EconPapers    
Economics at your fingertips  
 

Landscape Assessment via Regression Analysis

Manuel Arriaza Balmón, Juan F. Canas, Juan A. Canas, Pedro Ruiz, Jose Gonzalez and Francisco Barea

No 24469, 2005 International Congress, August 23-27, 2005, Copenhagen, Denmark from European Association of Agricultural Economists

Abstract: This paper presents a methodology for assessing the visual quality of agricultural landscapes through direct and indirect techniques of landscape valuation. The first technique enables us to rank agricultural landscapes on the basis of a survey of public preferences. The latter weighs the contribution of the elements and attributes contained in the picture to its overall scenic beauty via regression analysis. The photos used in the survey included man-made elements, positive and negative, agricultural fields, mainly of cereals and olive trees, and a natural park. The results show that perceived visual quality increases, in decreasing order of importance, with the degree of wilderness of the landscape, the presence of well-preserved man-made elements, the percentage of plant cover, the amount of water, the presence of mountains and the colour contrast.

Keywords: Land; Economics/Use (search for similar items in EconPapers)
Date: 2005
References: View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link)
http://ageconsearch.umn.edu/record/24469/files/pp05ar01.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ags:eaae05:24469

DOI: 10.22004/ag.econ.24469

Access Statistics for this paper

More papers in 2005 International Congress, August 23-27, 2005, Copenhagen, Denmark from European Association of Agricultural Economists Contact information at EDIRC.
Bibliographic data for series maintained by AgEcon Search ().

 
Page updated 2019-10-12
Handle: RePEc:ags:eaae05:24469