A Method for Determining the Affected Areas of High-Alpine Mountain Trails

High-mountain areas with sensitive ecosystems are experiencing a steady increase in visitation, with visitors progressively moving outside designated trails, generating pressures on the natural environment. In extensive areas with numerous access points, it is difficult to monitor visitors’ movement and resulting impacts. This article describes a method for combining various data sources and approaches to determine affected areas, including their locations and extent. The method combines (1) field-mapping, (2) remote-sensing data display analysis, and (3) processing of publicly available GNSS tracks from sports applications, using 46 test plots along a selected trail to Mount Triglav in Slovenia. Affected-area surfaces and their spatial overlap were compared across the three approaches. The usefulness of remote-sensing displays and GNSS tracks for determining and predicting affected areas was assessed by reference to field measurements. A linear regression model showed that the display-analysis approach can explain 52.7% of the variability in field-mapping approach, while GNSS tracks do not provide enough information nor the accuracy comparable to field surveys. This study can help other researchers and nature-protection managers in selecting most suitable data derived from non-traditional sources to improve delineation of hiking trails and estimation of potential pressures on fragile environments.

Authors

Institutions

Publication Details

Journal
Land
Published
2026-01-22
DOI
https://doi.org/10.3390/land15010200
Primary Topic
Recreation, Leisure, Wilderness Management
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Method for Determining the Affected Areas of High-Alpine Mountain Trails

Mojca Golobiĉ, Žiga Malek, D. Kastelec, Andrej Bašelj et al.
Land
Recreation, Leisure, Wilderness Management
article

A Method for Determining the Affected Areas of High-Alpine Mountain Trails

Mojca Golobiĉ, Žiga Malek, D. Kastelec, Andrej Bašelj, Žiga Kokalj
article en

Abstract

High-mountain areas with sensitive ecosystems are experiencing a steady increase in visitation, with visitors progressively moving outside designated trails, generating pressures on the natural environment. In extensive areas with numerous access points, it is difficult to monitor visitors’ movement and resulting impacts. This article describes a method for combining various data sources and approaches to determine affected areas, including their locations and extent. The method combines (1) field-mapping, (2) remote-sensing data display analysis, and (3) processing of publicly available GNSS tracks from sports applications, using 46 test plots along a selected trail to Mount Triglav in Slovenia. Affected-area surfaces and their spatial overlap were compared across the three approaches. The usefulness of remote-sensing displays and GNSS tracks for determining and predicting affected areas was assessed by reference to field measurements. A linear regression model showed that the display-analysis approach can explain 52.7% of the variability in field-mapping approach, while GNSS tracks do not provide enough information nor the accuracy comparable to field surveys. This study can help other researchers and nature-protection managers in selecting most suitable data derived from non-traditional sources to improve delineation of hiking trails and estimation of potential pressures on fragile environments.

LandVol. 15(1)
International Institute for Applied Systems Analysis (AT), University of Ljubljana (SI), Slovenian Academy of Sciences and Arts (SI)
Life in Land
Openalex Percentile: Top 83%
Recreation, Leisure, Wilderness Management
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.