Digital Exclusion of Favelas from the Solar Map of Rio de Janeiro

Feitosa, Paulo Henrique Assis; Lima, Alberto Jorge Silva de; Cukierman, Henrique Luiz

doi:10.1109/mts.2020.2967491

Cited by 1 publication

(1 citation statement)

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“…It must be noted that the lack of (geospatial) information in those areas represents an additional challenge in understanding the urban processes that take place, as such informal settlements are, for many application domains, a sort of "terra incognita". For example, in the case of the solar cadastre of Rio de Janeiro, all favelas have not been considered and eventually left out of the solar map (Feitosa et al, 2020). Therefore, knowing which tools to use, their data requirements, and their overall accuracy (also without the availability of a reference station nearby for calibration) play a major role when dealing with these urban areas.…”

Section: Introductionmentioning

confidence: 99%

Comparison and Evaluation of Different Gis Software Tools to Estimate Solar Irradiation

Giannelli

León-Sánchez

Agugiaro

2022

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. In this paper, five commonly used software tools to estimate solar radiation in the urban context (GRASS GIS, ArcGIS, SimStadt, CitySim and Ladybug) are run on the same test site and are compared in terms of input data requirements, usability, and accuracy of the results. Spatial and weather data have been collected for an area located in the Brazilian city of São Paulo, in the district of Santana. The test area surrounds a weather station, for which meteorological data of the last 15 years have been collected and used as ground truth when analysing and comparing the simulation results. In terms of spatial data, raster- and vector-based models of the study area have been generated in order to comply with the different input requirements. More specifically, in the case of the vector-based tools (SimStadt, CitySim and Ladybug), a common 3D model based on CityGML and containing buildings, vegetation (trees) and terrain has been generated and used as a common urban model. The paper presents the findings and discusses the results not only from a numerical point of view, but also from the perspective of the overall usability of the software in terms of data requirements, simulation time and task automatisation.

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Section: Introductionmentioning

confidence: 99%