Bamford, Steven

Gwinner, Klaus

Houghton, Robert

Ivanov, Anton

Kim, Jung-Rack

Morley, Jeremy

Muller, Jan-Peter

Sidirpoulos, Panagiotis

van Gasselt, Stephan

Yershov, Vladimir

Institute of Transport Research:Publications

Geophysical Research AbstractsVol. 16, EGU2014-13744, 2014EGU General Assembly 2014© Author(s) 2014. CC Attribution 3.0 License.EU-FP7-iMars: Analysis of Mars Multi-Resolution Images usingAuto-Coregistration, Data Mining and Crowd Source Techniques: anoverview and a request for scientific inputs.Jan-Peter Muller (1), Klaus Gwinner (2), Stephan van Gasselt (3), Anton Ivanov (4), Jeremy Morley (5), RobertHoughton (6), Steven Bamford (7), Vladimir Yershov (1), Panagiotis Sidirpoulos (1), and Jungrack Kim (8)(1) University College London, Mullard Space Science Laboratory, Space and Climate Physics, Dorking, United Kingdom(jpm@mssl.ucl.ac.uk, +44 1483 278312), (2) DLR, DEUTSCHES ZENTRUM FUER LUFT - UND RAUMFAHRT EV,Rutherfordstrasse, 2 Berlin - 12489 Germany, (3) FREIE UNIVERSITAET BERLIN, Malteserstrasse, 74-100 Berlin - 12249Germany, (4) ECOLE POLYTECHNIQUE FEDERALE DE LAUSANNE, ELD 014, Station 11 Lausanne - 1015Switzerland, (5) THE UNIVERSITY OF NOTTINGHAM, The Nottingham Geospatial Building, Triumph Road Nottingham -NG7 2TU UK, (6) Human Factors Research Group, Faculty of Engineering, University of Nottingham, University ParkNottingham NG7 2RD UK, (7) School of Physics and Astronomy University of Nottingham, University Park NottinghamNG7 2RD UK, (8) UNIVERSITY OF SEOUL Jeonnong Dong 90 Dongdaemun Gu Seoul - 130 743 Republic of KoreaUnderstanding the role of different planetary surface formation processes within our Solar System is one of thefundamental goals of planetary science research. There has been a revolution in planetary surface observationsover the last 7 years, especially in 3D imaging of surface shape (down to resolutions of 10cm) and subsequentterrain correction of imagery from orbiting spacecraft. This has led to the ability to be able to overlay differentepochs back to the mid-1970s, examine time-varying changes (such as the recent discovery of boulder movement[Orloff et al., 2011] or the sublimation of sub-surface ice revealed by meteoritic impact [Byrne et al., 2009] as wellas examine geophysical phenomena, such as surface roughness on different length scales. Consequently we areseeing a dramatic improvement in our understanding of surface formation processes.Since January 2004 the ESA Mars Express has been acquiring global data, especially HRSC stereo (12.5-25m nadirimages) with 87% coverage with images ≤25m and more than 65% useful for stereo mapping (e.g. atmospheresufficiently clear). It has been demonstrated [Gwinner et al., 2010] that HRSC has the highest possible planimetricaccuracy of ≤25m and is well co-registered with MOLA, which represents the global 3D reference frame. HRSC3D and terrain-corrected image products therefore represent the best available 3D reference data for Mars.NASA began imaging the surface of Mars, initially from flybys in the 1960s with the first orbiter with images≤100m in the late 1970s from Viking Orbiter. The most recent orbiter to begin imaging in November 2006 is theNASA MRO which has acquired surface imagery of around 1% of the Martian surface from HiRISE (at ≈20cm)and ≈5% from CTX (≈6m) in stereo. Unfortunately, for most of these NASA images, especially MGS, MO, VOand HiRISE their accuracy of georeferencing is often worse than the quality of Mars reference data from HRSC.This reduces their value for analysing changes in time series.Within the iMars project (http://i-Mars.eu), a fully automated large-scale processing (“Big Data”) solution is beingdeveloped to generate the best possible multi-resolution DTM of Mars co-registered to HRSC (50-100m grid)products generated at DLR from CTX (6-20m grid, loc.cit.) and HiRISE (1-3m grids) on a large-scale linux clusterbased at MSSL with 224 cores and 0.25 Pb of storage. The HRSC products are employed to provide a geographicreference for all current, future and historical NASA products using automated co-registration based on featurepoints and initial results will be shown. The metadata already available for all orbital imagery acquired to date, withpoor georeferencing information, has been employed to determine the “sweet spots” which have long time seriesof measurements with different spatial resolution ranges over the last ≈50 years of observations and these will beshown. In 2015, as much of the entire NASA and ESA record of orbital images will be co-registered and the updatedgeoreferencing information employed to generate a time series of terrain relief corrected orthorectified images(ORIs) back to 1977. Web-GIS using OGC protocols will be employed to allow exploration visually of changesof the surface. Data mining processing chains are being developed to search for changes in the Martian surfacefrom 1971-2015 and the output of this data mining will be compared against the results from citizen scientists’measurements in a specialised Zooniverse implementation. Final co-registered data sets will be distributed throughboth European and US channels in a manner to be decided towards the end of the project. The resultant co-registered image datasets will represent the best possible capture of changes and evolutions in the Martian surface.A workshop is planned to be held during the EGU time period to try to capture scientific input on the relativepriorities of different types of changes based on these “sweet spots”.Acknowledgements: The research leading to these results has received funding from the European Union’s Sev-enth Framework Programme (FP7/2007-2013) under iMars grant agreement n˚ 607379.References: [1] Orloff et al. (2011) Boulder movement at high northern latitudes of Mars. J Geophys Res-Planet,116: E11006-1-12; [2] Byrne et al. (2009) Distribution of mid-latitude ground ice on Mars from new impact craters.Science, 325: 1674-1676; [3] Gwinner, K., F. et al. (2010) Topography of Mars from global mapping by HRSChigh-resolution digital terrain models and orthoimages: characteristics and performance. Earth and Planetary Sci-ence Letters 294, 506-519, doi:10.1016/j.epsl.2009.11.007, 2010.

EU-FP7-iMars: Analysis of Mars Multi-Resolution Images using 

Auto-Coregistration, Data Mining and Crowd Source Techniques

EU-FP7-iMars: Analysis of Mars Multi-Resolution Images using Auto-Coregistration, Data Mining and Crowd Source Techniques

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