Using deep learning to understand and map the impact of large-scale dam removals on plant communities and fluvial landforms
Faculty Mentor
Rebecca Brown
Document Type
Poster
Start Date
10-5-2023 11:15 AM
End Date
10-5-2023 1:00 PM
Location
PUB NCR
Department
Biology
Abstract
In the United States, there are now more dams being removed than being constructed; however, less than 10% of these removals have been or are being studied. While the negative environmental impacts of dams are well documented, the ecological responses to dam removal are less understood. The Elwha and Glines Canyon dams on the Elwha River, Washington, USA were removed in 2011 and 2014, respectively, and they became the largest dams to be removed to date. A decade after these removals, how have plant communities and fluvial landforms changed, and, if so, how has the relationship between these two factors evolved over the past ten years? Using vegetation surveys and remotely sensed aerial imagery collected by the United States Geological Survey, I will define vegetation cover and fluvial landform types. Then, using deep learning, I will train a neural network to identify and digitize these vegetation and landform layers. The landform and vegetation layers will then be overlayed to examine their relationship. This deep learning model could then be deployed in other dam removals to help restoration practitioners better understand and manage plant community responses to future large dam removals.
Recommended Citation
Trier, Michael, "Using deep learning to understand and map the impact of large-scale dam removals on plant communities and fluvial landforms" (2023). 2023 Symposium. 14.
https://dc.ewu.edu/srcw_2023/res_2023/p2_2023/14
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Using deep learning to understand and map the impact of large-scale dam removals on plant communities and fluvial landforms
PUB NCR
In the United States, there are now more dams being removed than being constructed; however, less than 10% of these removals have been or are being studied. While the negative environmental impacts of dams are well documented, the ecological responses to dam removal are less understood. The Elwha and Glines Canyon dams on the Elwha River, Washington, USA were removed in 2011 and 2014, respectively, and they became the largest dams to be removed to date. A decade after these removals, how have plant communities and fluvial landforms changed, and, if so, how has the relationship between these two factors evolved over the past ten years? Using vegetation surveys and remotely sensed aerial imagery collected by the United States Geological Survey, I will define vegetation cover and fluvial landform types. Then, using deep learning, I will train a neural network to identify and digitize these vegetation and landform layers. The landform and vegetation layers will then be overlayed to examine their relationship. This deep learning model could then be deployed in other dam removals to help restoration practitioners better understand and manage plant community responses to future large dam removals.
