Many scholars focused on the location based attributes rather than the non-location factors in decision making on land prices. Further, new research studies have identified the importance of the non-location attributes with the location factors. Many studies suggest that, many attributes exist which affects the housing price. Since the attributes involved and dominant for a particular case differs from one situation to the other, there cannot be an exact list of attributes. Yet, identification of factors that determine housing price and their relationships and the level of influence have poorly understood in planning and property development in the context of Sri Lanka. This study attempts to address what make householders to decide on housing price and application of hedonic pricing approach to estimate the implicit price of housing attributes in context of Sri Lanka. A sample study of selected fifty (50) single house transactions in Maharagama urban neighborhood area has been utilized to illustrate the applicability of the hedonic pricing model. As a methodology, correlation analysis has been carried out to study the degree of relationship between the housing price and the independent variables. The attributes which correlate with housing prices, the study identified the most significant attributes. A model was developed to estimate the future house price by applying the pricing model which is incorporated with these attributes. A hedonic house price model derived from multiple liner regression analysis was developed for the purpose. The findings reveal that six attributes as design type of the house, distance to the local road, quality of Infrastructure, garden size, number of the bed rooms and property age are contributed to estimate the implicit value of Housing property. The model developed would be used to identify implicit values of houses located in urban neighborhood area of Sri Lanka.

The quality of the neighboring environment plays a major role in encouraging people to walk when attending their daily needs. Although past studies have identified a relationship between neighborhood design factors and the level of walkability, this interdependence is poorly understood in urban planning in Sri Lanka. The purpose of this study is to determine factors and conditions that influence walkability in a selected neighborhood in the town of Panadura and develop a model to predict what design factors enhance walkability in the neighborhood area. Ninety three (93) factors that affect the walkability in urban neighborhood were identified as the findings of the literature review of this study. Seventy six (76) walkability factors identified through perception surveys were examined within a 100m radius of 70 buffered circles representing 140 participants' residences through a questionnaire survey and field observations. Chi-square and Bivariate correlation analysis were carried out to identify the most decisive factors for walkability. Multiple Linear Regression analysis was applied to develop a model to assess the level of walkability of residents in the selected area based on the most significant factors. The study has identified main nine variables that determine the level of walkability. Based on the significant values the model can be used to assess the level of walkability of the people in Sri Lankan context.

Sri Lanka is a rapidly urbanizing country with 70% of its urban population and 80% of national economic infrastructure concentrated along the coastal cities of the country which are more susceptible for climate change impact and disaster risks. Drought is one of the worst natural disasters that affect Sri Lanka and create numerous problems by making adverse impacts to the economy of the country. Forecasting the drought period before the occurrence and implementation of appropriate drought management strategies may help to reduce the disaster risk and its related impacts mainly in coastal cities of Sri Lanka. Meteorological droughts eventually trigger other forms of droughts in Sri Lanka and it leads to water scarcity due to insufficient precipitation and high evaporation or combination of both. This study analyses the time series characteristics of total monthly precipitation and mean monthly temperature from year 1950 to 2013 for Mannar urban development area located in coastal zone of Sri Lanka to identify specific drought period in Mannar urban development area since it has been changing due to different climate change scenarios.Brainstorming approach was applied to identify sustainable drought management strategies and to validate the above identified drought period as an outcome of time series analyses and location specific information on drought in ground situation by consulting community and other prospective stakeholders in the area. Weather data was analyzed applying decomposition method of time series analyses which include trend, cycle, seasonal and irregular components. Considering results of time series analyses, high temperature and severe drought situation can be identified in Mannar urban development area from March to September while observing highest rainfall during October to December every year. The total monthly precipitation in Mannar has been increasing by 0.0194 mm while mean monthly temperature is increasing by 0.0004°C. As drought management strategies, the excess water of three months rainy season could be better utilized by developing new irrigation tanks and existing abundant tanks in many parts of the Mannar urban development area. Rain water harvesting and introducing new crops suitable for changing climatic conditions will be encouraged for sustainable dry farming activities in Mannar urban development area. Vertical greenery on walls, greenery on roof tops and green paving are being planned and building design strategies that can be promoted to reduce the heat environment of Mannar urban development area in sustainable Mannar.

Climate change has raised much concern regarding its impacts on future land use planning, varying by region, time, and socio-economic development path. The principle purpose of land suitability evaluation is to predict the potential and limitation of the land for crop production and other land uses. This study was carried out to predict the temperature and rainfall trends as one of the major factor for evaluating land suitability. Climatic data such as monthly mean temperature, total monthly rainfall, maximum daily rainfall and total annual rainfall during last 30 years of all weather stations located in Bentota River basin was collected and analyzed applying time series analysis, correlation analysis and Manna Kendall trend test methods. Spatial distribution of forecast rainfall values was illustrated applying Arc GIS software. The findings revealed that monthly mean temperature and maximum daily rainfall had a general increasing trend whereas, total monthly rainfall and total annual rainfall showed a general decreasing trend in  Bentota area. It was indicated relatively high rainfall situations during May and October while low rainfall situations during January and February by occurring flood situation in once per five year. During Yala season the area will be received comparatively more rainfall (331mm) than Maha season (300mm) in future. Community and the farmers in this area can be aware about the anticipated spatial distribution of total monthly rainfall during two major seasons and flood occurrence periods. Decision makers should evaluate land suitability of Bentota area by considering above climatological influences and its spatial distribution pattern that identified as major outcome of this research. The approach and the methodology adopted in this study will be useful for other researchers, agriculturalist and planners to identify the future climatological influences and its spatial distribution pattern for land suitability evaluations and other decision making purposes for other areas.

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