GIScience 2021 Short Paper Proceedings
Parent: Center for Spatial Studies
eScholarship stats: History by Item for December, 2024 through March, 2025
Item | Title | Total requests | 2025-03 | 2025-02 | 2025-01 | 2024-12 |
---|---|---|---|---|---|---|
60v7597c | Assessing Correlation Between Night-Time Light and Road Infrastructure: An Empirical Study | 76 | 16 | 30 | 17 | 13 |
0kb4z5hq | Embodied digital twins of forest environments | 68 | 16 | 16 | 21 | 15 |
9vv6j0m9 | Integrating XAI and GeoAI | 62 | 13 | 24 | 14 | 11 |
6q03b36x | Generalizing the Simple Linear Iterative Clustering (SLIC) superpixels | 60 | 19 | 14 | 10 | 17 |
89h883x4 | Improving pedestrians' spatial learning during landmark-based navigation with auditory emotional cues and narrative | 58 | 13 | 17 | 17 | 11 |
7km7x3w1 | The influence of landmark visualization style on expert wayfinders' visual attention during a real-world navigation task | 57 | 15 | 15 | 12 | 15 |
8kg664zg | Stable geographically weighted Poisson regression for count data | 54 | 15 | 14 | 16 | 9 |
41t46420 | Multiscale Geographically Weighted Discriminant Analysis | 53 | 14 | 14 | 8 | 17 |
6tt8j58m | Varying salience in indoor landmark selection for familiar and unfamiliar wayfinders: evidence from machine learning and self-reports | 51 | 11 | 14 | 18 | 8 |
88c5p28w | A network for simulating pre-colonial migration in the Americas | 45 | 12 | 21 | 7 | 5 |
4bp4q4z3 | Testing Landmark Salience Prediction in Indoor Environments Based on Visual Information | 44 | 15 | 13 | 8 | 8 |
0kd9q103 | MapSpace: POI-based Multi-Scale Global Land Use Modeling | 43 | 10 | 15 | 9 | 9 |
9cs309kd | Geo-Event Question Answering Systems: A Preliminary Research Study | 38 | 9 | 12 | 4 | 13 |
5016t2k9 | A novel method for mapping spatiotemporal structure of mobility patterns during the COVID-19 pandemic | 37 | 7 | 9 | 9 | 12 |
8dc7t93b | Understanding the use of greenspace before and during the COVID-19 pandemic by using mobile phone app data | 37 | 11 | 8 | 9 | 9 |
62s7n79k | Geographically weighted regression for compositional data: An application to the U.S. household income compositions | 35 | 7 | 14 | 7 | 7 |
1690j3zc | Examining geographical generalisation of machine learning models in urban analytics through street frontage classification and house price regression | 34 | 5 | 12 | 12 | 5 |
8t51k45t | Measuring Polycentricity: A Whole Graph Embedding Perspective | 33 | 9 | 5 | 13 | 6 |
3wz9104b | The Virtual Reality of GIScience | 31 | 6 | 13 | 7 | 5 |
4c09g6wt | Anonymization via Clustering of Locations in Road Networks | 29 | 10 | 12 | 5 | 2 |
4xj1008p | An Individual-Centered Approach for Geodemographic Classification | 28 | 8 | 8 | 5 | 7 |
5zt0p1ft | Urban Data Science for Sustainable Transport Policies in Emerging Economies | 28 | 5 | 12 | 6 | 5 |
65t7h04k | Spatio-temporal variability in Wikipedia content: The case of Greater London | 28 | 9 | 7 | 7 | 5 |
59t385np | Specifying multi-scale spatial heterogeneity in the rental housing market: The case of the Tokyo metropolitan area | 25 | 12 | 6 | 2 | 5 |
4575267v | Eco-friendly Routing based on real-time Air-quality Sensor Data from Vehicles | 24 | 8 | 4 | 6 | 6 |
0x82c21d | Agent-based Line-of-Sight Simulation for safer Crossings | 22 | 6 | 8 | 4 | 4 |
5dj756b5 | Simulating changing traffic flow caused by new bus route in Augsburg | 19 | 2 | 5 | 6 | 6 |
3376341d | Segmentation of point-based geographic space | 18 | 5 | 10 | 1 | 2 |
4bs0z3mc | GIScience in Poland – Research, Education, Community | 17 | 4 | 7 | 1 | 5 |
4n31h85w | Spatially-explicit forecasting of racial change | 15 | 2 | 5 | 5 | 3 |
9pc4j56s | A pattern-based approach to analysis and visualization of spatio-racial distribution | 14 | 3 | 5 | 2 | 4 |
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