International Conference on GIScience Short Paper Proceedings
Parent: Department of Geography
eScholarship stats: Breakdown by Item for July through October, 2026
| Item | Title | Total requests | Download | View-only | %Dnld |
|---|---|---|---|---|---|
| 729295dw | Spatiotemporal enabled Content-based Image Retrieval | 209 | 135 | 74 | 64.6% |
| 7gc866qs | Time-Geography in Four Dimensions: Potential Path Volumes around 3D Trajectories | 207 | 28 | 179 | 13.5% |
| 67f0678p | Can we use OpenStreetMap POIs for the Evaluation of Urban Accessibility? | 197 | 56 | 141 | 28.4% |
| 6x0199bg | Location Optimization of Fire Stations: Trade-off between Accessibility and Service Coverage | 151 | 46 | 105 | 30.5% |
| 4hp830d6 | Outlier Detection in OpenStreetMap Data using the Random Forest Algorithm | 149 | 44 | 105 | 29.5% |
| 9z90g3zd | A Function-based model of Place | 137 | 56 | 81 | 40.9% |
| 71h533kp | Fast Computation of Continental-Sized Isochrones | 136 | 27 | 109 | 19.9% |
| 0wf6w9p9 | Tweet Geolocation Error Estimation | 135 | 38 | 97 | 28.1% |
| 0cq8c6dd | Understanding spatial patterns of biodiversity: How sensitive is phylogenetic endemism to the randomisation model? | 132 | 36 | 96 | 27.3% |
| 04b2d8xp | Identifying Local Spatiotemporal Autocorrelation Patterns of Taxi Pick-ups and Dropoffs | 130 | 78 | 52 | 60.0% |
| 46p8p31g | The Life Cycle of Volunteered Geographic Information (VGI) Contributors: the OpenStreetMap Example | 124 | 41 | 83 | 33.1% |
| 0dk1t0vc | TerraEx – a GeoWeb app for world-wide content-based search and distribution of elevation and landforms data | 121 | 45 | 76 | 37.2% |
| 0fn9v0q8 | Assessing Spatiotemporal Agreement between Multi-Temporal Built-up Land Layers and Integrated Cadastral and Building Data | 121 | 53 | 68 | 43.8% |
| 5w54k25v | Using dynamic geospatial ontologies to support information extraction from big Earth observation data sets | 121 | 45 | 76 | 37.2% |
| 8rh987cz | Measuring Distance “As the Horse Runs”: Cross-Scale Comparison of Terrain-Based Metrics | 120 | 26 | 94 | 21.7% |
| 1jb92687 | Using GPS-enabled mobile phones to characterize individuals’ activity patterns for epidemiology applications | 118 | 46 | 72 | 39.0% |
| 0tn5s4v9 | Deriving Locational Reference through Implicit Information Retrieval | 111 | 44 | 67 | 39.6% |
| 4z30b09d | Space-Time Topological Graphs | 111 | 35 | 76 | 31.5% |
| 3hc8k3js | Walk and Learn: An Empirical Framework for Assessing Spatial Knowledge Acquisition during Mobile Map Use | 110 | 52 | 58 | 47.3% |
| 5wt35578 | Crowd-sorting: reducing bias in decision making through consensus generated crowdsourced spatial information | 110 | 29 | 81 | 26.4% |
| 4b58k9tp | Pedestrian Navigation Aids, Spatial Knowledge and Walkability | 108 | 43 | 65 | 39.8% |
| 0080r0n8 | Which Kobani? A Case Study on the Role of Spatial Statistics and Semantics for Coreference Resolution Across Gazetteers | 107 | 65 | 42 | 60.7% |
| 2993d46s | A comparative study of existing multi-scale maps: what content at which scale? | 107 | 58 | 49 | 54.2% |
| 3ht0m7hh | A Field-Based Time Geography for Wildlife Movement Analysis | 107 | 39 | 68 | 36.4% |
| 54n7c1z2 | Deriving Hospital Catchment Areas from Mobile Phone Data | 106 | 53 | 53 | 50.0% |
| 26q142pp | The Role of Space in Remote Collaborations: An Exploration of Immersive Technology Attributes on Co-presence and Team Membership | 105 | 34 | 71 | 32.4% |
| 9fs8s68v | Accessing Distributed WFS Data Through A RDF Query Interface | 105 | 38 | 67 | 36.2% |
| 1g87v8dg | Refugee Spatial Awareness: Evidence from Za’atari | 104 | 40 | 64 | 38.5% |
| 8kv3n3bq | Semi-parametric Geographically Weighted Regression (S-GWR): a Case Study on Invasive Plant Species Distribution in Subtropical Nepal | 103 | 38 | 65 | 36.9% |
| 4dw721gn | Machine Learning on Spark for the Optimal IDW-based Spatiotemporal Interpolation | 102 | 19 | 83 | 18.6% |
| 8jd35618 | Retrieving Indigenous Knowledge to a Digital Map: the Case of the Traditional Farming System in a Hñahñu (Otomí) Community, Mexico | 102 | 29 | 73 | 28.4% |
| 5854c2jv | High resolution, multi-year compatible dasymetric models of US population | 98 | 39 | 59 | 39.8% |
| 6dd1m0j2 | Stress Supports Spatial Knowledge Acquisition during Wayfinding with Mobile Maps | 98 | 40 | 58 | 40.8% |
| 8nq409qz | Searching for common ground (again) | 98 | 24 | 74 | 24.5% |
| 6928w12f | The Cognitive Aspect of Place Properties | 97 | 33 | 64 | 34.0% |
| 76z9g4vb | Deserts in the Deluge: TerraPopulus and Big Human-Environment Data | 97 | 42 | 55 | 43.3% |
| 8ff033ht | An Ontological Analysis of Water Features | 97 | 26 | 71 | 26.8% |
| 1wx3m2cd | Land Use Regression of Particulate Matter in Calgary, Canada | 96 | 42 | 54 | 43.8% |
| 94g0c634 | An Algorithm for Empirically Informed Random Trajectory Generation Between Two Endpoints | 96 | 44 | 52 | 45.8% |
| 9v31f3m8 | Multi-resolution, pattern-based segmentation of very large raster datasets | 96 | 32 | 64 | 33.3% |
| 4kv536qq | A novel method for probabilistic coverage estimation of sensor networks based on 3D vector representation in complex urban environments | 95 | 31 | 64 | 32.6% |
| 8n57h6zv | Understanding the Mapping Sequence of Online Volunteers in Disaster Response | 95 | 41 | 54 | 43.2% |
| 0qh4t98s | Local variation in hedonic house pricing in Hanoi, Vietnam: a spatial analysis of status quality trade-off (SQTO) theory | 94 | 41 | 53 | 43.6% |
| 5bp4f7gj | Comparing Geospatial Ontologies with Indigenous Conceptualizations of Time | 94 | 46 | 48 | 48.9% |
| 5hc4d2q6 | Characterizing Volunteered Geographic Information using Fuzzy Clustering | 93 | 42 | 51 | 45.2% |
| 6mg271rn | A 3D Virtual Environment for Spatio-Temporal Analysis: Theoretical Approach, Proof of Concept, and User Study | 93 | 33 | 60 | 35.5% |
| 5vm764rp | Constructing a Routable Transit Network from a Real-time Vehicle Location Feed | 92 | 35 | 57 | 38.0% |
| 1jr9168v | Applied CyberGIS in the Age of Complex Spatial Health Data | 91 | 55 | 36 | 60.4% |
| 5640633b | Extracting Accurate Building Information from Off-Nadir VHR Images | 91 | 35 | 56 | 38.5% |
| 971896bp | Curating Transient Population in Urban Dynamics System | 90 | 29 | 61 | 32.2% |
Note: Due to the evolving nature of web traffic, the data presented here should be considered approximate and subject to revision. Learn more.