A hedonic linear regression model is constructed in this paper to estimate property value. In our model, the property value (sales price) is a function of several selected variables such as the property characteristic...A hedonic linear regression model is constructed in this paper to estimate property value. In our model, the property value (sales price) is a function of several selected variables such as the property characteristics, social neighborhoods, level of neighborhood environmental contaminations, level of neighborhood crimes, and locational accessibility to jobs or services. Definitions and calculation of these variables are approached by using Geographic Information System tools. For improving estimation, gravity model is employed to measure both levels of neighborhood toxic sites and crimes; and a time-based method is used to measure the locational accessibility rather than simple straight-line distance measurement. This study discovers that the relationship between house value and its nearby highway is nonlinear. The methodology could help policy makers assess the external effects of a property. Our model also could be used potentially to identify the current and historic trends of development caused by neighborhood or environments change in the study area.展开更多
A research method was presented for spatially quantifying and allocating the potential activity of a fine particle matter emission （ PM2.5 ）, which originated from residential wood burning （RWB） in this study. Dem...A research method was presented for spatially quantifying and allocating the potential activity of a fine particle matter emission （ PM2.5 ）, which originated from residential wood burning （RWB） in this study. Demographic, hypsographic, climatic and topographic data were compiled and processed within a geographic information system（GIS）, and as independent variables put into a linear regression model for describing spatial distribution of the potential activity of residential wood burning as primary heating source. In order to improve the estimation, the classifications of urban, suburban and rural were redefined to meet the specifications of this application. Also, several definitions of forest accessibility were tested for estimation. The results suggested that the potential activity of RWB was mostly determined by elevation of a location, forest accessibility, urban/non-urban position, climatic conditions and several demographic variables. The linear regression model could explain approximately 86% of the variation of surveyed potential activity of RWB. The analysis results were validated by employing survey data collected mainly from a WebGIS based phone interview over the study area in central California. Based on lots free public GIS data, the model provided an easy and ideal tool for geographic researchers, environmental planners and administrators to understand where and how much PM2.5 emission from RWB was contributed to air quality. With this knowledge they could identify regions of concern, and better plan mitigation strategies to improve air quality. Furthermore, it allows for future adjustment on some parameters as the spatial analysis method is implemented in the different regions or various eco-social models.展开更多
基金Under the auspices of the Research Client West Oakland Environmental Indicators Taskforce, Talented Foundationof Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences (No. C08Y17)
文摘A hedonic linear regression model is constructed in this paper to estimate property value. In our model, the property value (sales price) is a function of several selected variables such as the property characteristics, social neighborhoods, level of neighborhood environmental contaminations, level of neighborhood crimes, and locational accessibility to jobs or services. Definitions and calculation of these variables are approached by using Geographic Information System tools. For improving estimation, gravity model is employed to measure both levels of neighborhood toxic sites and crimes; and a time-based method is used to measure the locational accessibility rather than simple straight-line distance measurement. This study discovers that the relationship between house value and its nearby highway is nonlinear. The methodology could help policy makers assess the external effects of a property. Our model also could be used potentially to identify the current and historic trends of development caused by neighborhood or environments change in the study area.
基金The research contract fromCalifornia Air Resources Board (ARB) ,USAthe Talented FoundationfromNortheast Institute of Geography and AgriculturalEcology,Chinese Academy of Sciences ,China(No.C08Y17)
文摘A research method was presented for spatially quantifying and allocating the potential activity of a fine particle matter emission （ PM2.5 ）, which originated from residential wood burning （RWB） in this study. Demographic, hypsographic, climatic and topographic data were compiled and processed within a geographic information system（GIS）, and as independent variables put into a linear regression model for describing spatial distribution of the potential activity of residential wood burning as primary heating source. In order to improve the estimation, the classifications of urban, suburban and rural were redefined to meet the specifications of this application. Also, several definitions of forest accessibility were tested for estimation. The results suggested that the potential activity of RWB was mostly determined by elevation of a location, forest accessibility, urban/non-urban position, climatic conditions and several demographic variables. The linear regression model could explain approximately 86% of the variation of surveyed potential activity of RWB. The analysis results were validated by employing survey data collected mainly from a WebGIS based phone interview over the study area in central California. Based on lots free public GIS data, the model provided an easy and ideal tool for geographic researchers, environmental planners and administrators to understand where and how much PM2.5 emission from RWB was contributed to air quality. With this knowledge they could identify regions of concern, and better plan mitigation strategies to improve air quality. Furthermore, it allows for future adjustment on some parameters as the spatial analysis method is implemented in the different regions or various eco-social models.
