Super-Resolved SAR Data

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Dataset information

Country of origin
Updated
2024.12.09 00:00
Created
2024.08.28
Available languages
English
Keywords
Quality scoring

Dataset description

Abstract This dataset contains Super Resolved Synthetic Aperture Radar (SAR) images obtained using Cosmo-SkyMed data, covering the years 2014 to 2020. The images were created for monitoring illegal mining activities in Gumern, Austria. The dataset offers a high spatial resolution of 2.5 meters, achieved through advanced processing techniques, including patching and a half-band filter. The half-band filter was applied to enhance the resolution and reduce noise, making the dataset useful for detecting and analyzing changes over time.  This depository contains data generated within the European S34 project. The data are in raw form and have not been further processed. Processed data are published in other depositories.   Identification Full Title  Super-Resolved SAR Data Abstract  This dataset contains Super Resolved SAR images from Cosmo-SkyMed, covering the years 2014 to 2020, focused on monitoring illegal mining in Gumern, Austria. With a high spatial resolution of 2.5 meters, achieved through patching and a half-band filter, the dataset is ideal for detecting and analyzing subtle changes in the region over time. Keywords  SAR, mine activity disturbances, change detection, mine monitoring, super resolution si artificial intelligence/ deep learning Pilot area  Gumern Associated resources  / Language  English URL  / Categories  / Temporal reference Creation date (dd.mm.yyyy)  05/06/2024 Revision date (dd.mm.yyyy)  05/06/2024 Quality and validity Representation type  Raster Fromat  .GeoTiff Lineage  / Spatial resolution  2.5 Positional accuracy  / Maintenance information  / Coordinate system  WGS84 Constranits related to access and use Use limitation  Free Access constraint  None Public/Private  Public Responsible organisation Responsible Contact  teodora.selea@gmv.com Responsible Party  GMV Innovating Solutions Romania Metadata on metadata Contact  teodora.selea@gmv.com Metadata language  English
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