Zhang, H., Zhou, X., Ye, X., Tang, G., Wang, H., & Jiang, S. (2023). Strength-weighted flow cluster method considering spatiotemporal contiguity to reveal interregional association patterns. GIScience & Remote Sensing, 60(1), 2252923.
One of the most crucial topics in spatial interaction studies is mining patterns from extensive origin-destination (OD) flow data to capture interregional associations. However, prevailing methodologies tend to disregard the importance of using the relative closeness of interregional connections as weights, treat spatial and temporal dimensions independently, or overlook the temporal dimension completely. Consequently, the identified patterns are susceptible to inaccuracies, and the precise identification of pattern occurrence time and duration, despite their fundamental importance, remains elusive. In light of these challenges, this study proposes a strategy to calculate and combine the strength of weighted spatiotemporal flows, and develops a clustering method and evaluation metrics based on this framework.
Cai, Z., Newman, G., Lee, J., Ye, X., Retchless, D., Zou, L., & Ham, Y. (2023). Simulating the spatial impacts of a coastal barrier in Galveston Island, Texas: a three-dimensional urban modeling approach. Geomatics, Natural Hazards and Risk, 14(1), 2192332.
Due to its vulnerability to hurricanes, Galveston Island, TX, USA, is exploring the implementation of a coastal surge barrier (also referred to as the ‘Ike Dike’) for protection from severe flood events. This research evaluates the predicted effects that the coastal spine will have across four different storm scenarios, including a Hurricane Ike scenario and 10-year, 100-year, and 500-year storm events with and without a 2.4 ft. sea level rise (SLR). To achieve this, we develop a 1:1 ratio, 3-dimensional urban model and ran real-time flood projections using ADCIRC model data with and without the coastal barrier in place.
Li, X., Rybarczyk, G., Li, W., Usman, M., Bian, J., Chen, A., & Ye, X. (2023). How do people perceive driving risks in small towns? A case study in Central Texas. Accident Analysis & Prevention, 193, 107285.
This study aims to investigate this dynamic within an understudied transportation environment – small towns in Texas, USA, defined as incorporated places with a population of less than 50,000. A web-based survey was distributed to six small towns in central Texas to ascertain perceptual traffic risk factors and personal characteristics. A participatory GIS exercise was also conducted to collect where high-risk locations were perceived and to correlate them to high crash zones. This study spatially examined the relations between perceived and observed risk locations and statistically identified a set of contributing factors which could make crash-intensive areas more perceivable by road users. The results indicated that road users’ perceived risk locations are not always associated with high crash rates. The match rate between perceived and observed risk locations varied significantly across studied sites.
Zhang, H., Qi, Z. F., Ye, X. Y., Cai, Y. B., Ma, W. C., & Chen, M. N. (2013). Analysis of land use/land cover change, population shift, and their effects on spatiotemporal patterns of urban heat islands in metropolitan Shanghai, China. Applied Geography, 44, 121-133.
Using time series Landsat TM/ETM+ imagery and demographic data of Shanghai for 1997 and 2008, the relationship between land use/land cover (LULC) change and population shift and their effects on the spatiotemporal patterns of urban heat islands (UHIs) were quantitatively examined using an integrated approach of remote sensing, geographical information systems (GIS), and statistical analysis.
Wu, K. Y., Ye, X. Y., Qi, Z. F., & Zhang, H. (2013). Impacts of land use/land cover change and socioeconomic development on regional ecosystem services: The case of fast-growing Hangzhou metropolitan area, China. Cities, 31, 276-284.
This study analyzes land use dynamics, spatiotemporal patterns of ecosystem service value (ESV), and the forces driving growth in the Hangzhou metropolitan area (HMA) in China. An integrated approach utilizing a Geographic Information System (GIS) and Remote Sensing (RS) was used to extract information on land use/land cover (LULC) change over the period of 1978–2008 from time-series Landsat MSS/TM/ETM+ imagery.
