LifeWatch ERIC Metadata Catalogue
2nd stage Image Stacking
This service aims at creating a stack of coregistered multi-spectral raster images. It groups two seasons images (summer and autumn) and stack them to obtain a unique image at native resolution (2 meters) by using the Worldview-2 sensor.
It represents the Step 5 of the Ailanthus Workflow within the Internal Joint Initiative.
Default
Identification
- Date ( Creation )
- 2019-07-04
- Date ( Publication )
- 2021-04-02
- Status
- Under development / Pre operational
- Version
- 1.0
- Keywords
- Stacking
- Keywords
- multi-layer file
- Keywords
- Ailanthus
- Keywords
- IJI
- Keywords
- data processing
- Access constraints
- License
- Use limitation
- The final license will be available soon
- Protocol
- DOI
- Operation name
- Image3_WV2_2m_DrySeason.tiff
- Description
- It represents the summer multi-spectral (8 bands) image (vegetation at the dry season) acquired from Worldview-2 satellite at 2 meters spatial resolution. The data needs to be georeferenced and a surface reflectance product. These data will be stacked with coregistered images from the other season to be used as input to the supervised data-driven classifier. File format: raster geotiff.
- Function
- Input file
- Operation name
- Image4_WV2_2m_PostPeak.tiff
- Description
- It represents the autumn multi-spectral (8 bands) image (vegetation at the post peak of biomass) acquired from Worldview-2 satellite at 2 meters spatial resolution. The data needs to be georeferenced and a surface reflectance product. These data will be stacked with coregistered images from the other season to be used as input to the supervised data-driven classifier. File format: raster geotiff.
- Function
- Input file
- Operation name
- Stack_2dates_WV2_2m.tiff
- Description
- It is a multi-layer file containing the two multi-season images each one with its 8 bands. File format: raster geotiff.
- Function
- Output file
- Topic Category
- Land cover
- Service Category
- data processing
- Service Language
- eng
- Service TRL
- TRL 9 – Actual system proven in operational environment
