Journal: International Journal of Geographical Information Science

Abbreviation

Int. J. Geographical Information Systems

Publisher

Taylor & Francis

Journal Volumes

ISSN

1362-3087
1365-8816

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Filters

2010 - 2019132020 - 202511
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Publications 1 - 10 of 24
  • An alternative approach to transverse and profile terrain curvature
    Item type: Journal Article
    Krebs, Patrik; Stocker, Markus; Pezzatti, Gianni Boris; et al. (2015)
    International Journal of Geographical Information Science
  • Mapping ecosystem services at the regional scale: the validity of an upscaling approach
    Item type: Journal Article
    Le Clec'h, Solen; Sloan, Sean; Gond, Valéry; et al. (2018)
    International Journal of Geographical Information Science
  • Decoding wayfinding: analyzing wayfinding processes in the outdoor environment
    Item type: Journal Article
    Alinaghi, Negar; Giannopoulos, Ioannis; Kattenbeck, Markus; et al. (2025)
    International Journal of Geographical Information Science
    Navigating complex environments is crucial for human life, yet understanding the cognitive processes involved in its wayfinding component remains challenging. One theoretical model that explains these processes is Downs and Stea's four-step model. Our study builds on this model to empirically analyze its steps, focusing particularly on the monitoring step. Machine learning models were trained on gaze behavior and head/body movement data from over 300 routes walked by 56 participants in a real-world outdoor study, predicting three of these wayfinding steps: self-localization, route planning, and goal recognition. Applying this trained model to the respective monitoring segment of the same routes suggests that monitoring includes micro-versions of these three steps, indicating it operates as a recursive process rather than a distinct cognitive step. By bridging theoretical frameworks with empirical evidence, these findings enhance our understanding of spatial cognition and can inform the design of navigational tools and urban spaces.
  • Machine learning for cross-gazetteer matching of natural features
    Item type: Journal Article
    Acheson, Elise; Volpi, Michele; Purves, Ross S. (2020)
    International Journal of Geographical Information Science
    Defining and identifying duplicate records in a dataset is a challenging task which grows more complex when the modeled entities themselves are hard to delineate. In the geospatial domain, it may not be clear where a mountain, stream, or valley ends and begins, a problem carried over when such entities are catalogued in gazetteers. In this paper, we take two gazetteers, GeoNames and SwissNames3D, and perform matching – identifying records in each that are about the same entity – across a sample of natural feature records. We first perform rule-based matching, establishing competitive results, then apply machine learning using Random Forests, a method well-suited to the matching task. We report on the performance of a wider array of matching features than has been previously studied, including domain-specific ones such as feature type, land cover class, and elevation. Our results show an increase in performance using machine learning over rules, with a notable performance gain from considering feature types, but negligible gains from other specialized matching features. We argue that future work in this area should strive to be more reproducible and report results on a realistic testing pipeline including candidate selection, feature extraction, and classification.
  • Anomaly detection for volunteered geographic information: a case study of Safecast data
    Item type: Journal Article
    Xin, Yanan (2022)
    International Journal of Geographical Information Science
    Volunteered Geographic Information (VGI), defined as geographic information contributed voluntarily by individuals, has grown exponentially with the aid of ubiquitous GPS-enabled technologies. VGI projects have generated a large amount of geographic data, providing a new data source for scientific research. However, many scientists are concerned about the quality of VGI data for research, given the lack of rigorous and systematic quality control procedures. This study contributes to the improvement of quality control procedures by proposing a Cross-Volunteer Referencing Anomaly Detection (CVRAD) method to filter anomalous data, using the crowdsourced Safecast radiation data as a case study. The anomaly detection method is validated using two data sets: (1) an official radiation survey data set collected by the KURAMA car-borne system, (2) a set of anomalous Safecast measurements filtered by Safecast moderators. The validation results show that the proposed CVRAD method outperformed the 1.5 IQR benchmark method in minimizing the overall measurement error and detecting abnormal imports of Safecast measurements, thus demonstrating the effectiveness of the proposed method in improving the overall accuracy of crowdsourced radiation measurements.
  • Graphical design of world map projections
    Item type: Journal Article
    Jenny, Bernhard; Patterson, Tom; Hurni, Lorenz (2010)
    International Journal of Geographical Information Science
  • Special section in honor of Andrew U. Frank
    Item type: Other Journal Item
    Winter, Stephan; Egenhofer, Max; Kuhn, Werner; et al. (2018)
    International Journal of Geographical Information Science
  • An empirical study on the intra-urban goods movement patterns using logistics big data
    Item type: Journal Article
    Zhao, Pengxiang; Liu, Xintao; Shi, Wenzhong; et al. (2020)
    International Journal of Geographical Information Science
  • Improving the performance of genetic algorithms for land-use allocation problems
    Item type: Journal Article
    Schwaab, Jonas; Deb, Kalyanmoy; Goodman, Erik; et al. (2017)
    International Journal of Geographical Information Science
  • Mining transition rules of cellular automata for simulating urban expansion by using the deep learning techniques
    Item type: Journal Article
    He, Jialv; Li, Xia; Yao, Yao; et al. (2018)
    International Journal of Geographical Information Science
Publications 1 - 10 of 24