description | Rapid urbanization and associated land use/land cover (LULC) changes significantly affect urban environments, intensifying urban heat islands (UHIs) and environmental challenges. This study presents a spatiotemporal analysis of LULC and land surface temperature (LST) changes in Lucknow City, India, from 2001 to 2021, and predicts scenarios for 2031. Using Landsat imagery and support vector machine classification, results reveal that built-up areas expanded from 10.93% (127.82 km²) to 25.47% (297.74 km²), while vegetation declined from 71.55% (836.43 km²) to 45.33% (530.04 km²). Mean LST increased from 25.3°C to 29.8°C, with 51.75% of the area reaching 30–35°C in 2021. Cellular automata–artificial neural network (CA-ANN) models predict built-up areas to reach 29.99% (350.51 km²) and vegetation to drop to 42.62% (498.10 km²) by 2031. The ANN model further forecasts UHI intensification, with 58.95% of the city experiencing LSTs above 30°C, reaching a maximum of 42.7°C. The findings emphasize the urgent need for sustainable urban planning to mitigate environmental degradation and maintain ecological balance amid ongoing urban expansion in Lucknow. |
| format | Article |
| id | doaj-art-166b59d0f49c48bfab68a04ecddfcf43 |
| institution | Kabale University |
| issn | 2474-9508 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Geology, Ecology, and Landscapes |
| spelling | doaj-art-166b59d0f49c48bfab68a04ecddfcf432025-08-20T03:27:56ZengTaylor & Francis GroupGeology, Ecology, and Landscapes2474-95082025-06-0112610.1080/24749508.2025.2524207Modelling urban future: integrating CA-ANN model for comprehensive understanding of land use, land cover changes, and temperature dynamics in Lucknow City, IndiaDanish Khan0Nizamuddin Khan1Interdisciplinary Department of Remote Sensing and GIS Applications, Faculty of Science, Aligarh Muslim University, Aligarh, IndiaDepartment of Geography, Faculty of Science, Aligarh Muslim University, Aligarh, IndiaRapid urbanization and associated land use/land cover (LULC) changes significantly affect urban environments, intensifying urban heat islands (UHIs) and environmental challenges. This study presents a spatiotemporal analysis of LULC and land surface temperature (LST) changes in Lucknow City, India, from 2001 to 2021, and predicts scenarios for 2031. Using Landsat imagery and support vector machine classification, results reveal that built-up areas expanded from 10.93% (127.82 km²) to 25.47% (297.74 km²), while vegetation declined from 71.55% (836.43 km²) to 45.33% (530.04 km²). Mean LST increased from 25.3°C to 29.8°C, with 51.75% of the area reaching 30–35°C in 2021. Cellular automata–artificial neural network (CA-ANN) models predict built-up areas to reach 29.99% (350.51 km²) and vegetation to drop to 42.62% (498.10 km²) by 2031. The ANN model further forecasts UHI intensification, with 58.95% of the city experiencing LSTs above 30°C, reaching a maximum of 42.7°C. The findings emphasize the urgent need for sustainable urban planning to mitigate environmental degradation and maintain ecological balance amid ongoing urban expansion in Lucknow.https://www.tandfonline.com/doi/10.1080/24749508.2025.2524207Land cover dynamicstemperature dynamicscellular automataartificial neural networksprediction modelling |
| spellingShingle | Danish Khan Nizamuddin Khan Modelling urban future: integrating CA-ANN model for comprehensive understanding of land use, land cover changes, and temperature dynamics in Lucknow City, India Geology, Ecology, and Landscapes Land cover dynamics temperature dynamics cellular automata artificial neural networks prediction modelling |
| title | Modelling urban future: integrating CA-ANN model for comprehensive understanding of land use, land cover changes, and temperature dynamics in Lucknow City, India |
| title_full | Modelling urban future: integrating CA-ANN model for comprehensive understanding of land use, land cover changes, and temperature dynamics in Lucknow City, India |
| title_fullStr | Modelling urban future: integrating CA-ANN model for comprehensive understanding of land use, land cover changes, and temperature dynamics in Lucknow City, India |
| title_full_unstemmed | Modelling urban future: integrating CA-ANN model for comprehensive understanding of land use, land cover changes, and temperature dynamics in Lucknow City, India |
| title_short | Modelling urban future: integrating CA-ANN model for comprehensive understanding of land use, land cover changes, and temperature dynamics in Lucknow City, India |
| title_sort | modelling urban future integrating ca ann model for comprehensive understanding of land use land cover changes and temperature dynamics in lucknow city india |
| topic | Land cover dynamics temperature dynamics cellular automata artificial neural networks prediction modelling |
| url | https://www.tandfonline.com/doi/10.1080/24749508.2025.2524207 |
| work_keys_str_mv | AT danishkhan modellingurbanfutureintegratingcaannmodelforcomprehensiveunderstandingoflanduselandcoverchangesandtemperaturedynamicsinlucknowcityindia AT nizamuddinkhan modellingurbanfutureintegratingcaannmodelforcomprehensiveunderstandingoflanduselandcoverchangesandtemperaturedynamicsinlucknowcityindia |