The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLII-3/W12-2020
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W12-2020, 87–90, 2020
https://doi.org/10.5194/isprs-archives-XLII-3-W12-2020-87-2020
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W12-2020, 87–90, 2020
https://doi.org/10.5194/isprs-archives-XLII-3-W12-2020-87-2020

  04 Nov 2020

04 Nov 2020

MAPPING THE USABILITY AND QUALITY OF BICYCLE PATHS USING A TERRAIN-INCLINATION-BASED CLASSIFICATION, STUDY CASE: DARCY RIBEIRO CAMPUS, UNIVERSITY OF BRASÍLIA, BRAZIL

A. J. d. Siqueira, P. M. d. Almo, R. E. Cicerelli, R. F. C. Machado, and T. Almeida A. J. d. Siqueira et al.
  • Instituto de Geociências, University of Brasília, 70910900, Asa Norte, Brasília, Brazil

Keywords: Bicycle path, DEM, slope, GIS, Brasilia

Abstract. Over the last decades, Brazilian cities have gone through a rapid process of urbanization. Population growth has brought the need for new technological and construction developments such as highways and housing centers. One of the most important factors related to this growth has to do with the capacity of locomotion, which is done especially by car. In Brasilia there is a large volume of cars circulating, which causes noise, air pollution, difficulty of locomotion during rush hours generated by traffic jam and stress that affects drivers and the general population. The bike stands out in this context because it is a vehicle considered clean for not polluting the environment and it is easily accessible to almost all social classes, being ideal for short to medium range routes. The University of Brasilia (UnB) has a considerable number of cyclists. The University has several bike lanes that have been built to connect the various departments along the campus. In this context, the purpose of this work is the elaboration of a slope map made from a Digital Elevation Model (DEM) to classify the bike lanes as critical or not. The DEM was made from a rectangular grid by the Anudem method and a final map in the 1 : 10000 scale was generated. The proportion of green areas and lampposts that cover the bike lanes on campus was also analyzed. The results characterize the bike lanes as non-critical in relation to the inclination, whereas the relation of number of lampposts as well as the vegetation that cover the area to the number of bike racks on campus was considered low.