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Repo for the analysis of high-resolution SAR data with Sub-Pixel Offset Tracking(SPOT). The code particularly focusses on the use and validation of inlier/outlier classification and data stacking through multi-kernel averaging. The package can perform detailed analysis and optimalisation of outlier detection and removal as well as time series SPOT.

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MBemelmans/SPOTSAR

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.idea
.idea
 
 
.vscode
.vscode
 
 
SPOTSAR_main
SPOTSAR_main
 
 
__pycache__
__pycache__
 
 
tests
tests
 
 
tutorials
tutorials
 
 
.gitignore
.gitignore
 
 
AUC_heatmap_plots.ipynb
AUC_heatmap_plots.ipynb
 
 
Merapi_overview.ipynb
Merapi_overview.ipynb
 
 
PhD_env.yml
PhD_env.yml
 
 
README.md
README.md
 
 
ROC_examples.ipynb
ROC_examples.ipynb
 
 
ROC_test.ipynb
ROC_test.ipynb
 
 
SPOTSAR_env.yml
SPOTSAR_env.yml
 
 
SPOT_med_MKA.ipynb
SPOT_med_MKA.ipynb
 
 
SPOT_med_MKA_v2.ipynb
SPOT_med_MKA_v2.ipynb
 
 
__init__.py
__init__.py
 
 
animation_CSK_rmli.ipynb
animation_CSK_rmli.ipynb
 
 
data_boxplots.ipynb
data_boxplots.ipynb
 
 
data_compare_outlier.ipynb
data_compare_outlier.ipynb
 
 
inlier_probability_maps.ipynb
inlier_probability_maps.ipynb
 
 
limits_of_SAR.ipynb
limits_of_SAR.ipynb
 
 
load_data.py
load_data.py
 
 
offset_std_NDVI_boxplot.ipynb
offset_std_NDVI_boxplot.ipynb
 
 
outlier_detection.ipynb
outlier_detection.ipynb
 
 
outlier_detection_test.ipynb
outlier_detection_test.ipynb
 
 
outlier_detection_test_iter.ipynb
outlier_detection_test_iter.ipynb
 
 
package_test.ipynb
package_test.ipynb
 
 
phd.yml
phd.yml
 
 
phd2.yml
phd2.yml
 
 
phd_env_copy.yml
phd_env_copy.yml
 
 
plot_TSX_PO_SBAS.ipynb
plot_TSX_PO_SBAS.ipynb
 
 
sliding_window_std_functions.py
sliding_window_std_functions.py
 
 
stretch_amp_xcorr.ipynb
stretch_amp_xcorr.ipynb
 
 
test_env.py
test_env.py
 
 
test_haversines.py
test_haversines.py
 
 
test_haversines_v2.ipynb
test_haversines_v2.ipynb
 
 
to_do_abstract.txt
to_do_abstract.txt
 
 
tutorial2_loading_data_into_python.ipynb
tutorial2_loading_data_into_python.ipynb
 
 
tutorial3_outlier_detection.ipynb
tutorial3_outlier_detection.ipynb
 
 

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SPOTSAR

SPOTS_main README

Repository for Sub-Pixel-Offset-Tracking with SAR (SPOTSAR) package

The SPOTSAR package can be used for:

  • Performing outlier detection and removal from offset estimates (tested)
  • Performing Multi-Kernel averaging (tested)
  • Plotting results using matplotlib and seaborn (in progress)
  • Calculating offset statistics (to do)
    • query point
    • swath profile
  • Time series processing (to do)

You can test the package by using the package_test notebook

About

Repo for the analysis of high-resolution SAR data with Sub-Pixel Offset Tracking(SPOT). The code particularly focusses on the use and validation of inlier/outlier classification and data stacking through multi-kernel averaging. The package can perform detailed analysis and optimalisation of outlier detection and removal as well as time series SPOT.

Topics

classification sar volcano sub-pixel-offset-tracking

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