Abstract
Sediment accumulation at culverts involves large-scale and interlinked environmental processes that are difficult to address with experimental or physical modeling methods. This article presents an alternative data-driven investigation for shedding insights into these processes. Accordingly, a web-based geovisual analytics application, the IowaDOT platform, was developed, which allows users to explore the complex processes associated with the sediment deposition at culverts. The platform provides systematic procedures for (1) collecting and integrating analytical variables into a single dataset, (2) quantifying the degree of culvert sedimentation using time series of aerial images, (3) identifying drivers that contribute to culvert sedimentation processes from a variety of culvert structural and upstream landscape characteristics using a tree-based feature selection algorithm, and (4) facilitating the understanding of complex spatial and relational patterns of culvert sedimentation processes using multivariate geovisualizations supported by a self-organizing map (SOM). As the outcomes of this study, these patterns identify culvert sedimentation-prone regions in Iowa and quantify empirical relationships between the drivers and culvert sedimentation degrees. A simple evaluation of the platform was performed to assess the usefulness and user satisfaction of the tool by professional users, and positive feedbacks are received.
Original language | English |
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Pages (from-to) | 806-817 |
Number of pages | 12 |
Journal | Science of the Total Environment |
Volume | 692 |
DOIs | |
State | Published - Nov 20 2019 |
Funding
Funding for the “Iowa Culverts” platform development was provided by the Iowa Highway Research Board , and Iowa Department of Transportation , Grant TR-655 . Special thanks to our agency colleagues David Claman and Vanessa Goetz from the Iowa Department of Transportation for guidance and support.
Keywords
- Culverts
- Data-driven
- Decision support
- Environmental transport processes
- Erosion and sedimentation
- GIS application
- Geovisual analytics
- Multivariate clustering
- Web-based