2026-10-26

7 arXiv categories· 96 journals· 2709 candidates — 4 worth your time· 93 without an open abstract

Headline

National-scale multimodal accessibility fields generated from OpenStreetMap and GTFS data

Today, together

tag shift
no tag ran above its 30-day average
on the same shoulders
8 of the day's papers cite Travel and the Built Environment (Reid Ewing, Robert Cervero 2010); 4 cite Accessibility evaluation of land-use and transport strategies: review and research directions (Karst Geurs, Bert van Wee 2003); 4 cite Travel demand and the 3Ds: Density, diversity, and design (Robert Cervero, Kara M. Kockelman 1997) counted over the 89 of this day's 97 named papers whose reference lists we have — standing on the same older work is not the same as being about the same thing
first appearance
no institution here was new to the last 136 days none of them on a paper we published in the 136 days before this issue

Two counts, not one counted twice: every row here but “on the same shoulders” counts the papers published above, and that one counts every paper this day named — those and the ones under Also published today, whose abstracts we could not read.

National-Scale Multimodal Accessibility Fields from Open Geospatial Data introduces MAPPER, an open-data C++/OpenMP pipeline that processes OpenStreetMap and GTFS data with network kernel density estimation to build continuous travel-time fields for walking, biking, driving, and public transit. Evaluated near Cusco, Peru, A political ecology of reforestation in the Peruvian Andes examines how institutional dynamics and tree species choices influence tree-planting initiatives through a political ecology framework. Changing contribution of a shared neighbourhood pattern to reported sexual and non-sexual violence against women and girls in Medellín, Colombia, 2018--2022 applies a Bayesian shared-component model to 46,390 reported cases across 285 neighbourhoods to track spatial violence patterns.

datapreprint

Till Zacher, Louis Stille-Hönig, Markus Lienkamp
arXiv cs.CY

openstreetmap · points of interest

National-Scale Multimodal Accessibility Fields from Open Geospatial Data

MAPPER is an open-data, C++/OpenMP-powered pipeline that builds walk, bike, car, and public transport travel-time graphs from OpenStreetMap and GTFS data to generate continuous accessibility fields using network kernel density estimation. A full-country deployment across Germany generated an H3-indexed grid dataset containing nearly 40 million cells and 972 mode-layer fields spanning nine intermodal and network modes. Validation against an empirical mobility panel confirmed low mean bias for road and active travel, while public transit outputs serve as schedule-based supply estimates.

Why it matters — Researchers can now run continent- or national-scale multimodal accessibility models combining custom opportunity layers on standard commodity hardware without specialized computing infrastructure.

Caveat: Public transit travel times rely on schedule supply models rather than observed trips, making them sensitive to default transfer and waiting time parameters.

arXiv · pdf

published: GeoJournal

James R. Keese, Milagro Montufar Paz, Danielle Gerger, et al.
GeoJournal

California Polytechnic State University

Conservation, Biodiversity, and Resource Management · Forest Ecology and Conservation · Social Sciences and Humanities · interview · California Polytechnic State University · George Washington University

A political ecology of reforestation in the Peruvian Andes: a field study of tree species and institutional dynamics

Through a political ecology framework, this field study evaluated the institutional and species-choice dynamics of tree planting initiatives near Cusco, Peru. The authors gathered qualitative field data by interviewing stakeholders across three levels of the Peruvian government, two environmental non-profits, timber-related businesses, and members of an Indigenous agricultural community actively engaged in local tree planting. Findings reveal persistent institutional tensions between ecological restoration objectives—such as planting native species—and economic livelihood priorities that favor fast-growing exotic species like eucalyptus and pine.

Why it matters — The study demonstrates that top-down reforestation goals fail without community-led governance structures that reconcile economic livelihood needs with ecological conservation.

Caveat: Findings rely on qualitative interviews and a single regional case study in the Andean highlands near Cusco, limiting direct generalization to other geographic regions.

GeoJournal · pdf · doi

preprint

Tomás Rodríguez-Taborda, Alejandra-Estefanía Patiño-Hoyos, Simón Ruiz-Martínez, et al.
arXiv stat.AP

spatial analysis

Changing contribution of a shared neighbourhood pattern to reported sexual and non-sexual violence against women and girls in Medellín, Colombia, 2018--2022

Using a Bayesian shared-component model, this study analyzed 46,390 reported cases of violence against women and girls across 285 neighbourhoods in Medellín, Colombia, from 2018 to 2022. During pandemic restrictions, the influence of a shared neighbourhood spatial field—which correlated with poorer living conditions—increased by 0.26 for non-sexual violence and 0.23 for sexual violence, widening the risk ratio gap between high- and low-risk areas by over 30%. By 2022, the spatial loading for non-sexual violence remained 0.19 above pre-pandemic baselines, while sexual violence returned near historical levels.

Why it matters — It demonstrates that urban spatial inequalities in gender-based violence intensified during pandemic lockdowns and sustained persistent, elevated risks for non-sexual domestic violence even after restrictions lifted.

Caveat: The findings rely on public-health surveillance notifications, which reflect reported incidents rather than total actual prevalence.

arXiv · pdf

preprint

Muhammad Adil Abid, Johan Holmgren, Fabian Lorig, et al.
arXiv cs.LG

machine learning

Beyond Heuristics and Commercial Navigation: An AI-Augmented Decision-Support for Ambulance Travel Time Estimation

Analysis of historical emergency trips in Skåne, Sweden, shows that ambulance travel duration varies significantly by priority level, time of day, and day of the week, causing commercial navigation platforms to produce systematically inaccurate estimates. To resolve this, a machine learning model was developed and evaluated alongside SHAP and permutation importance interpretability tools to capture emergency routing dynamics.

Why it matters — Dispatchers can replace unvalidated assumptions, like fixed 5% speed advantages over standard passenger traffic, with predictive software grounded in actual emergency operations data.

Caveat: The predictive system was trained and evaluated solely on historical emergency vehicle data from a single Swedish region.

arXiv · pdf

Also published today

These appeared today in journals we track. Their abstracts are not openly available, so we cannot summarise them.

Status changes