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Remote sensing and GIS approach to assess landform changes in Kaduwela divisional secretariat area and its impacts to the environment

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dc.contributor.author Gamsavi, K
dc.contributor.author Gajan, S
dc.contributor.author Jananthanan, B
dc.contributor.author Dissanayake, DMDOK
dc.contributor.author Chaminda, SP
dc.contributor.editor Dissanayake, DMDOK
dc.contributor.editor Jayawardena, CL
dc.date.accessioned 2022-02-28T06:58:45Z
dc.date.available 2022-02-28T06:58:45Z
dc.date.issued 2021-12
dc.identifier.citation Gamsavi, K., Gajan, S., Jananthanan, B. Dissanayake, D.M.D.O.K., & Chaminda, S.P. (2021). Remote sensing and GIS approach to assess landform changes in Kaduwela divisional secretariat area and its impacts to the environment. In D.M.D.O.K. Dissanayake & C.L. Jayawardena (Eds.), Proceedings of International Symposium on Earth Resources Management & Environment 2021 (pp. 91-98). Department of Earth Resources Engineering, University of Moratuwa. https://uom.lk/sites/default/files/ere/files/ISERME%202021%20Proceedings_2.pdf en_US
dc.identifier.uri http://dl.lib.uom.lk/handle/123/17108
dc.description.abstract Land use/land cover (LULC) change plays one of the major key roles in environmental impacts, and it is common to all nations. Monitoring this LULC change together with quantifications of environmental changes is an important concept in the Sustainable Development process. Therefore, remote sensing and geographic information system technique (RS & GIS) was used to exploit the variation of the LULC pattern, and satellite images of five years between 1997 and 2019 were used in this research. LULC changes in the Kaduwela Divisional Secretariat area were analysed using the Maximum likelihood supervised classification method and found that there was a significant decrease in vegetation cover due to rapid urbanisation. To assess landform changes and their impacts on the environment, normalised difference vegetation index (NDVI), normalised difference built-up index (NDBI), and land surface temperature (LST) were used. Further, relationships inbetween them were used to analyse the correlations between NDVI and LST, NDBI and LST, and NDVI and NDBI, and it was noticed that negative, positive, and negative correlations respectively among them. It indicates that healthy vegetation can decrease the land surface temperature, whereas built-up will enhance land surface temperature. More than 70% of overall accuracy for LULC classification was able to achieve in this study. en_US
dc.language.iso en en_US
dc.publisher Department of Earth Resources Engineering, University of Moratuwa en_US
dc.relation.uri https://uom.lk/sites/default/files/ere/files/ISERME%202021%20Proceedings_2.pdf en_US
dc.subject LST en_US
dc.subject LULC en_US
dc.subject NDBI en_US
dc.subject NDVI en_US
dc.subject Supervised classification en_US
dc.title Remote sensing and GIS approach to assess landform changes in Kaduwela divisional secretariat area and its impacts to the environment en_US
dc.type Conference-Full-text en_US
dc.identifier.faculty Engineering en_US
dc.identifier.department Department of Earth Resources Engineering en_US
dc.identifier.year 2021 en_US
dc.identifier.conference International Symposium on Earth Resources Management & Environment 2021 en_US
dc.identifier.place Colombo en_US
dc.identifier.pgnos pp. 91-98 en_US
dc.identifier.proceeding Proceedings of International Symposium on Earth Resources Management & Environment 2021 en_US
dc.identifier.email dmdok@uom.lk en_US


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