Understanding the solar potential through spatial urban infrastructure analysis

Abstract

The impacts of spatial technologies in understanding realisms in infrastructure. The design, capture, analysis and integration process are discussed in order to understand the best approaches to elicit scientific outputs for policy making and decision taking. This research was based on 2018 LiDAR and orthophoto data. It is important to acknowledge that the situation on the ground may have changed since then. LiDAR and orthophoto data are typically collected at a specific point in time and may not reflect more recent changes in the landscape, such as new developments or new solar panel installations. While extracting vector data from LiDAR data can be a useful tool, there are some limitations to this process. One limitation is the accuracy of the extracted vector data, which is dependent on the quality and density of the LiDAR points. Additionally, this method is sensitive to noise and other data artifacts especially for the Maltese context. For example, on the roofs of the Maltese buildings one would find all sorts of features such as air conditioning units, water tanks, solar panels, in some instances tables / roof gardens / tents. These "features" would create polygons which would affect the quality of the extracted data and limits the proper definition of the roof extents.