Mass appraisal of urban land value using artificial intelligence. The case of San Francisco city, Córdoba, Argentina.
Keywords:
Land value, Mass appraisal, Machine Learning, Random Forest, Ordinary KrigingAbstract
The real estate market plays an important role in the economy and society, therefore, the downgrading of cadastral valuations, particularly urban land, has harmful effects on tax, territorial and housing public policies, property market, as in the stability of the finance system. For this reason, the cadastres face the challenge of developing massive valuations of a jurisdiction in order to provide updated and quality data, quickly and efficiently. Given the technological advance, the generation of large volumes of information and the progress associated with computer science, the ideas of massive appraisal of real estate by the catastres is increasingly taking hold. Under these needs and new situation, the results reflects the advantage of the predictive capacity in estimating the value of urban land by applying an algorithmic technique of machine learning, known as Random Forest, in combination with a geo-statistical technique called Ordinary Kriging for the treatment of error.
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