Modeling the Spatial Characteristics of City Parks Based on Geographically Weighted Regression (GWR) Analysis Using Coefficients of General Performance of Park (GPP) and Area of Supply and Demand (ASD) (Case Study: First Region of Tehran)

The spatial weighted regression method is one of the best methods to achieve higher accuracy in analyzing space-affected relations. This article attempts to introduce a model of the results of Area of Supply and Demand and general park performance with a spatially weighted regression model for evaluating parks in Region 1 of Tehran. The density of parks and population density in Region 1 of Tehran with the help of some environmental variables-space such as the area of parks. To follow the theoretical framework, spatial distribution and urban green space efficiency indices were used. With their help, environmental-spatial variables have been extracted, and the required data have been collected through systematic scientific methods and turned into information in determining the relationship between the data. Based on the findings, it is expected that this indicator will help landscape planners to understand the supply and demand index of parks and their relationship with the general efficiency of parks. It can help planners reconsider their projects' policies, goals, and costs. The results show that the general performance development index of parks in the first Region of Tehran is not commensurate with their supply and demand. In some areas, parks with appropriate performance indexes have low demand. Predictions of this research show that parks with index (-0.5>StdError) value will need more demand in the future, and demand for parks with index (StdError>2.5) will decrease.