aj1365/MultiModelCNN
Here are the codes for the "Swin Transformer and Deep Convolutional Neural Networks for Coastal Wetland Classification using Sentinel-1, Sentinel-2, and LiDAR Data" paper.
This project helps environmental scientists and remote sensing analysts accurately map coastal wetland types. It takes satellite imagery (from Sentinel-1 and Sentinel-2) and elevation data (from LiDAR) as input, then identifies and classifies different wetland categories. The output is a precise map of coastal wetlands, valuable for ecological studies and conservation efforts.
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Use this if you need to classify coastal wetland areas using a combination of radar, optical, and elevation data from satellite and LiDAR sources.
Not ideal if you are working with non-coastal environments or different types of remote sensing data beyond Sentinel-1, Sentinel-2, and LiDAR.
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Language
Jupyter Notebook
License
Apache-2.0
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Last pushed
Aug 29, 2022
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