Smart City Gnosys

Smart city article details

Title Usage Of Airborne Lidar Data And High-Resolution Remote Sensing Images In Implementing The Smart City Concept
ID_Doc 60323
Authors Uciechowska-Grakowicz A.; Herrera-Granados O.; Biernat S.; Bac-Bronowicz J.
Year 2023
Published Remote Sensing, 15, 24
DOI http://dx.doi.org/10.3390/rs15245776
Abstract The cities of the future should not only be smart, but also smart green, for the well-being of their inhabitants, the biodiversity of their ecosystems and for greater resilience to climate change. In a smart green city, the location of urban green spaces should be based on an analysis of the ecosystem services they provide. Therefore, it is necessary to develop appropriate information technology tools that process data from different sources to support the decision-making process by analysing ecosystem services. This article presents the methodology used to develop an urban green space planning tool, including its main challenges and solutions. Based on the integration of data from ALS, CLMS, topographic data, and orthoimagery, an urban green cover model and a 3D tree model were generated to complement a smart-city model with comprehensive statistics. The applied computational algorithms allow for reports on canopy volume, CO (Formula presented.) reduction, air pollutants, the effect of greenery on average temperature, interception, precipitation absorption, and changes in biomass. Furthermore, the tool can be used to analyse potential opportunities to modify the location of urban green spaces and their impact on ecosystem services. It can also assist urban planners in their decision-making process. © 2023 by the authors.
Author Keywords data integration; ecosystem services; remote sensing; smart city; smart urban forest; tree models; trunk detection; urban green spaces


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