EU-FP7-iMARS: ANALYSIS OF MARS MULTI-RESOLUTION IMAGES USING AUTO-COREGISTRATION, DATA MINING AND CROWD SOURCE TECHNIQUES: PROCESSED RESULTS – A FIRST LOOK
- 1Imaging Group, Mullard Space Science Laboratory, University College London, Holmbury St Mary, Surrey, RH56NT, UK
- 2DLR, Deutsches Zentrum für Luft - und Raumfahrt EV, Rutherfordstrasse 2, 12489 Berlin, Germany
- 3Freie Universität Berlin, Malteserstrasse 74-100, 12249 Berlin, Germany
- 4École Polytechnique Federale de Lausanne, ELD 014, Station 11, 1015 Lausanne, Switzerland
- 5The Nottingham Geospatial Institute, University of Nottingham, Nottingham, NG7 2TU, UK
- 6University of Seoul, Jeonnong Dong 90 Dongdaemun Gu Seoul - 130 743, Republic of Korea
- 7Human Factors Research Group, University of Nottingham, Nottingham, NG7 2RD, UK
- 8School of Physics and Astronomy, University of Nottingham, Nottingham, NG7 2RD, UK
Keywords: automated DTM and co-registration, multi-resolution DTM + ORI, CTX, HiRISE, HRSC, webGIS
Abstract. Understanding planetary atmosphere-surface exchange and extra-terrestrial-surface formation processes within our Solar System is one of the fundamental goals of planetary science research. There has been a revolution in planetary surface observations over the last 15 years, especially in 3D imaging of surface shape. This has led to the ability to overlay image data and derived information from different epochs, back in time to the mid 1970s, to examine changes through time, such as the recent discovery of mass movement, tracking inter-year seasonal changes and looking for occurrences of fresh craters.
Within the EU FP-7 iMars project, we have developed a fully automated multi-resolution DTM processing chain, called the Coregistration ASP-Gotcha Optimised (CASP-GO), based on the open source NASA Ames Stereo Pipeline (ASP) [Tao et al., this conference], which is being applied to the production of planetwide DTMs and ORIs (OrthoRectified Images) from CTX and HiRISE. Alongside the production of individual strip CTX & HiRISE DTMs & ORIs, DLR [Gwinner et al., 2015] have processed HRSC mosaics of ORIs and DTMs for complete areas in a consistent manner using photogrammetric bundle block adjustment techniques. A novel automated co-registration and orthorectification chain has been developed by [Sidiropoulos & Muller, this conference]. Using the HRSC map products (both mosaics and orbital strips) as a map-base it is being applied to many of the 400,000 level-1 EDR images taken by the 4 NASA orbital cameras. In particular, the NASA Viking Orbiter camera (VO), Mars Orbiter Camera (MOC), Context Camera (CTX) as well as the High Resolution Imaging Science Experiment (HiRISE) back to 1976. A webGIS has been developed [van Gasselt et al., this conference] for displaying this time sequence of imagery and will be demonstrated showing an example from one of the HRSC quadrangle map-sheets.
Automated quality control [Sidiropoulos & Muller, 2015] techniques are applied to screen for suitable images and these are extended to detect temporal changes in features on the surface such as mass movements, streaks, spiders, impact craters, CO2 geysers and Swiss Cheese terrain. For result verification these data mining techniques are then being employed within a citizen science project within the Zooniverse family. Examples of data mining and its verification will be presented.