Processing Services
This section of the user manual aims to describe the processing services available in the GEP . Each of the services are described one by one with the provision of all essential information for their correct usage and related examples. This introduction aims to provide all the necessary information required to better understand product specifications and tutorials of the multiple services.
List of processing services
Multiple EO data pre-processing services are currently available in the GEP .
All the services are mapped in the below table 1 with service number, service name and short name. Table 1 also includes production mode, EO data type supported (Optical and/or SAR), if Multi-mission and/or multitemporal, and service owner.
| # | Service name | Short name | Mode | EO data | Combine multi-sensor assets | Owner |
|---|---|---|---|---|---|---|
| 1 | Optical Products Calibration | OPT-Calib | Systematic | Optical | No (intrasensor) | Terradue |
| 2 | Optical Pan sharpened Image Generation | PAN-Sharp | On-demand | Optical | No (intrasensor) | Terradue |
| 3 | Radar Products Calibration | SAR-Calib | Systematic | Radar | No (intrasensor) | Terradue |
| 4 | Multi-Sensor Band Composite | COMBI | On-demand | Optical and SAR | Yes (multi-sensor, multitemporal) | Terradue |
| 5 | Advanced Multi-Sensor Band Composite | COMBI-Plus | On-demand | Optical and SAR | Yes (multi-sensor, multitemporal) | Terradue |
| 6 | Optical Spectral Index Generation | OPT-Index | On-demand | Optical | No (intrasensor) | Terradue |
| 7 | Co-located Stacking | STACK | On-demand | Optical and SAR | Yes (multi-sensor, multitemporal) | Terradue |
| 10 | Coherence and Intensity Composite | SAR-COIN | On-demand | SAR | No (intrasensor, multitemporal) | Terradue |
| 11 | SAR Amplitude Change | SAR-Change | On-demand | SAR | No (intrasensor, multitemporal) | Terradue |
| 14 | DInSAR Displacement Mapping | DInSAR | On-demand | SAR | No (intrasensor, multitemporal) | Terradue |
| 15 | Hotspot Detection | HOTSPOT | On-demand | Optical | No (intrasensor) | Terradue |
| 17 | Burned Areas Severity Analysis | BAS | On-demand | Optical | No (intrasensor, multitemporal) | Terradue |
| 18 | Change Vector Analysis (CVA) | CVA | On-demand | Optical and SAR | No (intrasensor, multitemporal) | Terradue |
| 19 | IRMAD Change Detection (IRMAD) | IRMAD | On-demand | Optical and SAR | No (intrasensor, multitemporal) | Terradue |
| 20 | K-means Unsupervised Classifier (K-means) | K-Means | On-demand | Optical and SAR | Yes (multi-sensor, multitemporal) | Terradue |
| 21 | Sentinel-2 Cloudless processor (S2-Cloudless) | S2-Cloudless | On-demand | Optical | No | Sinergise |
| 24 | Filter and Vectorize Discrete Raster | FilterVectorize | On-demand | Terradue | ||
| 25 | NDVI Change Detection | NDVI-CD | On-demand | Optical | Yes (multi-sensor, multitemporal) | Terradue |
| 26 | Auxiliary Dataset Mosaicking | MOSAIC | On-demand | Terradue | ||
| 27 | Multiple Pairwise Image Correlation of OPTical images for EarThQuake analysis | GDM-OPT_ETQ | On-demand | Optical | CNRS/EOST | |
| 28 | Ground Deformation Monitoring with OPtical image Time series for landSLIDE analysis | GDM-OPT_SLIDE | On-demand | Optical | CNRS/EOST | |
| 29 | Ground Deformation Monitoring with OPtical image Time series for ICE/glacier analysis | GDM-OPT_ICE | On-demand | Optical | CNRS/EOST | |
| 30 | Digital surface models from optical stereo satellite images | DSM-OPT | On-demand | Optical | CNRS/EOST | |
| 31 | Automatic LAndslide Detection and Inventory Mapping from multispectral HR (S2 or L8) data | ALADIM-HR | On-demand | Optical | CNRS/EOST | |
| 32 | Automatic LAndslide Detection and Inventory Mapping from multispectral Very-High Resolution images | ALADIM-VHR | On-demand | Optical | CNRS/EOST | |
| 33 | DIAPASON InSAR Sentinel-1 TOPSAR(IW,EW) | DIAPASON-S1 | On-demand | SAR | CNES, Tre Altamira | |
| 34 | DIAPASON InSAR - StripMap(SM) | DIAPASON-SM | On-demand | SAR | CNES, Tre Altamira | |
| 35 | DIAPASON InSAR - StripMap(SM) | DIAPASON-SM | On-demand | SAR | CNES, Tre Altamira | |
| 36 | GMT5SAR InSAR - Sentinel-1 TOPSAR | GMT5SAR-S1 | On-demand | SAR | Terradue | |
| 37 | Ground motion pattern detection and classification in satellite image time series | TimeSAT | On-demand | CNRS/EOST | ||
| 38 | Flow Path Assessment of Gravitational Hazards at a Regional Scale | Flow-R | On-demand | Terranum | ||
| 39 | VOLume TOOl for empirical assessment of landslide volumes | VolToo | On-demand | Terranum | ||
| 40 | P-SBAS Sentinel-1 processing on-demand | P-SBAS | On-demand | SAR | CNR-IREA | |
| 41 | Surface motioN mAPPING Sentinel-1 on-demand processing service | SNAPPING | On-demand | SAR | AUTh, UJAEN, Terradue |
Table 1 - Outlook of the GEP processing services. For each service are given: service number, name, short name, production mode, possibiliy to combine multi-sensor assets, and service owner.
Different types of output products
In the GEP two main types of Product can be derived from both systematic and on-demand processing services:
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overview assets (full-res browse images as grayscale or RGB composite).
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single band assets (TOA reflectance, Brightness Temperature, Sigma Nought, interferometric phase and coherence, LOS displacement, spectral indexes, change detection bitmasks, etc.).
Each of them is given by following a dedicated data structure (e.g. unit, data type, scale factor, valid range) with respect to the nature of the product, as described in Table 2.
| Product | Type | EO data | Description | Unit | Data type | Scale factor | Valid Range | From service # |
|---|---|---|---|---|---|---|---|---|
| Overview | Visual | OPT, SAR | Overview image as RGBA band composite or grayscale product | Uint 8 | [0, 255] | all | ||
| Reflectance | Physical | OPT | TOA reflectance for VIS, RE and SWIR CBNs (e.g. blue, nir) | Uint 16 | 0.0001 | [0, 10000] | 1 | |
| Brightness temperature | Physical | OPT | TOA brightness temperature for LWIR CBNs (e.g lwir11) | K | Uint 16 | 0.01 | 1 | |
| Sigma nought | Physical | SAR | Sigma nought for L-, C-, X-band SAR data in each polarization (e.g. sigma0-HH-db) | dB | Float 32 | 3, 10, 11, 12 | ||
| Spectral index | Physical | OPT | Spectral index (NDVI, NDMIR, NBR, NDWI, NDWI2, MNDWI, NDBI) as normalized difference of CBNs in TOA reflectance | Float 32 | [-1,1] | 6, 17 | ||
| dNBR | Physical | OPT | Difference between the pre and post Normalized Burn Ratio | Float 32 | 17 | |||
| RBR | Physical | OPT | Relativized Burn Ratio using the pre and post Normalized Burn Ratio | Float 32 | 17 | |||
| Coherence | Physical | SAR | Interferometric Coherence from SAR complex imagery (a pair of SLC Datasets). Asset name is: coh_b_pp_YYYYMMDD_YYYYMMDD, where b the SAR-band [x,c,l], pp is the polarization [hh, vv], YYYYMMDD is the date of Reference and Secondary SLC Dataset |
- | Float 32 | [0,1] | 10, 14 | |
| Wrapped Phase | Physical | SAR | Interferometric Phase from SAR complex imagery (a pair of SLC Datasets). Asset name is: phase_b_pp_YYYYMMDD_YYYYMMDD, where b the SAR-band [x,c,l], pp is the polarization [hh, vv], YYYYMMDD is the date of Reference and Secondary SLC Dataset. |
rad | Float 32 | [-3.14,3.14] | 14 | |
| LOS displacement | Physical | SAR | Line of Sight Displacement in centimeters from SAR complex imagery (a pair of SLC Datasets). Asset name is: displacement_b_pp_YYYYMMDD_YYYYMMDD, where b the SAR-band [x,c,l], pp is the polarization [hh, vv], YYYYMMDD is the date of Reference and Secondary SLC Dataset. |
cm | Float 32 | 14 | ||
| Hotspot bitmask | Physical | OPT | Hotspot bitmask from hotspot detection based on nir and swir22. (bitmask defined as 0=no-hotspot, 1=hotspot) | 1-bit | [0,1] | 15 | ||
| Change detection bitmask | Physical | OPT, SAR | Change detection bitmask from IRMAD and CVA services (bitmask defined as 0=no-change, 1=change) | 8-bit | [0,1] | 18, 19 | ||
| NDVI loss bitmask | Physical | OPT | NDVI loss bitmask from the NDVI-CD. (bitmask defined as 0=no-ndvi-loss, 1=ndvi-loss) | 8-bit | [0,1] | 25 | ||
| CLM | Physical | OPT | Cloud Mask from the S2-Cloudless service. (bitmask defined as 1=clouds, 0=no-clouds) | 8-bit | [0,1] | 21 | ||
| CLP | Physical | OPT | Cloud probability in a [0-1] range from the S2-Cloudless service | 8-bit | [0,1] | 21 | ||
| Classification map | Physical | OPT, SAR | Unsupervised classification map into up to 12 classes from the K-Means service | 16-bit | [0,11] | 20 | ||
| Asset from band arithmetic | OPT, SAR | A single-band asset generated from a co-located/co-registered stack of N-images (reference plus all secondary assets) produced by the co-location /co-registered processors | Float 32 | 7, 8 |
Table 2 - Description, unit, bit-depth, scaling factor, valid range and originated service for all the GEP product types.
More details about each of the physical meaning or visual products of the GEP can be found in the specifications of each service.