Assessing Ecological Impacts of Urban Land Valuation: AI and Regression Models for Sustainable Land Management

The results of mass appraisal in many countries are used as a basis for calculating the amount of real estate tax, therefore, regardless of the methods used to calculate it, the resulting value should be as close as possible to the market value of the real estate to maintain a balance of interests between the state and the rights holders. In practice, this condition is not always met, since, firstly, the quality of market data is often very low, and secondly, some markets are characterized by low activity, which is expressed in a deficit of information on asking prices. The aim of the work is ecological valuation of land use: how regression-based mass appraisal can inform ecological conservation, land degradation, and sustainable land management. Four multiple regression models were constructed for AI generated map of land plots for recreational use in St. Petersburg (Russia) with different volumes of market information (32, 30, 20 and 15 units of market information with four price-forming factors). During the analysis of the quality of the models, it was revealed that the best result is shown by the model built on the maximum sample size, then the model based on 15 analogs, which proves that a larger number of analog objects does not always allow us to achieve better results, since the more analog objects there are.