海岸环境卫生的维持.pptVIP

Assessing Housing Value in City of Toronto Xuefei Hui - Geographyic information system-winter 2009 Why choose this topic Rosen (1974) stated the market price of a good into the value of its constituents characteristics and obtain estimates of the contributory value of each characteristic. A simple, and common, example is that the price of a house may depend on its size, its location and other factors. It possible to construct a better model embedding correlating factors to predict the value of an asset. Influencing factors: suitability This is a suitability-oriented research, based on building relationship of population/population density with accessibility to transportation and other important factors affect dwelling decision. Road accessibility Transit accessibility Slope Aspect Goals of Research Use census data of city of Toronto into find out if the house value changes are positively correlated with the total suitability contributed by weighted factors. This research will reveal the spatial relationship between the house value change and each of the topographical factors. The first hypothesis is the house value is a function of suitability of different variables. The second hypothesis is all the suitability of each attribute take account different weight in total suitability. The goal of research is to predict the future “HOT” places Study area (City of Toronto) Toronto is a immigration city and the housing cost is increase as the population increase year by year. Multiple possible factors affecting the housing value are various: topography: slope, aspect, keen to lake shore view transportation: access to road and transportation How can GIS help? Data analysis Sampling technique Fuzzy logic Weight of suitability Data and Methodology 200106 average house value of each DAin city of Toronto (owner-occupied private non-farm, non-reserve dwelling), oak ridge moraine DEM file, 2006 total population in each DAs, Toro