Eigenvector spatial filtering (ESF) is a spatial modeling approach, which has been applied in
urban and regional studies, ecological studies, and so on. However, it is computationally …

Spatial sampling is widely used in environmental and social research. In this paper we
consider the situation where instead of a single global estimate of the mean of an attribute …

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 …

Accurate land valuation is necessary for tax purposes, land resources allocation, real estate
management and urban development and planning. Since various factors from different …

This article attempts to use spatial maps as a way of presenting additional information about
the phenomena occurring in the housing market. In our opinion, spatial maps may facilitate …

Housing mismatch becomes vital issues to studies; it happens due to inequality of housing
demand and supply in the property market. Housing mismatch has generated by various …

Participants in the land market are usually hampered to browse and analyze the land price
information due to the lack of information sources and available analysis tools. A service …

Land price mapping has recently drawn considerable attention from academics and
practitioners alike. This paper investigates the factors influencing residential land prices in a …

The increased decentralization of renewable energy has increased curtailment rates in
stagnating demand zones, increasing the levelized cost of energy (LCOE). The …

This study argues that the spatiotemporal geostatistical model for real estate prices, which
accounts for and incorporates spatial autocorrelation, can be estimated successfully using …