"Very High Spatial Resolution" workshop objectives
The objectives of the "Very high spatial resolution" workshop are both linked to ORFEO, in the context of a preparatory program for processing this data, and at the same time go beyond this context. More generally, it is a way of determining major work priorities concerning methodological developments associated with the use and interpretation of very high spatial resolution optical, radar, or optical and radar data, specifically with regard to what has already been developed or what is still to be developed in the high spatial resolution field.
Therefore the input points for the workshop will be user needs, specifically those previously defined (CNES seminar on 1st-2nd April) and requalified in terms of products (DTM, DHM, change maps, risk maps, etc.). Taking into account the current state of the art in processing methods (applicable to high to very high spatial resolution data), new methodological developments - or the adaptations required for existing methods - may be defined and priorities established.
The following guidelines have already been identified:
- DTM, DHM (for example, interpretation of interferometric results in the X band, possible polarisation selection, stereoscopy - interferometry combination, etc.), change detection (velocity fields), speckle tracking (phase correlation);
- Pattern recognition (in that very high spatial resolution for many of the objects observed can be likened to photography, and further processing be considered at object (high-)level rather than at pixel (low-)level);
- texture analysis - derived from parameters such as ground roughness or vegetation (e.g. very high resolution, like aerial photography but with a higher operational level, should be able to distinguish between different types of forests depending on the texture);
- the complementary nature of optical and radar images and merging of optical and radar data; either with metric resolution data in both cases, or by combining metric optical data and high frequency radar data to improve the temporal coverage;
- change detection, either in surveillance mode to prevent phenomena such as geophysical risks, or in crisis mode to quantify changes by comparing the pre- and post-phenomenon data (this mainly means using the potential of the different SAR constellation modes to detect changes in data with different spatial and temporal resolutions, or even in possible synergy with optical data depending on the cloud cover).