Evidence map›Paper›PMID 42655453›Full record

ArticleSensors (Basel, Switzerland)2026

Potential of Mobile LiDAR Sensors in Hiking Trail Management.

Rui Fernandes, Alberto Gomes, Borja Moya-Gomez, Nelson Mileu

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Rui FernandesCentre of Studies in Geography and Spatial Planning, University of Porto, 4150-564 Porto, Portugal.ORCID 0000-0003-2832-1589
Alberto GomesCentre of Studies in Geography and Spatial Planning, University of Porto, 4150-564 Porto, Portugal.ORCID 0000-0002-1764-0659
Borja Moya-GomezTransport, Infrastructure and Territory Research Group (tGIS), Department of Geography, Complutense University of Madrid, 28040 Madrid, Spain.ORCID 0000-0002-0520-039X
Nelson MileuInstitute of Geography and Spatial Planning, University of Lisbon, 1600-276 Lisbon, Portugal.ORCID 0000-0002-6677-0425

Funding

Foundation for Science and Technology 2023.00993.BD
6 · The paper itself

Abstract

The LiDAR sensor embedded in recent iPhone Pro devices offers new opportunities for rapid, low-cost, and spatially detailed assessment of outdoor recreational infrastructure. Framed within mobile sensing and IoT-based environmental monitoring, this proof-of-concept case study evaluates a smartphone-based LiDAR workflow for localized hiking trail assessment under dense canopy conditions. Four independent surveys of a degraded hiking trail section were conducted to assess inter-survey repeatability, agreement with conventional field measurements, and practical field applicability. The resulting three-dimensional models reproduced trail morphology, including incised tread sections, exposed roots, rocky surfaces, and localized irregularities relevant to trail-condition assessment. Repeated registrations demonstrated consistent cloud-to-cloud comparison metrics, while comparisons with field reference measurements showed good agreement in the representation of cross-sectional morphology and exposed root characteristics. Continuous surface reconstruction additionally supported exploratory identification of potential runoff pathways and relative surface depressions. Although limited to a single trail section and one smartphone-application combination (iPhone 13 Pro with Scaniverse), the evaluated workflow demonstrates potential as a rapid, accessible, and relatively low-cost approach for localized trail-condition assessment and provides a foundation for further evaluation in hiking trail monitoring.

Indexed as

hiking trailsmobile LiDARsmartphonestrail degradationtrail monitoring

Identifiers

PMID42655453
PMCPMC13517338

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.