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Title:Fractal dimension of linear network segments: experiments on hiking trails
Authors:ID Prah, Klemen (Author)
ID Shortridge, Ashton (Author)
Files:.pdf RAZ_Prah_Klemen_2026.pdf (293,18 KB)
MD5: 32D2348D5EB297DC969E2869A208E2B6
 
URL https://doi.org/10.5281/zenodo.20407690
 
Language:English
Work type:Other
Typology:1.08 - Published Scientific Conference Contribution
Organization:FL - Faculty of Logistic
Abstract:Complex terrestrial linear networks like roads, rivers, and hiking trails have different degrees of spatial variation in different environments and across different geographic scales. Fractal dimension is a longstanding conceptual approach to characterizing such spatial variation over multiple scales, and a number of algorithms have been developed to calculate fractal dimension of a linear feature. In this paper, we develop, implement, and test a variant of the widely published box-counting algorithm that uses rasterization to make the process computationally efficient to run on datasets containing hundreds or thousands of high-spatial resolution linear features. This variant separately calculates fractal dimension in the horizontal and vertical dimensions. We then apply this variant on a dataset of over 300 randomly sampled segments of Slovenia's 10,000 km hiking trail network. Segments range from trails in gently varying terrain to routes in alpine regions with extremely steep and rough topography. Two methodological approaches were applied and compared: a raster-based R workflow and a vector-based ArcGIS Pro/Python workflow, the latter applied to a smaller subset of the dataset. Two main datasets were used: vector data representing hiking trails and a lidar derived digital terrain model (DTM) with a 1 m horizontal resolution, both covering the entirety of Slovenia. The two approaches were further tested and compared using five synthetic curves. Results show that, while like other box counting implementations, ours suffer from some inaccuracy, fractal dimensions in the horizontal and vertical dimensions provide useful insight into the variation in hiking trails in a wide range of conditions and offer promise for new approaches to classify trail difficulty.
Keywords:fractal dimension, box-counting, hiking trails, GIS, Slovenia
Publication status:Published
Publication version:Version of Record
Publication date:01.07.2026
Year of publishing:2026
Number of pages:Str. 115-119
PID:20.500.12556/DKUM-98869 New window
UDC:659.2:004:91
ISSN on article:3043-8861
COBISS.SI-ID:284774403 New window
DOI:10.5281/zenodo.20407690 New window
Publication date in DKUM:14.07.2026
Views:263
Downloads:4
Metadata:XML DC-XML DC-RDF
Categories:Misc.
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Record is a part of a proceedings

Title:2nd International Conference of Environmental Remote Sensing and GIS
COBISS.SI-ID:284769027 New window

Record is a part of a journal

Title:International Conference of Environmental Remote Sensing and GIS
Shortened title:Int. Conf. Environ. Remote Sens. GIS
Publisher:University of Zagreb, Faculty of Geodesy
ISSN:3043-8861
COBISS.SI-ID:204849667 New window

Document is financed by a project

Funder:ARIS - Slovenian Research and Innovation Agency
Project number:BI-US/24-26-058
Name:Vertikalna fraktalna dimenzija pohodniških poti na hribovitem terenu skozi prizmo občanske znanosti

Licences

License:CC BY 4.0, Creative Commons Attribution 4.0 International
Link:http://creativecommons.org/licenses/by/4.0/
Description:This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.
Licensing start date:01.07.2026

Secondary language

Language:Slovenian
Keywords:fraktalna dimenzija, štetje škatel, pohodniške poti, Slovenija


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