Estimation of the Setting and Infrastructure Criterion of the UI GreenMetric Ranking Using Unmanned Aerial Vehicles

Abstract

This study presents a methodology to estimate the seven indicators of the Setting and Infrastructure criterion of the UI GreenMetric World University Ranking based on three-dimensional data from a point cloud taken from an unmanned aerial vehicle (UAV). This study also estimated the potential aerial biomass, C and CO2, stored in the green spaces of a university campus using photogrammetric data analyzed in a Geographic Information System (GIS). The method was based on isolating classified point clouds using digital surface models (DSMs) and ground control points (GCPs) considering the canopy height model (CHM), the allometric equation (DBH, p, h), the biomass conversion factor, and carbon dioxide equivalents (CO2-e). The results confirmed that the national models for estimating the potential C reserves in natural forests are very close to reality and that the open space and green areas available to people on campus are adequate. The use of photogrammetric data facilitated the estimation of UI GreenMetric indicators from a highly detailed, low-cost three-dimensional model. The results of a case study revealed that the campus assimilates the CO2 emissions it produces and generates a surplus.