Abstract:
The morphology of isolated barchan dunes on Mars and Earth may shed light on the dynamic conditions that form them, their migration direction and the physical properties ...Show MoreMetadata
Abstract:
The morphology of isolated barchan dunes on Mars and Earth may shed light on the dynamic conditions that form them, their migration direction and the physical properties of the sediments composing them. Prior to this study, dune fields have been largely analyzed manually from aerial and satellite imagery, as automatic detection techniques are often not sufficiently accurate in outlining dunes. Here, we employ an instance segmentation neural network to detect and outline isolated barchan dunes on Mars and Earth. We train and test the model on martian targets using Mars reconnaissance orbiter (MRO) context camera (CTX) images, and find it sufficiently accurate (mAP=77% on the test dataset) to characterize dune field dynamics. Using our trained model, we detect and map the global distribution of barchan dunes relative to previously mapped dune fields, and find that barchan dunes are more abundant in the northern hemisphere than in the southern hemisphere. These contrasting abundances of barchans may reflect latitudinally dependent wind regimes, sediment supply, or sediment availability.
Published in: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing ( Volume: 14)
Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Neural Network ,
- Convolutional Neural Network ,
- Automatic Detection ,
- Barchan Dunes ,
- Test Dataset ,
- Northern Hemisphere ,
- Detection Techniques ,
- Satellite Imagery ,
- Southern Hemisphere ,
- Directional Migration ,
- Instance Segmentation ,
- Sediment Supply ,
- Accuracy Of Model ,
- Artificial Neural Network ,
- Iterative Process ,
- Output Layer ,
- Machine Learning Techniques ,
- Object Detection ,
- Transfer Learning ,
- Digital Elevation Model ,
- Model Hyperparameters ,
- Weight Training ,
- Region Proposal Network ,
- Image Object ,
- Model Weights ,
- Image Object Detection ,
- High Latitudes ,
- Bounding Box ,
- Mean Average Precision ,
- Planetary Bodies
- Author Keywords
Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Neural Network ,
- Convolutional Neural Network ,
- Automatic Detection ,
- Barchan Dunes ,
- Test Dataset ,
- Northern Hemisphere ,
- Detection Techniques ,
- Satellite Imagery ,
- Southern Hemisphere ,
- Directional Migration ,
- Instance Segmentation ,
- Sediment Supply ,
- Accuracy Of Model ,
- Artificial Neural Network ,
- Iterative Process ,
- Output Layer ,
- Machine Learning Techniques ,
- Object Detection ,
- Transfer Learning ,
- Digital Elevation Model ,
- Model Hyperparameters ,
- Weight Training ,
- Region Proposal Network ,
- Image Object ,
- Model Weights ,
- Image Object Detection ,
- High Latitudes ,
- Bounding Box ,
- Mean Average Precision ,
- Planetary Bodies
- Author Keywords