A Geospatial Exploration of Surface Urban Heat Dynamics and Predictive Modeling in Kandy Municipal Council Using GIS and RS Techniques

dc.contributor.authorRanasinghe, L.A.
dc.contributor.authorKonara, K.M.K.P.
dc.contributor.authorJayarathne, M.
dc.date.accessioned2025-10-09T05:44:51Z
dc.date.issued2024
dc.description.abstractThis research, conducted in the Kandy MC area, addresses critical research gaps pertaining to urban temperature in mountainous regions. Bridging existing knowledge with current data, the study highlights a notable increase in maximum temperature from 31 °C in 2013 to 38°C in 2023, underscoring a significant 7°C rise. A unique observation reveals Deiyannewela consistently registering the highest temperature across all three time points. The research delves into the correlation dynamics, establishing a negative relationship between LST, NDWI and NDVI, while showcasing a positive correlation with the NDBI. Factoring in these correlations, the projected urban temperature for 2033 indicates a range of 32.88 to 41.2 degrees Celsius, reflecting a 3.2 °C increase from 2023.This temperature escalation underscores the urgent need for sustainable urbanization. The study advocates immediate measures to mitigate rising temperatures, emphasizing the incorporation of green spaces into future urban development strategies. In conclusion, the challenge of escalating surface temperatures in Kandy MC demands a comprehensive, multidimensional approach that integrates geographical insights with sustainable development practices. Drawing insights from Landsat 8, renowned for its 30m high resolution and spectral compatibility with MODIS data, this research spans 2013, 2018, and 2023, utilizing Landsat 8 imagery to calculate key indices such as LST, NDVI, NDWI, and NDBI. These findings offer a nuanced understanding of the temperature dynamics in the region, providing essential guidance for well-informed urban planning and laying the groundwork for climate-sensitive and sustainable development in rapidly urbanizing mountain cities like Kandy.
dc.identifier.citationRanasinghe, L.A., Konara, K.M.K.P., & Jayarathne, M. (2024). A Geospatial Exploration of Surface Urban Heat Dynamics and Predictive Modeling in Kandy Municipal Council Using GIS and RS Techniques. Journal of Colombo Geographer, 2(2), 1-25.
dc.identifier.issn3021-6478
dc.identifier.urihttps://archive.cmb.ac.lk/handle/70130/7947
dc.language.isoen
dc.publisherDepartment of Geography, University of Colombo
dc.subjectLand Surface Temperature (LST)
dc.subjectLandsat 8
dc.subjectCorrelation
dc.subjectSustainable Development
dc.subjectKandy MC
dc.titleA Geospatial Exploration of Surface Urban Heat Dynamics and Predictive Modeling in Kandy Municipal Council Using GIS and RS Techniques
dc.typeArticle

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