ArticlePloS one2023
Pedestrian street behavior mapping using unmanned aerial vehicles. A case study in Santiago de Chile.
Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Real-Time Tracking Data and Machine Learning Approaches for Mapping Pedestrian Walking Behavior: A Case Study at the University of Moratuwa.Sensors (Basel, Switzerland) · 2024Article
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3 authors.
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Abstract
Objective observation of pedestrian behavior on the street has traditionally been difficult due to intensive commitment of time and resources with spatial analysis of pedestrian locations encountering additional problems. Recently, Unmanned Aerial Vehicles (UAVs) have gained popularity due to the significant improvements they offer over other conventional observation systems, such as their ability to cover larger surface areas in less time. This study tests the performance of UAV-based observation techniques in measuring pedestrian activity in two comparative settings in Santiago de Chile. The study develops an alternative technique adapting the behavioral mapping methodology that allows acquiring information about the people's activities and the places where they are carried out. In this study a set of streets in the city of Santiago de Chile was selected as a case study, and the reliability of those observations was tested among raters in a population sample. Further, the use of a Geographic Information System (GIS) in the data coding process is detailed and exemplified using some of its spatial analysis tools. The results show high levels of inter-rater reliability in the different categories of recorded data. Finally, we discuss the advantages and limitations in observing pedestrian behavior using this technology and observation technique.
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