Estimating the Marginal Implicit Price of the Spatially Diverse Environmental Amenities from Urban Open Space in Onondaga County, New York: A Geographically Weighted Regression Approach

2017 ◽  
Author(s):  
Sanglim Yoo
Keyword(s):  
New York ◽  
Geographically Weighted Regression ◽  
Open Space ◽  
Weighted Regression ◽  
Environmental Amenities ◽  
Urban Open Space ◽  
Regression Approach ◽  
Onondaga County

Number of flood disaster estimation in Indonesia using local linear and geographically weighted regression approach

2021 ◽  
Author(s):  
M. Fariz Fadillah Mardianto ◽  
Sediono ◽  
Novia Anggita Aprilianti ◽  
Belindha Ayu Ardhani ◽  
Rizka Firdaus Rahmadina ◽  
...  
Keyword(s):  
Geographically Weighted Regression ◽  
Flood Disaster ◽  
Weighted Regression ◽  
Local Linear ◽  
Regression Approach

scholarly journals Local modelling of U.S. mortality rates: A multiscale geographically weighted regression approach

2020 ◽  
Author(s):  
Kyran Cupido ◽  
A. Stewart Fotheringham ◽  
Petar Jevtic
Keyword(s):  
Geographically Weighted Regression ◽  
Mortality Rates ◽  
Weighted Regression ◽  
Regression Approach

scholarly journals Valuing Environmental Amenities across Space: A Geographically Weighted Regression of Housing Preferences in Greenville County, SC

Land ◽  
2019 ◽  
Vol 8 (10) ◽  
pp. 147
Author(s):  
Hiebert ◽  
Allen
Keyword(s):  
Geographically Weighted Regression ◽  
City Planning ◽  
Spatial Dynamics ◽  
Ordinary Least Squares ◽  
Hedonic Model ◽  
Weighted Regression ◽  
Hedonic Price ◽  
Environmental Amenities ◽  
Forested Areas ◽  
The Impact

As global consumption and development rates continue to grow, there will be persistent stress placed on public goods, namely environmental amenities. Urban sprawl and development places pressure on forested areas, as they are often displaced or degraded in the name of economic development. This is problematic because environmental amenities are valued by the public, but traditional market analysis typically obscures the value of these goods and services that are not explicitly traded in a market setting. This research examines the non-market value of environmental amenities in Greenville County, SC, by utilizing a hedonic price model of home sale data in 2011. We overlaid home sale data with 2011 National Land Cover Data to estimate the value of a forest view, proximity to a forest, and proximity to agriculture on the value of homes. We then ran two regression models, an ordinary least squares (OLS) and a geographically weighted regression to compare the impact of space on the hedonic model variables. Results show that citizens in Greenville County are willing to pay for environmental amenities, particularly views of a forest and proximity to forested and agricultural areas. However, the impact and directionality of these variables differ greatly across space. These findings suggest the need for an integration of spatial dynamics into environmental valuation estimates to inform conservation policy and intentional city planning.

Regional spillover research and development investment: A geographically weighted regression approach

2013 ◽  
Vol 7 (33) ◽  
pp. 3212-3219 ◽  
Author(s):  
Rasekhi Saeed ◽  
Anousheh Shahrzad ◽  
Ranjbar Homayoun ◽  
Moghimi Maryam
Keyword(s):  
Research And Development ◽  
Geographically Weighted Regression ◽  
Weighted Regression ◽  
Regression Approach

RNN-GWR: A geographically weighted regression approach for frequently updated data

2020 ◽  
Vol 399 ◽  
pp. 258-270 ◽  
Author(s):  
Murat Tasyurek ◽  
Mete Celik
Keyword(s):  
Geographically Weighted Regression ◽  
Weighted Regression ◽  
Regression Approach
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