Evaluating Matrix Factorization Techniques for Thematic Mapping of Wilderness Walkability Using Multiple GPX Datasets
Quantitative thematic mapping of walkability in wilderness areas is challenging due to sparse and unreliable data. Unlike urban walkability, which depends on built infrastructure, wilderness walkability is influenced by natural terrain features such as slope, surface stability, and vegetation densit...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2025-07-01
|
| Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | https://isprs-archives.copernicus.org/articles/XLVIII-4-W13-2025/233/2025/isprs-archives-XLVIII-4-W13-2025-233-2025.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849704170367483904 |
|---|---|
| author | L. Šerić B. Draško A. Ivanda |
| author_facet | L. Šerić B. Draško A. Ivanda |
| author_sort | L. Šerić |
| collection | DOAJ |
| description | Quantitative thematic mapping of walkability in wilderness areas is challenging due to sparse and unreliable data. Unlike urban walkability, which depends on built infrastructure, wilderness walkability is influenced by natural terrain features such as slope, surface stability, and vegetation density. This study leverages 1,620 GPX trail datasets from Croatia to infer walkability by analyzing movement speed across spatial cells. To extract latent walkability patterns, we apply matrix factorization techniques, including Singular Value Decomposition (SVD), Non-Negative Matrix Factorization (NMF), Stochastic Gradient Descent (SGD), Alternating Least Squares (ALS), and Fast Independent Component Analysis (FastICA). Evaluation results indicate that NMF and Truncated SVD yield the most accurate and interpretable walkability maps. These findings highlight the potential of matrix factorization for mapping hidden variables in geospatial studies and suggest applications in related fields such as fire risk assessment. |
| format | Article |
| id | doaj-art-49b60c9cb3d54c56926aa13c68aa0f45 |
| institution | DOAJ |
| issn | 1682-1750 2194-9034 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| spelling | doaj-art-49b60c9cb3d54c56926aa13c68aa0f452025-08-20T03:16:51ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342025-07-01XLVIII-4-W13-202523323810.5194/isprs-archives-XLVIII-4-W13-2025-233-2025Evaluating Matrix Factorization Techniques for Thematic Mapping of Wilderness Walkability Using Multiple GPX DatasetsL. Šerić0B. Draško1A. Ivanda2University of Split Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, Split, CroatiaUniversity of Mostar, Mostar, Bosnia and HerzegovinaUniversity of Split Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, Split, CroatiaQuantitative thematic mapping of walkability in wilderness areas is challenging due to sparse and unreliable data. Unlike urban walkability, which depends on built infrastructure, wilderness walkability is influenced by natural terrain features such as slope, surface stability, and vegetation density. This study leverages 1,620 GPX trail datasets from Croatia to infer walkability by analyzing movement speed across spatial cells. To extract latent walkability patterns, we apply matrix factorization techniques, including Singular Value Decomposition (SVD), Non-Negative Matrix Factorization (NMF), Stochastic Gradient Descent (SGD), Alternating Least Squares (ALS), and Fast Independent Component Analysis (FastICA). Evaluation results indicate that NMF and Truncated SVD yield the most accurate and interpretable walkability maps. These findings highlight the potential of matrix factorization for mapping hidden variables in geospatial studies and suggest applications in related fields such as fire risk assessment.https://isprs-archives.copernicus.org/articles/XLVIII-4-W13-2025/233/2025/isprs-archives-XLVIII-4-W13-2025-233-2025.pdf |
| spellingShingle | L. Šerić B. Draško A. Ivanda Evaluating Matrix Factorization Techniques for Thematic Mapping of Wilderness Walkability Using Multiple GPX Datasets The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| title | Evaluating Matrix Factorization Techniques for Thematic Mapping of Wilderness Walkability Using Multiple GPX Datasets |
| title_full | Evaluating Matrix Factorization Techniques for Thematic Mapping of Wilderness Walkability Using Multiple GPX Datasets |
| title_fullStr | Evaluating Matrix Factorization Techniques for Thematic Mapping of Wilderness Walkability Using Multiple GPX Datasets |
| title_full_unstemmed | Evaluating Matrix Factorization Techniques for Thematic Mapping of Wilderness Walkability Using Multiple GPX Datasets |
| title_short | Evaluating Matrix Factorization Techniques for Thematic Mapping of Wilderness Walkability Using Multiple GPX Datasets |
| title_sort | evaluating matrix factorization techniques for thematic mapping of wilderness walkability using multiple gpx datasets |
| url | https://isprs-archives.copernicus.org/articles/XLVIII-4-W13-2025/233/2025/isprs-archives-XLVIII-4-W13-2025-233-2025.pdf |
| work_keys_str_mv | AT lseric evaluatingmatrixfactorizationtechniquesforthematicmappingofwildernesswalkabilityusingmultiplegpxdatasets AT bdrasko evaluatingmatrixfactorizationtechniquesforthematicmappingofwildernesswalkabilityusingmultiplegpxdatasets AT aivanda evaluatingmatrixfactorizationtechniquesforthematicmappingofwildernesswalkabilityusingmultiplegpxdatasets |