Heterogeneous/Homogeneous Change Detection dataset

"Please if you use this datasets we appreciated that you reference this repository and cite the works related that made possible the generation of this dataset."

This change detection datastet has different events, satellites, resolutions and includes both homogeneous/heterogeneous cases. The main idea of the dataset is to bring a benchmark on semantic change detection in remote sensing field.

This dataset is the outcome of the following publications:

1. @article{   JimenezSierra2022graph,
   author={Jimenez-Sierra, David Alejandro and Quintero-Olaya, David Alfredo and Alvear-Mu{\~n}oz, Juan Carlos and Ben{\'i}tez-Restrepo, Hern{\'a}n Dar{\'i}o and Florez-Ospina, Juan Felipe and Chanussot, Jocelyn},
   journal={IEEE Transactions on Geoscience and Remote Sensing},
   title={Graph Learning Based on Signal Smoothness Representation for Homogeneous and Heterogeneous Change Detection},
   year={2022},
   volume={60},
   number={},
   pages={1-16},
   doi={10.1109/TGRS.2022.3168126}
   }
    
2. @article{   JimenezSierra2020graph,
   title={Graph-Based Data Fusion Applied to: Change Detection and Biomass Estimation in Rice Crops},
   author={Jimenez-Sierra, David Alejandro and Ben{\'i}tez-Restrepo, Hern{\'a}n Dar{\'i}o and Vargas-Cardona, Hern{\'a}n Dar{\'i}o and Chanussot, Jocelyn},
   journal={Remote Sensing},
   volume={12},
   number={17},
   pages={2683},
   year={2020},
   publisher={Multidisciplinary Digital Publishing Institute},
   doi={10.3390/rs12172683}
   }
    
3. @inproceedings{jimenez2021blue,
   title={Blue noise sampling and Nystrom extension for graph based change detection},
   author={Jimenez-Sierra, David Alejandro and Ben{\'\i}tez-Restrepo, Hern{\'a}n Dar{\'\i}o and Arce, Gonzalo R and Florez-Ospina, Juan F},
   booktitle={2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS},
   ages={2895--2898},
   year={2021},
   organization={IEEE},
   doi={10.1109/IGARSS47720.2021.9555107}
   }
    
4. @article{florez2023exploiting,
   title={Exploiting variational inequalities for generalized change detection on graphs},
   author={Florez-Ospina, Juan F and Jimenez Sierra, David A and Benitez-Restrepo, Hernan D and Arce, Gonzalo},
   journal={IEEE Transactions on Geoscience and Remote Sensing},  
   year={2023},
   volume={61},
   number={},
   pages={1-16},
   doi={10.1109/TGRS.2023.3322377}
   }
    
5. @article{florez2023exploitingxiv,
   title={Exploiting variational inequalities for generalized change detection on graphs},
   author={Florez-Ospina, Juan F. and Jimenez-Sierra, David A. and Benitez-Restrepo, Hernan D. and Arce, Gonzalo R},
   year={2023},
   publisher={TechRxiv},
   doi={10.36227/techrxiv.23295866.v1}
   }

In the table on the html file (dataset_table.html) are tabulated all the metadata and details related to each case within the dasetet. The cases with a link, were gathered from those sources and authors, therefore you should refer to their work as well.

The rest of the cases or events (without a link), were obtained through the use of open sources such as:

• Copernicus
• European Space Agency
• Alaska Satellite Facility (Vertex)
• Earth Data

In addition, we carried out all the processing of the images by using the SNAP toolbox from the European Space Agency. This proccessing involves the following:

• Data co-registration
• Cropping
• Apply Orbit (for SAR data)
• Calibration (for SAR data)
• Speckle Filter (for SAR data)
• Terrain Correction (for SAR data)

Lastly, the ground truth was obtained from homogeneous images for pre/post events by drawing polygons to highlight the areas where a visible change was present. The images where layout and synchorized to be zoomed over the same are to have a better view of changes. This was an exhaustive work in order to be precise as possible.

Feel free to improve and contribute to this dataset.