The Tenacious Challenge:
Maria Nieto Santisteban and Jeff Valenti (the JHU team) have provided a lot of good data. It is good to provide the full problem so that other teams/people can freely take a stab at it without having to read different sources in order to figure out where all the information is. The cross correlation work is really an inference problem based on data fusion (from different sensors and places.) I am sure some of you know somebody who does this well within your campus or organization.
1. Problem Statement
- There is this boat that is following currents (no sail, no engine). You have a model for these currents. The model is shown in some animated GIF here. The model for the current is provided in this dataset. It is a set of elements that are transported from day 0 till day 14. (Time starts at Jan 29, 00h00 GMT)
- The boat has been moving over several days because of the currents.
- There is no known spectral signature for the boat. This means that for every detector used for which the spatial resolution is coarse, we have a signal representing the presence of the boat but we do not know if this is the boat we are looking for or some other object. In particular, radar data indicate the presence of something but we do not know if this something is the boat of interest. The radar resolution is coarse and so is the ER-2.
- Several satellites, planes have flown over the differents areas at different times (see reference section below for bounding boxes). For each of these flights, data was acquired and several hits were obtained. Data from RadarSat1 were taken at day 2.6, RadarSat2 data were taken at day 5.1 and ER-2 data were taken at day 4.8
- In particular, because of the cloud condition, we believe that the radar data are the most accurate ones. Objects detected over the first radar pass (RadarSat 1) can be found here. Objects detected over the second radar pass (RadarSat 2) can be found here. Another set of objects were also detected by the ER-2 but we don't know to what extent it is affected by cloud (in other words, we might be missing some items from this detection scheme). Objects detected by the ER-2 are here.
- Our main objective is evaluating the transport/drift model and identify a potential target of interest.
The Tenacious Challenge, two questions:
- What are the hits on the RadarSat 1 pass that were detected on the RadarSat 2 pass ? We are assuming the following:
- not all hits of the first pass are in the second pass and inversely not all hits on the second pass are in the first pass.
- some hits on both the first and second pass are not following currents (powered boats going from place A to B)
- There is some inherent error in the transport solution. Any solution needs to state how bad this transport solution is.
- Does any pair identified in the RadarSat 1 and RadarSat 2 match an item detected by the ER-2 ?
We realize that the brain is a very nice inference engine, your solution may be just the description of all these data in a telling graphical manner.
2. Reporting your solution:
If you have a solution for this, please put a comment in this entry pointing to your solution (blog, website...) where you state your results and how you arrived to these results. We are assuming the rank of the target indentified is also its name, for instance the third target identified in the radarsat1 case should be called radarsat1-3. Any pair should then be labeled: Radarsat1-3/RadarSat2-17 for instance.
 Bounding box coordinates for ER-2 flights are here.
 Bounding box coordinates for the RadarSat 2 flight (Feb3) are here.
 JHU team website with actual images of targets is here.