S&T Project 1867 Final Report: Seasonal/Temporary Wetland/Floodplain Delineation using Remote Sensing and Deep Learning
Seasonal wetlands are an important habitat for many aquatic species, including juvenile anadromous fish. In the past, the delineation of seasonal wetlands has been very limited and often inaccurate by traditional methods used by Reclamation. A new methodology was created to automatically delineate seasonal wetlands from satellite imagery using machine learning methods. While additional research is needed to verify the accuracy of the results, this methodology has the potential to identify seasonal wetlands over a large area at a much lower cost than traditional methods.
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| description | Seasonal wetlands are an important habitat for many aquatic species, including juvenile anadromous fish. In the past, the delineation of seasonal wetlands has been very limited and often inaccurate by traditional methods used by Reclamation. A new methodology was created to automatically delineate seasonal wetlands from satellite imagery using machine learning methods. While additional research is needed to verify the accuracy of the results, this methodology has the potential to identify seasonal wetlands over a large area at a much lower cost than traditional methods. |
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| identifier | https://datainventory.usbr.gov/rise/item/10914 |
| keyword |
[
"Machine Learning",
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| landingPage | https://data.usbr.gov/catalog/4481/item/10914 |
| modified | 2021-05-18T17:44:26Z |
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| title | S&T Project 1867 Final Report: Seasonal/Temporary Wetland/Floodplain Delineation using Remote Sensing and Deep Learning |
