Using Satellite Imagery in Predicting Kansas Farmland Values

Can remotely sensed imagery improve hedonic land price models? A remotely sensed variable was added to a hedonic farmland value model as a proxy for land productivity. Land cover data were used to obtain urban and recreational effects as well. The urban and recreational effects were statistically significant but economically small. The remotely sensed productivity variable was statistically significant and economically large, indicating that knowing the "greenness" of the land increased the explanatory power of the hedonic price model. Thus, depending upon the cost of this information, including remotely sensed imagery in traditional hedonic land price models is economically beneficial.

Abstract licence: CC BY-NC

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