Chun, Yongwan
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Yongwan Chun is an Associate Professor in Geospatial Information Sciences. His research interests include:
- Geographic Information System
- Geocomputation
- Geovisualization
- Spatial statistics and spatial econometrics
- Migration and migration modeling
- Network autocorrelation
Works in Treasures @ UT Dallas are made available exclusively for educational purposes such as research or instruction. Literary rights, including copyright for published works held by the creator(s) or their heirs, or other third parties may apply. All rights are reserved unless otherwise indicated by the copyright owner(s).
Recent Submissions
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Uncertainty in the Effects of the Modifiable Areal Unit Problem under Different Levels of Spatial Autocorrelation: A Simulation Study
(Taylor & Francis Ltd, 2018-11-13)The objective of this paper is to investigate uncertainties surrounding relationships between spatial autocorrelation (SA) and the modifiable areal unit problem (MAUP) with an extensive simulation experiment. Especially, ... -
Uncertainty and Context in GIScience and Geography: Challenges in the Era of Geospatial Big Data
(Taylor & Francis Ltd, 2019-01-17)No abstract available. -
Environment and Anthropogenic Activities Influence Cetacean Habitat Use in Southeastern Brazil
(Inter-Research, 2019-05-09)Investigating the influence of coastal development on marine environments is a priority to maintain healthy seas. Cetaceans are top predators, keystone and umbrella species and thus are good candidate models to evaluate ... -
Measuring Global Spatial Autocorrelation with Data Reliability Information
Assessing spatial autocorrelation (SA) of statistical estimates such as means is a common practice in spatial analysis and statistics. Popular SA statistics implicitly assume that the reliability of the estimates is ... -
Implementing Moran Eigenvector Spatial Filtering for Massively Large Georeferenced Datasets
Moran eigenvector spatial filtering (MESF) furnishes an alternative method to account for spatial autocorrelation in linear regression specifications describing georeferenced data, although spatial auto-models also are ... -
Geovisualizing Attribute Uncertainty of Interval and Ratio Variables: A Framework and an Implementation for Vector Data
(2017-12-14)This is a prototype implementation for attribute uncertainty visualization based on bivariate. Specifically, the uncertainty visualizations implemented based on three different ways. First, an overlaid symbols on a choropleth ...
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