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# | Title | User Story | Importance | Notes |
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1 | Assessment using reference points | The user opens an OLCI L1B and a SLSTR L1B product. He/she continues to load in a list of reference points with well-known geolocations. These points are placed on the image grids. The user can then assess how well the points were placed. The primary format for the geolocations are plain text, CSV files: <lat>, <lon>, <label>. Useful are also Google Earth KMZ and ESRI Shapefiles. | MUST |
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2 | Assessment by comparing geolocations | The user places a pin in an OLCI L1B product at some distinct feature (e.g., the tip of an island). The user places another pin at the same feature in a SLSTR L1B product. Both pins will have geolocations assigned to them. These geolocations can be compared. | COULD | This would also require form of uncertainty information: What is the error which is introduced by the application of the inverse geocoding? |
3 | Assessment by transferring pins | The user places a pin in an OLCI L1B product. A pin is automatically set in a SLSTR product on base of the pin's geolocation. The displacement of the pin and its expected position can be assessed visually. In addition, the geocoding from the expected position in the SLSTR product can be derived and compared to the pin's geoposition. | MUST | This would make use of a global or synchronized pin. Short Term solution: Enable" Move pins to other product" action to also update pins |
4 | Assessment in a SYN L1C product | First, the L1C "OLC_RADIANCE_O17" band (which is located at 865 nm, the reference wavelength) is opened. The user places pins in one of the camera images or imports pins from an external file. The "OLCI pins" are automatically transferred to any "MISREGIST" files. These are nc-files which contain two variables: "row_corresp" and "col_corresp" for each camera image. From these variables, the pixel position in the respective radiance bands can be retrieved. The position of the pixels can be compared visually or by comparing the geo-locations. | MUST |
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