Browsing by Subject "Crust"

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Now showing items 1-12 of 12
  • Tiira, Timo; Janik, Tomasz; Kozlovskaya, Elena; Grad, Marek; Korja, Annakaisa; Komminaho, Kari; Hegedus, Endre; Kovacs, Csaba Attila; Silvennoinen, Hanna; Bruckl, Ewald (2014)
  • Pesonen, Lauri J.; Korja, Annakaisa; Hjelt, Sven-Erik (Institute of Seismology, University of Helsinki, 2000)
    S-41
  • Lahtinen, Raimo; Korja, Annakaisa; Arhe, Katriina; Eklund, Olav; Hjelt, Sven-Erik; Pesonen, Lauri J. (Institute of Seismology, University of Helsinki, 2002)
    S-42
  • Ehlers, Carl; Eklund, Olav; Korja, Annakaisa; Kruuna, Annika; Lahtinen, Raimo (Institute of Seismology, University of Helsinki, 2004)
    S-45
  • Kukkonen, Ilmo T.; Eklund, Olav; Korja, Annakaisa; Korja, Toivo; Pesonen, Lauri J.; Poutanen, Markku (Institute of Seismology, University of Helsinki, 2006)
    S-46
  • Korja, Toivo; Arhe, Katriina; Kaikkonen, Pertti; Korja, Annakaisa; Lahtinen, Raimo; Lunkka, Juha Pekka (Institute of Seismology, University of Helsinki, 2008)
    S-53
  • Heikkinen, Pekka; Arhe, Katriina; Korja, Toivo; Lahtinen, Raimo; Pesonen, Lauri J.; Rämö, Tapani (Institute of Seismology, University of Helsinki, 2010)
    S-55
  • Kukkonen, Ilmo; Kosonen, Emilia; Oinonen, Kati; Eklund, Olav; Korja, Annakaisa; Korja, Toivo; Lahtinen, Raimo; Lunkka, Juha Pekka; Poutanen, Markku (Institute of Seismology, University of Helsinki, 2012)
    S-56
  • Eklund, Olav; Kukkonen, Ilmo; Skyttä, Pietari; Sonck-Koota, Pia; Väisänen, Markku; Whipp, David (Institute of Seismology, University of Helsinki, 2014)
    S-62
  • Kukkonen, Ilmo; Heinonen, Suvi; Oinonen, Kati; Arhe, Katriina; Eklund, Olav; Karell, Fredrik; Kozlovskaya, Elena; Luttinen, Arto; Lahtinen, Raimo; Lunkka, Juha; Nykänen, Vesa; Poutanen, Markku; Tanskanen, Eija; Tiira, Timo (Institute of Seismology, University of Helsinki, 2016)
    S-65
  • Zhu, Lingli; Kukko, Antero; Virtanen, Juho-Pekka; Hyyppä, Juha; Kaartinen, Harri; Hyyppä, Hannu; Turppa, Tuomas (MDPI, 2019)
    Remote Sensing
    As data acquisition technology continues to advance, the improvement and upgrade of the algorithms for surface reconstruction are required. In this paper, we utilized multiple terrestrial Light Detection And Ranging (Lidar) systems to acquire point clouds with different levels of complexity, namely dynamic and rigid targets for surface reconstruction. We propose a robust and effective method to obtain simplified and uniform resample points for surface reconstruction. The method was evaluated. A point reduction of up to 99.371% with a standard deviation of 0.2 cm was achieved. In addition, well-known surface reconstruction methods, i.e., Alpha shapes, Screened Poisson reconstruction (SPR), the Crust, and Algebraic point set surfaces (APSS Marching Cubes), were utilized for object reconstruction. We evaluated the benefits in exploiting simplified and uniform points, as well as different density points, for surface reconstruction. These reconstruction methods and their capacities in handling data imperfections were analyzed and discussed. The findings are that (i) the capacity of surface reconstruction in dealing with diverse objects needs to be improved; (ii) when the number of points reaches the level of millions (e.g., approximately five million points in our data), point simplification is necessary, as otherwise, the reconstruction methods might fail; (iii) for some reconstruction methods, the number of input points is proportional to the number of output meshes; but a few methods are in the opposite; (iv) all reconstruction methods are beneficial from the reduction of running time; and (v) a balance between the geometric details and the level of smoothing is needed. Some methods produce detailed and accurate geometry, but their capacity to deal with data imperfection is poor, while some other methods exhibit the opposite characteristics.
  • Rothery, David A.; Massironi, Matteo; Alemanno, Giulia; Barraud, Oceane; Besse, Sebastien; Bott, Nicolas; Brunetto, Rosario; Bunce, Emma; Byrne, Paul; Capaccioni, Fabrizio; Capria, Maria Teresa; Carli, Cristian; Charlier, Bernard; Cornet, Thomas; Cremonese, Gabriele; D'Amore, Mario; De Sanctis, M. Cristina; Doressoundiram, Alain; Ferranti, Luigi; Filacchione, Gianrico; Galluzzi, Valentina; Giacomini, Lorenza; Grande, Manuel; Guzzetta, Laura G.; Helbert, Joern; Heyner, Daniel; Hiesinger, Harald; Hussmann, Hauke; Hyodo, Ryuku; Kohout, Tomas; Kozyrev, Alexander; Litvak, Maxim; Lucchetti, Alice; Malakhov, Alexey; Malliband, Christopher; Mancinelli, Paolo; Martikainen, Julia; Martindale, Adrian; Maturilli, Alessandro; Milillo, Anna; Mitrofanov, Igor; Mokrousov, Maxim; Morlok, Andreas; Muinonen, Karri; Namur, Olivier; Owens, Alan; Nittler, Larry R.; Oliveira, Joana S.; Palumbo, Pasquale; Pajola, Maurizio; Pegg, David L.; Penttilä, Antti; Politi, Romolo; Quarati, Francesco; Re, Cristina; Sanin, Anton; Schulz, Rita; Stangarone, Claudia; Stojic, Aleksandra; Tretiyakov, Vladislav; Vaisanen, Timo; Varatharajan, Indhu; Weber, Iris; Wright, Jack; Wurz, Peter; Zambon, Francesca (2020)
    BepiColombo has a larger and in many ways more capable suite of instruments relevant for determination of the topographic, physical, chemical and mineralogical properties of Mercury's surface than the suite carried by NASA's MESSENGER spacecraft. Moreover, BepiColombo's data rate is substantially higher. This equips it to confirm, elaborate upon, and go beyond many of MESSENGER's remarkable achievements. Furthermore, the geometry of BepiColombo's orbital science campaign, beginning in 2026, will enable it to make uniformly resolved observations of both northern and southern hemispheres. This will offer more detailed and complete imaging and topographic mapping, element mapping with better sensitivity and improved spatial resolution, and totally new mineralogical mapping. We discuss MESSENGER data in the context of preparing for BepiColombo, and describe the contributions that we expect BepiColombo to make towards increased knowledge and understanding of Mercury's surface and its composition. Much current work, including analysis of analogue materials, is directed towards better preparing ourselves to understand what BepiColombo might reveal. Some of MESSENGER's more remarkable observations were obtained under unique or extreme conditions. BepiColombo should be able to confirm the validity of these observations and reveal the extent to which they are representative of the planet as a whole. It will also make new observations to clarify geological processes governing and reflecting crustal origin and evolution. We anticipate that the insights gained into Mercury's geological history and its current space weathering environment will enable us to better understand the relationships of surface chemistry, morphologies and structures with the composition of crustal types, including the nature and mobility of volatile species. This will enable estimation of the composition of the mantle from which the crust was derived, and lead to tighter constraints on models for Mercury's origin including the nature and original heliocentric distance of the material from which it formed.