Përdorimi i inteligjencës artificiale në hartat mjedisore në Tiranë. Një rrugë drejt planifikimit urban të qëndrueshëm.
Abstrakti
Tirana, the capital of Albania, has experienced rapid urban development, resulting in significant environmental challenges. Historical data reveal a drastic reduction in green space per capita, from approximately 10 m² during the communist period to a concerning 0.5 m² in recent years. This de-cline highlights the urgent need for sustainable urban planning strategies that prioritize ecological resilience. This study explores the innovative application of Artificial Intelligence (AI) platforms to compile comprehensive environmental maps of Tirana, aiming to address the city’s sustainability challenges. By integrating AI techniques with urban planning, the research seeks to offer a novel approach to enhancing urban environments and ecological sustainability. Utilizing a diverse array of AI techniques, including machine learning algorithms, remote sensing data analysis, and predictive modeling, the study aggregates and interprets vast datasets. These meth-ods are employed to produce detailed environmental maps that highlight key features and challenges within the city, such as the distribution of green spaces, pollution hotspots, urban heat islands, and water management areas. The generated maps provide unprecedented insights into Tirana’s environmental dynamics, illumi-nating the areas most in need of intervention. This mapping enables the classification of the city into climatic zones, aiding in the identification of urgent regulatory plan interventions. The findings underscore the potential of AI in revolutionizing environmental monitoring and management, facili-tating informed decision-making for urban development strategies. By presenting Tirana as a focal point, this research showcases the practical applications and benefits of AI in environmental mapping and sets a precedent for other cities aiming to integrate advanced technologies into their environmental planning processes. The study emphasizes the importance of creating public and green spaces within urban settings, highlighting Tirana as a case study for avoid-ing environmental degradation in similar contexts. With population projections indicating significant growth, the necessity for adopting AI-driven environmental planning becomes increasingly evident as a means to ensure sustainable urban development and ecological resilience.
Fjalët kyçe:
Artificial Intelligence, Environmental Mapping, Sustainable Urban Planning, Tirana, Green Spaces, Urban DevelopmentShkarkimet
References
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Climate-Data.org
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SUTTON W. R., SRIVASTAVA J. P., NEUMANN J. E.: Looking Beyond the Horizon: How Climate Change Impacts and Adaptation Responses will Reshape Agriculture in Eastern Europe and Central Asia. Directions in development: Agriculture and Rural Development, (2013), Washington, DC: World Bank. https://openknowledge.worldbank.org/handle/10986/13119
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STEWART I. D., OKE, T.: Local Climate Zones for Urban Temperature Studies. Bulletin of the American Meteorological Society, 12 (2012), vol.93, pp. 1879–1900. doi: 10.1175/BAMS-D-11-00019
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Institute of Statistics Reports
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UNGER J., LELOVICS E., GÁL T.: Local Climate Zone mapping using GIS methods in Szeged, (2014), Hungarian Geographical Bulletin, 63(1), 29-41.
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DEMUZERE M., KITTNER J., BECHTEL B.: A Web Application to Create Local Climate Zone Maps. Frontiers in Environmental Science, 23 (April 2021), vol.9. doi: 10.3389/fenvs.2021.637455
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OLIVEIRA A., LOPES A., NIZA S.: Local climate zones classification method from Copernicus land monitoring service datasets: An ArcGIS-based toolbox. MethodsX, (2020), vol.7. doi: 10.1016/j.mex.2020.101150
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KAMROWSKA-ZAŁUSKA, D. Impact of AI-Based Tools and Urban Big Data Analytics on the Design and Planning of Cities. Land 2021, 10, 1209. https://doi.org/10.3390/land10111209
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AMERICAN PLANNING ASSOCIATION, AI in Planning: Opportunities and Challenges and How to Prepare, 2022
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CENAMERI A., ALBERT G.: Local climate zone mapping of Tirana, Albania, (2021), Abstracts of the ICA, 3, 49.
References
Climate-Data.org
SUTTON W. R., SRIVASTAVA J. P., NEUMANN J. E.: Looking Beyond the Horizon: How Climate Change Impacts and Adaptation Responses will Reshape Agriculture in Eastern Europe and Central Asia. Directions in development: Agriculture and Rural Development, (2013), Washington, DC: World Bank. https://openknowledge.worldbank.org/handle/10986/13119
STEWART I. D., OKE, T.: Local Climate Zones for Urban Temperature Studies. Bulletin of the American Meteorological Society, 12 (2012), vol.93, pp. 1879–1900. doi: 10.1175/BAMS-D-11-00019
Institute of Statistics Reports
UNGER J., LELOVICS E., GÁL T.: Local Climate Zone mapping using GIS methods in Szeged, (2014), Hungarian Geographical Bulletin, 63(1), 29-41.
DEMUZERE M., KITTNER J., BECHTEL B.: A Web Application to Create Local Climate Zone Maps. Frontiers in Environmental Science, 23 (April 2021), vol.9. doi: 10.3389/fenvs.2021.637455
OLIVEIRA A., LOPES A., NIZA S.: Local climate zones classification method from Copernicus land monitoring service datasets: An ArcGIS-based toolbox. MethodsX, (2020), vol.7. doi: 10.1016/j.mex.2020.101150
KAMROWSKA-ZAŁUSKA, D. Impact of AI-Based Tools and Urban Big Data Analytics on the Design and Planning of Cities. Land 2021, 10, 1209. https://doi.org/10.3390/land10111209
AMERICAN PLANNING ASSOCIATION, AI in Planning: Opportunities and Challenges and How to Prepare, 2022
CENAMERI A., ALBERT G.: Local climate zone mapping of Tirana, Albania, (2021), Abstracts of the ICA, 3, 49.