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PALSAR-2 ScanSAR Flooding in Rwanda

This dataset contains ALOS-2 PALSAR-2 ScanSAR Level 2.1 data, offering orthorectified backscatter observations with a 350 km observation width at 25m resolution. It was generated by JAXA in response to torrential rainfall, flooding, and landslides in Rwanda, activated through the International Disaster Charter. The data provides valuable insights for disaster response and natural resource monitoring in affected regions.

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The PALSAR-2 ScanSAR Flooding in Rwanda (L2.1) dataset offers crucial satellite imagery for understanding and responding to flood and landslide events in Rwanda. This data was specifically acquired by JAXA through the International Disaster Charter, activated by UNITAR on behalf of OCHA and the Rwanda Space Agency, following severe torrential rainfall that caused widespread damage and casualties in districts like Ngororero, Rubavu, Nyabihu, Rutsiro, and Karongi. The dataset includes ALOS-2 PALSAR-2 ScanSAR Level 2.1 data, which provides orthorectified, 25-meter resolution normalized backscatter observations.

The PALSAR-2 ScanSAR observations cover a broad area of 350 km, with polarization data stored as 16-bit digital numbers. These DN values can be converted to gamma naught values in decibel units using a specified equation. Level 2.1 data, derived from Level 1.1 data, is orthorectified using digital elevation models, ensuring geocoded image coordinates in map projection. This makes the data highly valuable for detailed analysis of affected areas, infrastructure assessment (such as impassable roads), and broader natural resource management.

The dataset is available for free under specified terms of use and is updated as new observations become available. Hosted on the Registry of Open Data on AWS, it supports various applications including disaster response, agriculture monitoring, and environmental sustainability efforts. Its inclusion on AWS Data Exchange further enhances its discoverability and accessibility for researchers, humanitarian organizations, and other stakeholders needing critical geospatial information for Rwanda.

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