A comparative study of land price estimation and mapping using regression kriging and machine learning algorithms across Fukushima prefecture,Japan

Finding accurate methods for estimating and mapping land prices at the macro-scale based on publicly accessible and low-cost spatial data is an essential step in producing a meaningful reference for regional planners.This asset would assist them in making economically justified decisions in favor of key investors for development projects and post-disaster recovery efforts.Since 2005,the Ministry of Land,Infrastructure,and Transport of Japan has made land price data open to the public in the form of observations at dispersed locations.Although this data is useful,it does not provide complete information at every site for all market participants.Therefore,estimating and mapping land prices based on sound statistical theories is required.This paper presents a comparative study of spatial prediction of land prices in 2015 in Fukushima prefecture based on geostatistical methods and machine learning algorithms.Land use,elevation,and socioeconomic factors,including population density and distance to railway stations,were used for modeling.Results show the superiority of the random forest algorithm.Overall,land prices are distributed unevenly across the prefecture with the most expensive land located in the western region characterized by flat topography and the availability of well-connected and highly dense economic hotspots.

Characteristics of neighborhood interaction in urban land-use changes： A comparative study between three metropolitan areas of Japan

Local spatial interaction between neighborhood land-use categories （i.e. neighborhood interaction） is an important factor which affects urban land-use change patterns. Therefore,it is a key component in cellular automata （CA）-based urban geosimulation models towards the simulation and forecast of urban land-use changes. Purpose of this paper is to interpret the similarities and differences of the characteristics of neighborhood interaction in urban land-use changes of different metropolitan areas in Japan for providing empirical materials to understand the mechanism of urban land-use changes and construct urban geosimulation models. Characteristics of neighborhood interaction in urban land-use changes of three metropolitan areas in Japan,i.e. Tokyo,Osaka,and Nagoya,were compared using such aids as the neighborhood interaction model and similarity measure function. As a result,urban land-use in the three metropolitan areas was found to have had similar structure and patterns during the study period. Characteristics of neighborhood interaction in urban land-use changes are quite different from land-use categories,meaning that the mechanism of urban land-use changes comparatively differs among land-use categories. Characteristics of neighborhood interaction reveal the effect of spatial autocorrelation in the spatial process of urban land-use changes in the three metropolitan areas,which correspond with the characteristics of agglomeration of urban land-use allocation in Japan. Neighborhood interaction amidst urban land-use changes between the three metropolitan areas generally showed similar characteristics. The regressed neighborhood interaction coefficients in the models may represent the general characteristics of neighborhood effect on urban land-use changes in the cities of Japan. The results provide very significant materials for exploring the mechanism of urban land-use changes and the construction of universal urban geosimulation models which may be applied to any city in Japan.