International Conference on GIScience Short Paper Proceedings
Parent: Department of Geography
eScholarship stats: Breakdown by Item for October, 2024 through January, 2025
| Item | Title | Total requests | Download | View-only | %Dnld |
|---|---|---|---|---|---|
| 8nh5943s | Scalability in Participatory Planning: A comparison of online PPGIS methods with faceto- face meetings | 124 | 6 | 118 | 4.8% |
| 71h533kp | Fast Computation of Continental-Sized Isochrones | 111 | 8 | 103 | 7.2% |
| 1g87v8dg | Refugee Spatial Awareness: Evidence from Za’atari | 98 | 5 | 93 | 5.1% |
| 4hp830d6 | Outlier Detection in OpenStreetMap Data using the Random Forest Algorithm | 97 | 14 | 83 | 14.4% |
| 6x0199bg | Location Optimization of Fire Stations: Trade-off between Accessibility and Service Coverage | 86 | 22 | 64 | 25.6% |
| 0dk1t0vc | TerraEx – a GeoWeb app for world-wide content-based search and distribution of elevation and landforms data | 79 | 9 | 70 | 11.4% |
| 67f0678p | Can we use OpenStreetMap POIs for the Evaluation of Urban Accessibility? | 78 | 34 | 44 | 43.6% |
| 04b2d8xp | Identifying Local Spatiotemporal Autocorrelation Patterns of Taxi Pick-ups and Dropoffs | 77 | 36 | 41 | 46.8% |
| 8ff033ht | An Ontological Analysis of Water Features | 68 | 6 | 62 | 8.8% |
| 3hc8k3js | Walk and Learn: An Empirical Framework for Assessing Spatial Knowledge Acquisition during Mobile Map Use | 48 | 7 | 41 | 14.6% |
| 9z90g3zd | A Function-based model of Place | 48 | 19 | 29 | 39.6% |
| 8mf4r9rw | A Density-Based Spatial Flow Cluster Detection Method | 46 | 16 | 30 | 34.8% |
| 5bp4f7gj | Comparing Geospatial Ontologies with Indigenous Conceptualizations of Time | 43 | 12 | 31 | 27.9% |
| 0080r0n8 | Which Kobani? A Case Study on the Role of Spatial Statistics and Semantics for Coreference Resolution Across Gazetteers | 42 | 5 | 37 | 11.9% |
| 5640633b | Extracting Accurate Building Information from Off-Nadir VHR Images | 42 | 11 | 31 | 26.2% |
| 7gc866qs | Time-Geography in Four Dimensions: Potential Path Volumes around 3D Trajectories | 42 | 7 | 35 | 16.7% |
| 8nq409qz | Searching for common ground (again) | 40 | 6 | 34 | 15.0% |
| 0qh4t98s | Local variation in hedonic house pricing in Hanoi, Vietnam: a spatial analysis of status quality trade-off (SQTO) theory | 39 | 13 | 26 | 33.3% |
| 6mg271rn | A 3D Virtual Environment for Spatio-Temporal Analysis: Theoretical Approach, Proof of Concept, and User Study | 39 | 4 | 35 | 10.3% |
| 4824r3wg | Hybrid Indexing for Parallel Analysis of Spatiotemporal Point Patterns | 37 | 8 | 29 | 21.6% |
| 4b58k9tp | Pedestrian Navigation Aids, Spatial Knowledge and Walkability | 37 | 12 | 25 | 32.4% |
| 5hp8t2q3 | Spatializing Global Urban Extent: A Source Driven Approach | 37 | 11 | 26 | 29.7% |
| 3969c18v | Predicting Influenza Dynamics using a Deep Learning Approach | 36 | 5 | 31 | 13.9% |
| 54n7c1z2 | Deriving Hospital Catchment Areas from Mobile Phone Data | 36 | 7 | 29 | 19.4% |
| 971896bp | Curating Transient Population in Urban Dynamics System | 36 | 6 | 30 | 16.7% |
| 05h6f9b1 | An Object Based Approach for Submarine Canyon Identification from Surface Networks | 35 | 6 | 29 | 17.1% |
| 1wx3m2cd | Land Use Regression of Particulate Matter in Calgary, Canada | 35 | 7 | 28 | 20.0% |
| 9hf8b2wb | A Dasymetric-Based Monte Carlo Simulation Approach to the Probabilistic Analysis of Spatial Variables | 35 | 10 | 25 | 28.6% |
| 01b1r10h | Multi-Scale Extraction of Regular Activity Patterns in Spatio-Temporal Events Databases: A Study Using Geolocated Tweets from Central Mexico | 33 | 8 | 25 | 24.2% |
| 0cq8c6dd | Understanding spatial patterns of biodiversity: How sensitive is phylogenetic endemism to the randomisation model? | 33 | 6 | 27 | 18.2% |
| 6k02850k | A Data-Driven Approach for Detecting and Quantifying Modeling Biases in Geo- Ontologies by Using a Discrepancy Index | 33 | 7 | 26 | 21.2% |
| 8rh987cz | Measuring Distance “As the Horse Runs”: Cross-Scale Comparison of Terrain-Based Metrics | 33 | 13 | 20 | 39.4% |
| 04t0t6ds | A Closer Examination of Spatial-Filter-Based Local Models | 32 | 8 | 24 | 25.0% |
| 1b9432ds | What are the Probabilities of Land-Use Transitions? The Answer Depends on the Classification Method | 32 | 7 | 25 | 21.9% |
| 4dw721gn | Machine Learning on Spark for the Optimal IDW-based Spatiotemporal Interpolation | 32 | 5 | 27 | 15.6% |
| 1bw2c801 | Characterizing place: an empirical comparison between user-generated content and freelisting data | 31 | 6 | 25 | 19.4% |
| 26q142pp | The Role of Space in Remote Collaborations: An Exploration of Immersive Technology Attributes on Co-presence and Team Membership | 31 | 7 | 24 | 22.6% |
| 4zk9g37h | Uber vs. Taxis: Event detection and differentiation in New York City | 31 | 6 | 25 | 19.4% |
| 5854c2jv | High resolution, multi-year compatible dasymetric models of US population | 31 | 7 | 24 | 22.6% |
| 5sc537n4 | A moan, a discursion into the visualisation of very large spatial data and some rubrics for identifying big questions | 31 | 7 | 24 | 22.6% |
| 8kv3n3bq | Semi-parametric Geographically Weighted Regression (S-GWR): a Case Study on Invasive Plant Species Distribution in Subtropical Nepal | 31 | 8 | 23 | 25.8% |
| 3ht0m7hh | A Field-Based Time Geography for Wildlife Movement Analysis | 30 | 10 | 20 | 33.3% |
| 4z30b09d | Space-Time Topological Graphs | 30 | 6 | 24 | 20.0% |
| 6dd1m0j2 | Stress Supports Spatial Knowledge Acquisition during Wayfinding with Mobile Maps | 30 | 8 | 22 | 26.7% |
| 8jd35618 | Retrieving Indigenous Knowledge to a Digital Map: the Case of the Traditional Farming System in a Hñahñu (Otomí) Community, Mexico | 30 | 10 | 20 | 33.3% |
| 8wg042kw | Preface | 30 | 5 | 25 | 16.7% |
| 0fn9v0q8 | Assessing Spatiotemporal Agreement between Multi-Temporal Built-up Land Layers and Integrated Cadastral and Building Data | 29 | 7 | 22 | 24.1% |
| 1gr5f2c6 | Geospatial Internet of Things: Framework for fugitive Methane Gas Leaks Monitoring | 29 | 9 | 20 | 31.0% |
| 6928w12f | The Cognitive Aspect of Place Properties | 29 | 6 | 23 | 20.7% |
| 6pw0r1dz | Crowd Sensing System for Public Participation | 28 | 3 | 25 | 10.7% |
Note: Due to the evolving nature of web traffic, the data presented here should be considered approximate and subject to revision. Learn more.