Jian Chen

University of North Alabama | UNA · Department of Geography

The over-use of groundwater is an increasing issue even in regions of the U.S. traditionally characterized by abundant rainfall and surface water. Part of the groundwater withdrawals in these regions can potentially be replaced by surface water, and quantitative spatial analysis to demonstrate this potential may help to spur policy changes. However...

Processing high-volume, high-velocity data streams is an important big data problem in many sciences, engineering, and technology domains. There are many open-source distributed stream processing and cloud platforms that offer low-latency stream processing at scale, but the visualization and user-interaction components of these systems are limited...

Spatial scan statistics is one of the most important models in order to detect high activity or hotspots in real world applications such as epidemiology, public health, astronomy and criminology applications on geographic data. Traditional scan statistic uses regular shapes like circles to detect areas of high activity; the same model was extended...

A major task in spatio-temporal outlier detection is to identify objects that exhibit abnormal behavior either spatially, and/or temporally. There have only been a few algorithms proposed for detecting spatial and/or temporal outliers. One example is the Local Density-Based Spatial Clustering of Applications with Noise (LDBSCAN). Density-Based Spat...

When analyzing streaming data, the results can depreciate in value faster than the analysis can be completed and results deployed. This is certainly the case in the area of anomaly detection, where detecting a potential problem as it is occurring (or in the early stages) can permit corrective behavior. However, most anomaly detection methods focus...

Water of poor quality can directly impact the budget of water available for key user groups. Despite this importance, methods for quantifying the impact of water quality on water availability remain elusive. Here, we develop a new framework for incorporating the impact of water quality on water supply by modifying the Water Supply Stress Index (WaS...

Data points that exhibit abnormal behavior, either spatially, temporally, or both, are considered spatio-temporal outliers. Spatio-Temporal outlier detection is important for the discovery of exceptional events due to the rapidly increasing amount of spatio-temporal data available, and the need to understand such data. A tropical cyclone system or...

Modeling flood inundation in an urban setting is increasingly relevant given the magnitude of potential loss and disruption associated with non-riverine, urban flooding. Both complexities in the urban environment and lack of high-resolution topographic and hydrologic data compromise the development and implementation of models of non-riverine flood...