Processing Services
This section of the user manual aims to describe the processing services available in mCube . 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 mCube .
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 | Radar Products Calibration | SAR-Calib | Systematic | Radar | No (intrasensor) | Terradue |
| 3 | Auxiliary Dataset Mosaicking | MOSAIC | Systematic | Terradue | ||
| 4 | Optical Pan sharpened Image Generation | PAN-Sharp | On-demand | Optical | No (intrasensor) | Terradue |
| 5 | Multi-Sensor Band Composite | COMBI | On-demand | Optical and SAR | Yes (multi-sensor, multitemporal) | Terradue |
| 6 | Advanced Multi-Sensor Band Composite | COMBI-Plus | On-demand | Optical and SAR | Yes (multi-sensor, multitemporal) | Terradue |
| 7 | Optical Spectral Index Generation | OPT-Index | On-demand | Optical | No (intrasensor) | Terradue |
| 8 | Co-registered Stacking | Co-Register | On-demand | Optical and SAR | Yes (multi-sensor, multitemporal) | Terradue |
| 9 | 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 |
| 12 | Change Vector Analysis (CVA) | CVA | On-demand | Optical and SAR | No (intrasensor, multitemporal) | Terradue |
| 13 | IRMAD Change Detection (IRMAD) | IRMAD | On-demand | Optical and 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 |
| 16 | Burned Areas Severity Analysis | BAS | On-demand | Optical | No (intrasensor, multitemporal) | Terradue |
| 17 | Crop health indicators | S2-Crop | On-demand | Optical | No (intrasensor, multitemporal) | Planetek |
| 18 | Water Quality Parameters | S3-WQ | On-demand | Optical | No (intrasensor, multitemporal) | Planetek |
| 19 | Sentinel-2 Cloudless processor (S2-Cloudless) | S2-Cloudless | On-demand | Optical | No | Sinergise |
| 20 | K-means Unsupervised Classifier (K-means) | K-Means | On-demand | Optical and SAR | Yes (multi-sensor, multitemporal) | Terradue |
| 21 | Filter and Vectorize Discrete Raster | FilterVectorize | On-demand | Terradue |
Table 1 - Outlook of mCube 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 mCube two main types of Product can be derived from both systematic and on-demand processing services:
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Visual Products (Overview images as grayscale or RGB composite).
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Physical meaning Products (TOA reflectance, Brightness Temperature, Sigma Nought in dB, vegetation and water quality indexes, and hotpsot bitmasks).
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 | |
| 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, 11, 13 | ||
| 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, 9 | ||
| Flood bitmask | Physical | OPT | Flood bitmask from the HASARD flood detection service. (bitmask defined as 0=flood, 1=no-flood) | 1-bit | [0,1] | 12 | ||
| dNBR | Physical | OPT | Difference between the pre and post Normalized Burn Ratio | Float 32 | 11 | |||
| RBR | Physical | OPT | Relativized Burn Ratio using the pre and post Normalized Burn Ratio | Float 32 | 11 | |||
| SSI | Physical | OPT | SSI value from change detection assigned to every pixel of the image | Float 32 | 14 | |||
| Multiple WQ parameters | Physical | OPT | Suspended particulate matter, turbidity, water transparency and harmful algal bloom probability | Float 32 | 12 | |||
| 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 mCube product types.
More details about each of the physical meaning or visual products of mCube can be found in the specifications of each service.