TY - GEN
T1 - Modelling environmental influences on property prices in an urban environment
AU - Lake, Iain R.
AU - Lovett, Andrew A.
AU - Bateman, Ian J.
AU - Langford, Ian H.
PY - 1998/3/1
Y1 - 1998/3/1
N2 - The aim of this research was to assign money values to the negative impacts associated with road development, more specifically noise and visual intrusion. These impacts do not have observable prices and so have to be calculated indirectly. One way of doing this is to examine their effect upon house prices. The valuations such a method produces can then be included alongside other costs and benefits in the appraisal of a road development. However in order to calculate these prices, one also has to control for the many other factors that affect house prices, in addition to specifying the two road variables. In previous research this has required much time and effort which has consequently limited the scope of such studies. The aim of this project was to use a geographical information system (GIS) and large-scale digital data to derive all the required variables in a quick and efficient manner. The flexibility of a GIS allows a large number of possible explanatory variables to be calculated, leading to a large and complex dataset. This paper describes how such a dataset was modelled and price estimates for road noise and the visual intrusion extracted. It concludes by commenting upon the benefits of using GIS in this type of study and considers the main limitations to their wider adoption.
AB - The aim of this research was to assign money values to the negative impacts associated with road development, more specifically noise and visual intrusion. These impacts do not have observable prices and so have to be calculated indirectly. One way of doing this is to examine their effect upon house prices. The valuations such a method produces can then be included alongside other costs and benefits in the appraisal of a road development. However in order to calculate these prices, one also has to control for the many other factors that affect house prices, in addition to specifying the two road variables. In previous research this has required much time and effort which has consequently limited the scope of such studies. The aim of this project was to use a geographical information system (GIS) and large-scale digital data to derive all the required variables in a quick and efficient manner. The flexibility of a GIS allows a large number of possible explanatory variables to be calculated, leading to a large and complex dataset. This paper describes how such a dataset was modelled and price estimates for road noise and the visual intrusion extracted. It concludes by commenting upon the benefits of using GIS in this type of study and considers the main limitations to their wider adoption.
UR - http://www.scopus.com/inward/record.url?scp=0032029091&partnerID=8YFLogxK
U2 - 10.1016/S0198-9715(98)00012-X
DO - 10.1016/S0198-9715(98)00012-X
M3 - Article
AN - SCOPUS:0032029091
VL - 22
SP - 121
EP - 136
JO - Computers, Environment and Urban Systems
JF - Computers, Environment and Urban Systems
SN - 0198-9715
ER -