Methodology for Green and Built Volume Analysis

Abstract

Today, in some Brazilian cities, there is the possibility of using high-resolution data and automated classification based on spectral bands. Thus, this article aims to evaluate the association of the NDVI(normalized difference vegetation index) to the use of LiDAR, in order to analyze urban vegetation cover and the changes of the local landscapes. It was observed that the association of the high spatial resolution of an aerophotogrammetric image to the spectral response in the near infrared range allowed the vegetation to be identified. This enabled the documentation, visualization and analysis of a location's phenomenon, facilitating the investigation of spatial relationships through representation by maps, charts, especially for simulating possible spatial scenarios and thus permitting the evaluation of interventions and predictions to be made, assisting projects or proposed laws and urban parameters.

ESDA (Exploratory Spatial Data Analysis) of Vegetation Cover in Urban Areas—Recognition of Vulnerabilities for the Management of Resources in Urban Green Infrastructure

“…In the territorial units' decision, green vegetation was characterized by the footprint of the arborous body, the fragment projected in the surface but associated with the values about the volume (data captured from LIDAR and elaborated into volume values). With specific studies that we had done before, in which we were analyzing life quality, the values were grouped by blocks [23,30]. The ideal condition was to transform all the variables in distribution per block but in Brazil, socioeconomic data are available only per census sectors, which forced us to work with this territorial unit and to summarize the data from vegetation cover into the census sector unit (that covers many blocks but does not cut a block in the middle, because it respects the limits of the roads).…”

“…Applying Zonal Statistics analysis, it was possible to get the Majority and the Range of the elevation values per shape of robust vegetation. The Range was used to control the difference from the lowest to the highest point of the plot element but the Majority value was used to calculate the volume of the vegetation (doing the multiplication of the area of the plot projection by the majority value in the height) [23,30].…”

“…There are still few studies that approach three-dimensional studies applied to urban vegetation cover, especially using LiDAR (Light Detection and Ranging) associated with the NDVI (Normalized Difference Vegetation Index), in order to support the comparison between built and vegetation volumes to evaluate urban environmental quality [1,22,23].…”