Eres : Digital Library : Works

Paper eres2017_511:
Image Analyses and Real Estate: Evaluation of the Quality of Location Using Remotely Sensed Imagery

id eres2017_511
authors Despotovic, Miroslav; David Koch, Gunther Maier, Matthias Zeppelzauer
year 2017
title Image Analyses and Real Estate: Evaluation of the Quality of Location Using Remotely Sensed Imagery
source 24th Annual European Real Estate Society Conference in Delft, Netherlands
summary A growing number of applied studies examine the impact of urban space quality on property price. Especially the planning and development of the immediate neighborhood (micro location) is an important influencing factor in regional economics. An image-based method for the estimation of location quality, in the context of property valuation, does not exist yet. We develop method for the determination of the quality of location using image processing, taking at the same time into account the classification in quality classes based on regional structural characteristics. With the help of automatic image analysis, a new information source is leveraged, which previously could not be taken into account within the scope of evaluation of location quality or within the scope of automated valuation models (e.g. hedonic models). In the field of image analysis, the extraction of parameters related to location quality is a new task. It is so far not clear to which degree meaningful parameters can be found autonomously by machine learning. This dissertation will investigate this question in detail and is to our knowledge the first approach for the automatic image-based valuation of location quality.
keywords location quality; hedonic pricing; image processing; neighborhoods; machine learning
series ERES:conference
type paper session
discussion No discussions. Post discussion ...
ratings
session Doctoral session B
last changed 2017/11/18 16:20
HOMELOGIN (you are user _anon_869058 from group guest) Powered by SciX Open Publishing Services 1.002