The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Publications Copernicus
Articles | Volume XLII-4/W19
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4/W19, 83–87, 2019
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4/W19, 83–87, 2019

  23 Dec 2019

23 Dec 2019


K. A. Cabello1, M. A. A. Manabat1, M. B. A. Zamora1, and A. C. Blanco1,2 K. A. Cabello et al.
  • 1Department of Geodetic Engineering, University of the Philippines Diliman, Philippines
  • 2Training Center for Applied Geodesy and Photogrammetry, University of the Philippines Diliman, Philippines

Keywords: business, permutation, combination, OpenStreetMap, Network Analysis, closest facility, DEM, optimal location, GIS

Abstract. Kiosks scattered around the UP Diliman campus have always been playing a significant role in shaping the present culture in the university. However, competition is inevitable among owners. Some have even lowered their prices to attract more customers and increase sales and profits. One of the reasons why some kiosks earn more than others is because of the location of the kiosks and their distribution within the campus. In this study, accessibility, walkability and site availability are the main factors that were considered to create an ideal kiosk distribution model. First, road points within an area with 10% slope grade and below were only considered to obtain optimum gradient that requires the least energy. Road points that are within a buffer of 5 meters from waiting sheds and parking lots and 10 meters from buildings were accepted to consider the accessibility of each point. Closest Facility Tool (CFT) under Network Analysis was used to identify road points within 200 meters of each building. These points were considered as good candidate locations for kiosks. CFT was used again to identify buildings within 200 meters from each candidate point. Potential customer count (PCC) per building was reduced when a canteen is within 200 meters. Lastly, the PCC multiplied by the inverse of the distance was used as weight to identify the area that will result in equal demands of customers. Python code was used to iteratively identify the combination of road points that have relatively equal weights. A map showing all 20 current kiosks in their ideal locations and a list of landmarks surrounding each kiosk were produced. Results show that, ideally, five kiosks should be located near Palma Hall, which has the largest population count. Two kiosks should also be placed between the Law Center and Asian Center, between the Institute of Biology and the National Institute of Molecular Biology and Biotechnology, and near College of Arts and Letters, Institute of Electrical and Electronics Engineering (IEEE) and College of Human Kinetics (CHK). Finally, only one kiosk each should be placed near buildings such as Melchor Hall, the National Institute of Physics (NIP), the National Institute of Geological Sciences (NIGS), the Institute of Civil Engineering (ICE) and Albert Hall.