Symposia & Conferences
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Item Identification of suitable areas to cultivate Aloe vera in Kegalle District, Sri Lanka using GIS(4th International Research Symposium on Pure and Applied Sciences, Faculty of Science, University of Kelaniya, Sri Lanka, 2019) Dissanayake, C. T. M.; Weerasinghe, V. P. A.Aloe vera (Aloe barbadensis Miller) is used in ayurvedic medicine, pharmaceuticals, cosmetic products and also as a food product such as drinks or mixer with yoghurt. It is getting popular with the improvements in technology of harvesting and processing the product. In Sri Lanka, it is popular as a home garden crop, but not as a crop growing in large-scale. Most Sri Lankans are less aware of getting an income from Aloe vera. Therefore, the aim of this study is to make Aloe vera cultivation popular by identifying suitable areas to cultivate Aloe vera in Kegalle district, which was the study area of this research. Data analysis was done by using ArcGIS software tools to select the suitable areas. The criteria to grow Aloe vera successfully were selected using relevant literature. They were namely land uses such as coconut or bare lands, annual rainfall range as 1800 mm-2300 mm and annual temperature range as 25 °C - 26 °C. Those criteria were considered as most favorable factors to grow Aloe vera successfully with demanding leaf thicknesses. Land use data was collected from the Survey Department, Colombo and rainfall and temperature data were collected from the Meteorology Department, Colombo. Rainfall and temperature layers were developed by using Kriging interpolation technique in spatial geostatistics in ArcGIS software. Then land use layer, rainfall layer and temperature layer were overlaid using spatial analysis tools to identify the most suitable area, moderately suitable areas and not suitable areas. Kelegama and Rambukkana DSD areas are the most suitable areas to grow Aloe vera in Kegalle district. The final map generated from this study will be useful for extension/field officers of the Department of Agriculture, to enhance the awareness of people in Kegalle district about suitable places to grow Aloe vera in order to get an extra income as well as to get the maximum utility of the land.Item A geo-spatial analysis of dengue patients and rainfall in Sri Lanka -2017(Research Symposium on Pure and Applied Sciences, 2018 Faculty of Science, University of Kelaniya, Sri Lanka, 2018) Pathiraja, K.; Premadasa, S.; Gnanasinghe, S.; Wadasinghe, L. G. Y. J. G.; Weerasinghe, V. P. A.Dengue is one of the most prevalent arthropod borne virus affecting human. There are four serotypes that manifest with similar symptoms and two main vectors identified in Sri Lanka named as Aedes aegypti and Aedes albopictus. Dengue disease range from mild to dengue hemorrhagic fever. The distribution of dengue vector is varied mostly according to the rainfall. This study evaluates the relationship between percentage dengue patients in each district of Sri Lanka and monthly average rainfall distribution in 2017. Data was analyzed using ArcGIS 10.2 software. In order to get descriptive results, spatial autocorrelation (Moran’s I) was carried out. Positive Moran’s I shows that the average rainfall data are clustered according to the climatic zones in Sri Lanka and percentage dengue patients’ data for February, March, May, June, July and August months are clustered. Hot Spot Analysis was carried out for the clustered months for dengue patients. According to the Hot Spot Analysis the average rainfall distribution of each month of 2017 in Sri Lanka is restricted to specific districts; Hot spots are, Ampara (February), Rathnapura (May, June, July), Rathnapura and Kaluthara (September), Kaluthara (October) and Badulla (December) (99% confidence). Similarly, percentage dengue patients’ distribution in 2017 is restricted to specific districts; Hot spots are Trincomalee (February) and Colombo (March) (99% confidence). Ordinary Least Squares (OLS) linear regression was carried out to identify the relationship between the percentage dengue patients and monthly average rainfall. The variable distributions and relationships graphs of each month indicate a positive relationship between average rainfall and percentage dengue patients. Adjusted R2 in the diagnostic output of each month range between 0.7785 (June) and 0.1674 (February) and indicates that 16.74% - 77.85% of the variation in percentage dengue patients can be explained by average rainfall in 2017. It shows that only rainfall cannot explain the total percentage of dengue patients and that there are other environmental parameters which may contribute. There is a relationship between the percentage of dengue patients in each district and average rainfall distribution which appears to vary. Therefore, further studies should be carried out to identify other environmental parameters on the distribution of dengue such as atmospheric temperature, humidity, wind velocity, intensive farming, urbanization and solid waste disposal practices etc. Using multiple regression, multicollinearity between independent variables can be estimated using Geo statistics. Using environmental parameters, an environmental dengue index can be developed to further relate it with dengue patients’ percentage for geo-spatial analysis to develop a model for incidence of dengue in each district in Sri Lanka with varying environmental variables.