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Predicting the variability in pedestrian travel rates and times using crowdsourced GPS data / Michael J. Campbell in Computers, Environment and Urban Systems, vol 97 (October 2022)  

Public [article]  inComputers, Environment and Urban Systems > vol 97 (October 2022) . - n° 101866 Titre : Predicting the variability in pedestrian travel rates and times using crowdsourced GPS data Type de document : Article/Communication Auteurs : Michael J. Campbell, Auteur ; Philip E. Dennison, Auteur ; Matthew Thompson, Auteur Année de publication : 2022 Article en page(s) : n° 101866 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] base de données localisées [Termes IGN] Californie (Etats-Unis) [Termes IGN] chemin le moins coûteux, algorithme du [Termes IGN] données issues des réseaux sociaux [Termes IGN] durée de trajet [Termes IGN] mobilité urbaine [Termes IGN] navigation pédestre [Termes IGN] pente [Termes IGN] planification urbaine [Termes IGN] trace GPS [Termes IGN] Utah (Etas-Unis) Résumé : (auteur) Accurately predicting pedestrian travel times is critically valuable in emergency response, wildland firefighting, disaster management, law enforcement, and urban planning. However, the relationship between pedestrian movement and landscape conditions is highly variable between individuals, making it difficult to estimate how long it will take broad populations to get from one location to another on foot. Although functions exist for predicting travel rates, they typically oversimplify the inherent variability of pedestrian travel by assuming the effects of landscapes on movement are universal. In this study, we present an approach for predicting the variability in pedestrian travel rates and times using a large, crowdsourced database of GPS tracks. Acquired from the outdoor recreation website AllTrails, these tracks represent nearly 2000 hikes on a diverse range of trails in Utah and California, USA. We model travel rates as a function of the slope of the terrain by generating a series of non-linear percentile models from the 2.5 th to the 97.5 th by 2.5 percentiles. The 50 th percentile model, representing the hiking speed of the typical individual, demonstrates marked improvement over existing slope-travel rate functions when compared to an independent test dataset. Our results demonstrate novel capacity to estimate travel time variability, with modeled percentiles being able to predict actual percentiles with less than 10% error. Travel rate functions can also be applied to least cost path analysis to provide variability in travel times. Numéro de notice : A2022-599 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.compenvurbsys.2022.101866 Date de publication en ligne : 20/08/2022 En ligne : https://doi.org/10.1016/j.compenvurbsys.2022.101866 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101452 [article]

Safe separation distance score : a new metric for evaluating wildland firefighter safety zones using lidar / Michael J. Campbell in International journal of geographical information science IJGIS, vol 31 n° 7-8 (July - August 2017)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 31 n° 7-8 (July - August 2017) . - pp 1448 - 1466 Titre : Safe separation distance score : a new metric for evaluating wildland firefighter safety zones using lidar Type de document : Article/Communication Auteurs : Michael J. Campbell, Auteur ; Philip E. Dennison, Auteur ; Bret W. Butler, Auteur Année de publication : 2017 Article en page(s) : pp 1448 - 1466 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] Californie (Etats-Unis) [Termes IGN] carte thématique [Termes IGN] distance euclidienne [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] hauteur des arbres [Termes IGN] incendie de forêt [Termes IGN] protection civile [Termes IGN] topographie locale [Termes IGN] zone tampon Résumé : (Ateur) Safety zones are areas where firefighters can retreat to in order to avoid bodily harm when threatened by burnover or entrapment from wildland fire. At present, safety zones are primarily designated by firefighting personnel as part of daily fire management activities. Though critical to safety zone assessment, the effectiveness of this approach is inherently limited by the individual firefighter’s or crew boss’s ability to accurately and consistently interpret vegetation conditions, topography, and spatial characteristics of potential safety zones (e.g. area and geometry of a forest clearing). In order to facilitate the safety zone identification and characterization process, this study introduces a new metric for safety zone evaluation: the Safe Separation Distance Score (SSDS). The SSDS is a numerical representation of the relative suitability of a given area as a safety zone according to its size, geometry, and surrounding vegetation height. This paper describes an algorithm for calculating pixel-based and polygon-based SSDS from lidar data. SSDS is calculated for every potential safety zone within a lidar dataset covering Tahoe National Forest, California, USA. A total of 2367 potential safety zones with an SSDS ≥1 were mapped, representing areas that are suitable for fires burning in low wind and low slope conditions. The highest SSDS calculated within the study area was 9.65, a score that represents suitability in the highest wind-steepest slope conditions. Potential safety zones were clustered in space, with areas in the northern and eastern portions of the National Forest containing an abundance of safety zones while areas to the south and west were completely devoid of them. SSDS can be calculated for potential safety zones in advance of firefighting, and can allow firefighters to carefully compare and select safety zones based on their location, terrain, and wind conditions. This technique shows promise as a standard method for objectively identifying and ranking safety zones on a spatial basis. Numéro de notice : A2017-308 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2016.1270453 En ligne : http://dx.doi.org/10.1080/13658816.2016.1270453 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85355 [article]

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