Publicacións

@article{fernandez-arango_methodology_2024,

title = {Methodology for Identifying Optimal Pedestrian Paths in an Urban Environment: A Case Study of a School Environment in A Coruña, Spain},

author = {David Fernández-Arango and Francisco Alberto Varela-García and Alberto M. Esmorís},

url = {https://www.mdpi.com/2624-6511/7/3/60},

doi = {10.3390/smartcities7030060},

issn = {2624-6511},

year  = {2024},

date = {2024-06-01},

urldate = {2026-04-21},

journal = {Smart Cities},

volume = {7},

number = {3},

pages = {1441–1461},

publisher = {Multidisciplinary Digital Publishing Institute},

abstract = {Improving urban mobility, especially pedestrian mobility, is a current challenge in virtually every city worldwide. To calculate the least-cost paths and safer, more efficient routes, it is necessary to understand the geometry of streets and their various elements accurately. In this study, we propose a semi-automatic methodology to assess the capacity of urban spaces to enable adequate pedestrian mobility. We employ various data sources, but primarily point clouds obtained through a mobile laser scanner (MLS), which provide a wealth of highly detailed information about the geometry of street elements. Our method allows us to characterize preferred pedestrian-traffic zones by segmenting crosswalks, delineating sidewalks, and identifying obstacles and impediments to walking in urban routes. Subsequently, we generate different displacement cost surfaces and identify the least-cost origin–destination paths. All these factors enable a detailed pedestrian mobility analysis, yielding results on a raster with a ground sampling distance (GSD) of 10 cm/pix. The method is validated through its application in a case study analyzing pedestrian mobility around an educational center in a purely urban area of A Coruña (Galicia, Spain). The segmentation model successfully identified all pedestrian crossings in the study area without false positives. Additionally, obstacle segmentation effectively identified urban elements and parked vehicles, providing crucial information to generate precise friction surfaces reflecting real environmental conditions. Furthermore, the generation of cumulative displacement cost surfaces allowed for identifying optimal routes for pedestrian movement, considering the presence of obstacles and the availability of traversable spaces. These surfaces provided a detailed representation of pedestrian mobility, highlighting significant variations in travel times, especially in areas with high obstacle density, where differences of up to 15% were observed. These results underscore the importance of considering obstacles’ existence and location when planning pedestrian routes, which can significantly influence travel times and route selection. We consider the capability to generate accurate cumulative cost surfaces to be a significant advantage, as it enables urban planners and local authorities to make informed decisions regarding the improvement of pedestrian infrastructure.},

keywords = {cumulative cost, least-cost path, pedestrian, pedestrian mobility, pedestrian path, school mobility, school route, urban mobility, walkability},

pubstate = {published},

tppubtype = {article}

}

@article{fernandez-arango_dynamic_2023,

title = {Dynamic Analysis of School Mobility Using Geolocation Web Technologies},

author = {David Fernández-Arango and Francisco Alberto Varela-García and Jorge López-Fernández},

url = {https://www.mdpi.com/2220-9964/12/1/8},

doi = {10.3390/ijgi12010008},

issn = {2220-9964},

year  = {2023},

date = {2023-01-01},

urldate = {2026-08-11},

journal = {ISPRS International Journal of Geo-Information},

volume = {12},

number = {1},

pages = {8},

abstract = {Pedestrian travel represents one of the most complex forms of mobility owing to the numerous parameters that influence its analysis and the difficulty of acquiring accurate travel information. In addition, the vulnerability of its protagonists, especially in urban environments, in coexistence with other types of transport, makes its study interesting. This paper proposes a web tool for use in geolocated surveys that allows the acquisition of georeferenced thematic information of interest for mobility studies. The analysis of different school routes from students’ homes to their respective schools has been proposed as a case study. This work covered a sample of 1883 students from 26 schools in Galicia (Spain), where population dispersion generates a particular type of mobility. We obtained relevant mobility data, such as the routes most traveled by students in their daily commute to school, the most efficient routes, the most used means of transport, or the exact location of various elements that hinder and dangerously affect students traveling these routes, such as sidewalks or crosswalks in poor condition, among others.},

note = {Publisher: Multidisciplinary Digital Publishing Institute},

keywords = {geolocated surveys, pedestrian, pedestrian mobility, pedestrian paths, school mobility, school routes, urban mobility},

pubstate = {published},

tppubtype = {article}

}

@article{montero-lamas_analysis_2022,

title = {Analysis of the Relationship between the Characteristics of the Areas of Influence of Bus Stops and the Decrease in Ridership during COVID-19 Lockdowns},

author = {Yaiza Montero-Lamas and Alfonso Orro-Arcay and Margarita Novales-Ordax and Francisco Alberto Varela-García},

url = {https://www.mdpi.com/2071-1050/14/7/4248},

doi = {10.3390/su14074248},

issn = {2071-1050},

year  = {2022},

date = {2022-01-01},

urldate = {2026-08-11},

journal = {Sustainability},

volume = {14},

number = {7},

pages = {4248},

abstract = {This study aimed to investigate the relationship between the characteristics of the areas of influence of bus stops and the decrease in ridership during COVID-19 lockdowns and subsequent initial reopening processes. A novel GIS methodology was developed to determine these characteristics from a large amount of data with high spatial detail and accurately assign them to individual bus stops. After processing the data, several multiple linear regression models were developed to determine the variables related to different activities and changes in mobility during lockdown that may explain the variation in demand owing to the COVID-19 pandemic. The characteristics related to population and land use were also studied. The proposed methodology can be used to improve transit planning during exceptional situations, by strengthening public transport in areas with a predictably higher transit demand, instead of uniformly decreasing the availability of public transport services, promoting sustainable mobility. The efficiency of the proposed methodology was shown by performing a case study that analysed the variation in bus demand in A Coruña, Spain. The areas with the highest sustained demand were those with low inhabitant incomes, a high population density, and significant proportions of land use dedicated to hospitals, offices, or supermarkets.},

note = {Publisher: Multidisciplinary Digital Publishing Institute},

keywords = {bus stop patronage, COVID-19, GIS, land use, Transit planning, urban mobility},

pubstate = {published},

tppubtype = {article}

}

@article{fernandez-arango_automatic_2022,

title = {Automatic Generation of Urban Road 3D Models for Pedestrian Studies from LiDAR Data},

author = {David Fernández-Arango and Francisco Alberto Varela-García and Diego González-Aguilera and Susana Lagüela-López},

url = {https://www.mdpi.com/2072-4292/14/5/1102},

doi = {10.3390/rs14051102},

issn = {2072-4292},

year  = {2022},

date = {2022-01-01},

urldate = {2026-08-11},

journal = {Remote Sensing},

volume = {14},

number = {5},

pages = {1102},

abstract = {The point clouds acquired with a mobile LiDAR scanner (MLS) have high density and accuracy, which allows one to identify different elements of the road in them, as can be found in many scientific references, especially in the last decade. This study presents a methodology to characterize the urban space available for walking, by segmenting point clouds from data acquired with MLS and automatically generating impedance surfaces to be used in pedestrian accessibility studies. Common problems in the automatic segmentation of the LiDAR point cloud were corrected, achieving a very accurate segmentation of the points belonging to the ground. In addition, problems caused by occlusions caused mainly by parked vehicles and that prevent the availability of LiDAR points in spaces normally intended for pedestrian circulation, such as sidewalks, were solved in the proposed methodology. The innovation of this method lies, therefore, in the high definition of the generated 3D model of the pedestrian space to model pedestrian mobility, which allowed us to apply it in the search for shorter and safer pedestrian paths between the homes and schools of students in urban areas within the Big-Geomove project. Both the developed algorithms and the LiDAR data used are freely licensed for their use in further research.},

note = {Publisher: Multidisciplinary Digital Publishing Institute},

keywords = {LiDAR point cloud, mobile LiDAR system, pedestrian accessibility, point cloud segmentation, urban mobility, urban road},

pubstate = {published},

tppubtype = {article}

}

@article{orro_impact_2020,

title = {Impact on City Bus Transit Services of the COVID–19 Lockdown and Return to the New Normal: The Case of A Coruña (Spain)},

author = {Alfonso Orro-Arcay and Margarita Novales-Ordax and Ángel Monteagudo and José-Benito Pérez-López and Miguel D. Rodríguez-Bugarín},

url = {https://www.mdpi.com/2071-1050/12/17/7206},

doi = {10.3390/su12177206},

issn = {2071-1050},

year  = {2020},

date = {2020-01-01},

urldate = {2026-08-06},

journal = {Sustainability},

volume = {12},

number = {17},

pages = {7206},

publisher = {Multidisciplinary Digital Publishing Institute},

abstract = {The COVID–19 pandemic led to restrictions on activities and mobility in many parts of the world. After the main peak of the crisis, restrictions were gradually removed, returning to a new normal situation. This process has impacted urban mobility. The limited information on the new normal situation shows changes that can be permanent or reversible. The impact on the diverse urban transport modes varies. This study analyzes the changes in transit ridership by line, the use of stops, the main origin–destination flows, changes in transit supply, operation time, and reliability of the city bus network of A Coruña. It is based on data from automatic vehicle location, bus stop boarding, and smart card use. Data from the first half of 2020 were compared to similar data in 2017–2019, defining suitable baselines for each analysis to avoid seasonal and day of week effects. The impact on transit ridership during the lockdown process was more significant than that on general traffic. In the new normal situation, the general traffic and the shared bike system recovered a higher percentage of their previous use than the bus system. These impacts are not uniform across the bus network.},

keywords = {COVID–19, sustainable modes, transit demand, transit supply, urban mobility},

pubstate = {published},

tppubtype = {article}

}