Remote sensing based analysis of urban heat islands with vegetation cover in Colombo city, Sri Lanka using landsat-7 ETM+ data.

Urbanisation leads to rapid constructions, which use low albedo materials leading to high heat absorption in urban centres. In addition, removal of vegetation cover and emissions of waste heat from various sources contribute to the accumulation of heat energy, leading to formation of urban heat islands (UHIs). UHIs have many adverse socio-environmental impacts. Therefore, spatial identification of UHIs is a necessity to take appropriate remedial measures to minimise their adverse impacts. Satellite remote sensing provides a cost-effective and time-saving methodology for spatio-temporal analyses of land surface temperature (LST) distribution. In this study, thermal bands (10.40–12.50 μm) of Landsat-7 ETM+ imagery acquired in 3 distinct dates covering Colombo city of Sri Lanka were analysed for the spatio-temporal identification of UHIs. Vegetation cover of Colombo city was extracted by using NDVI method and subsequently examined with the distribution of LST. A deductive index was defined to identify the environmentally critical areas in Colombo city based on the distribution of LST and availability of vegetation cover. Accordingly, Colombo harbour and surrounding areas were identified as the most critical areas. Remedial measures can be taken in future urban planning endeavours based on the results of this study

Assessment of green space requirement and site analysis in Colombo, Sri Lanka : a remote sensing and GIS approach

Green space distribution plays a vital role in urban planning since they contribute significantly in enhancing environmental quality of metropolitan areas by improving air quality, urban health, conserving biodiversity, reducing noise, etc. Migration of rural population into urban areas and widespread industrialization lead to the rapid growth of urban population, consequently expanding urban sprawls. Removal of vegetation cover can be identified as one of the most adverse effects of urbanization. Proper distribution of green spaces in urban environments is therefore a necessity for the sustainable development and healthy living. Hence, it is essential to identify the green space requirement quantitatively and spatially. In this endeavour, integration of remote sensing and GIS techniques can provide a time and cost effective methodology.Colombo city of Sri Lanka has been identified as one of the most polluted cities in South Asian region. Rapid urbanization and the population growth are the main causes for the degradation of environmental quality in Colombo. Unplanned constructions and settlements in Colombo have contributed to significant reduction of green spaces. Therefore, special consideration has to be made for the proper distribution of green spaces in future development and planning projects in Colombo. In this study, available green spaces in Colombo are extracted through NDVI method using THEOS satellite imagery. Subsequently, green spaces required to be created are calculated with respect to WHO standards of green spaces per capita for healthy living (9.5 m2/ person) and a methodology is developed to spatially define appropriate areas to establish them

Remote sensing and GIS based assessment of water scarcity: a case study from Hambantota district, Sri Lanka.

Sea level anomalies in the South China Sea are greatly influenced by interannual fluctuations. Studies have verified that mean sea level anomalies are negative during El Niño episodes and are positive during La Niña episodes. For this research, records of mean sea level anomalies from multiple satellite altimetry missions were obtained from the Radar Altimetry Database (RADS) web interface. The mean sea level anomalies were computed from 1991 to 2011, both for the entire Philippines and Bolinao, Pangasinan. To further illustrate the variability of sea level anomalies for the strong El Niño and La Niña years, prediction surfaces were generated from the satellite altimetry data using the Local Polynomial Interpolation method in ArcGIS. The distribution of sea level anomalies for the entire Philippines and Bolinao, Pangasinan for the strong El Niño (1991 and 1997) and La Niña (2001 and 2010) episodes were generated. Based on satellite altimetry, the approximate values of mean sea level rise for the Philippines and Bolinao, Pangasinan from 1991 to 2011 were 6.95 millimeters (0.00695 meters) and 7.28 millimeters (0.00728 meters), respectively. The estimated mean sea level anomaly for the entire Philippines from 1991 to 2011 is equivalent to 45.59 millimeters (0.04559 meters) and 38.51 millimeters (0.03851 meters) for Bolinao, Pangasinan. Mean sea level anomalies for the highly vulnerable provinces to climate and weather related risks were also calculated and the correlation between ENSO and mean sea level anomalies was further verified

Development of a flood hazard zonation map fur "Kalu Ganga" basin by GIS modelling

"Kalu ganga" (river) is one of the major rivers in Sri Lanka situated in south-western part of the country. Kalu ganga basin area is a highly populated area comprising urban centres and agricultural fields. River floods frequently occur in this area resulting severe damage and destructions. Local planers, decision makers and disaster relief organizations lacks accurate information on the spatial distribution of flooding and the land-use types. Only minimal efforts and resources have been allocated to deal with this problem. The objective of this research is to develop flood hazard zone maps for the Kalu ganga basin area in a Geographic Information Systems (GIS) environment. The applied methodology is comprised of 5 phases. They are preparation phase, fieldwork and data acquisition phase, modelling and flood hazard map generation phase, validation phase and reporting phase. According to the generated flood hazard map, Kuruvita, Elapitiya and Rathnapura divisional secretariats have the highest risk of flooding. Most divisional secretariats in the western province exhibit low or moderate risks of flooding. According to the analysis of flood hazard map with land-use classes, 2307hectares of residential areas and 5568 hectares of agricultural fields were found to be at high risk of flooding

Dissolution origin of Ontario Lacus on Titan: evidences from geomorphological mapping, terrestrial analogs (Namibia) and laboratory experiments

Poster 63