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Social and Behavioral Sciences Commons™
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Articles 1 - 4 of 4
Full-Text Articles in Social and Behavioral Sciences
Evaluating The Environmental Impacts Of U.S. Historical Oil Spill Incidents, Yiming Liu, Hua Cai
Evaluating The Environmental Impacts Of U.S. Historical Oil Spill Incidents, Yiming Liu, Hua Cai
Graduate Industrial Research Symposium
Exposure to risks associated with the production and usage of products, particularly oil, poses significant threats to both ecological systems and human health. Notable examples include the Gulf War Oil Spill (1991) and the Deepwater Horizon Oil Spill (2010). However, numerous smaller-scale oil spills, which collectively contribute to substantial oil releases, often remain overlooked. To fill this gap, our study first developed a detailed oil spill incidents database, covering 1967 to 2023. We quantified the released amount (RA) of oil spills recorded by the National Oceanic and Atmospheric Administration (NOAA). Subsequently, we utilized life cycle impact indicators in ReCiPe to …
An Agent-Based Modeling Approach To Spatial Accessibility, Alexander C. Michels, Shaowen Wang
An Agent-Based Modeling Approach To Spatial Accessibility, Alexander C. Michels, Shaowen Wang
I-GUIDE Forum
Place-based spatial accessibility represents the ability of populations within geographic units to access goods and services, and thus is an important indicator for sustainable development. Existing spatial accessibility models treat population as simply demand, calculating statistics or optimizing average cost for the population within each geographic unit, rather than modeling individual decisions. This paper proposes AgentAccess, a general-purpose Agent-Based Model (ABM) for spatial accessibility analysis. An ABM framework brings us closer to reality by simulating individual and imperfect decision-making. We introduce the model and compare its results against existing spatial accessibility models using a case study of hospital beds in …
Reducing Uncertainty In Sea-Level Rise Prediction: A Spatial-Variability-Aware Approach, Subhankar Ghosh, Shuai An, Arun Sharma, Jayant Gupta, Shashi Shekhar, Aneesh Subramanian
Reducing Uncertainty In Sea-Level Rise Prediction: A Spatial-Variability-Aware Approach, Subhankar Ghosh, Shuai An, Arun Sharma, Jayant Gupta, Shashi Shekhar, Aneesh Subramanian
I-GUIDE Forum
Given multi-model ensemble climate projections, the goal is to accurately and reliably predict future sea-level rise while lowering the uncertainty. This problem is important because sea-level rise affects millions of people in coastal communities and beyond due to climate change's impacts on polar ice sheets and the ocean. This problem is challenging due to spatial variability and unknowns such as possible tipping points (e.g., collapse of Greenland or West Antarctic ice-shelf), climate feedback loops (e.g., clouds, permafrost thawing), future policy decisions, and human actions. Most existing climate modeling approaches use the same set of weights globally, during either regression or …
Passive Visual Analytics Of Social Media Data For Detection Of Unusual Events, Kush Rustagi, Junghoon Chae
Passive Visual Analytics Of Social Media Data For Detection Of Unusual Events, Kush Rustagi, Junghoon Chae
The Summer Undergraduate Research Fellowship (SURF) Symposium
Now that social media sites have gained substantial traction, huge amounts of un-analyzed valuable data are being generated. Posts containing images and text have spatiotemporal data attached as well, having immense value for increasing situational awareness of local events, providing insights for investigations and understanding the extent of incidents, their severity, and consequences, as well as their time-evolving nature. However, the large volume of unstructured social media data hinders exploration and examination. To analyze such social media data, the S.M.A.R.T system provides the analyst with an interactive visual spatiotemporal analysis and spatial decision support environment that assists in evacuation planning …