Applying Multivariate Data Analysis as Objective Method for Calculating the Location Index for Use in Urban Tree Appraisal

Abstract

The urban canopy is a very valuable element in cities, and its environmental benefits are significant. It is very important for cities to assess adequately their canopy. An important part of its value is related to the tree number density according to the population density. The most commonly used methods for tree appraisal use subjective means to obtain the influence of location. A new methodology is developed in this work to obtain an objective location index. The proposed index gives a value to the tree according to its location in the city. A multiple regression model (function of the canopy density per inhabitant and the urban area percentage) is used to calculate the location index. The index has been calculated for the neighborhoods of the city of Santiago del Estero, Argentina, but can be applied to any city with objective variables, available from any local administration.