ANAPOLIS (2010-2012)
Analysis of polygonal terrains on Mars based on Earth analogues
Project details
Funding Institution
Fundação para a Ciência e a Tecnologia (FCT), contract PTDC/CTE-SPA/099041/2008
Period
January 2010 - June 2012
Principal Contractor
Centro de Recursos Naturais e Ambiente, Instituto Superior Técnico (CERENA/IST)
Participating Institutions
Centro de Estudos Geográficos, Universidade de Lisboa, Portugal (CEG/UL)
Centro de Geofísica, Universidade de Coimbra (CG/UC)
The University Centre in Svalbard, Norway (UNIS)
Principal Investigator
Pedro Pina (IST)
Team Members
CERENA/IST - Cristina Lira, José Saraiva, Lourenço Bandeira, Maura Lousada and Pedro Pina
CEG/UL - Alexandre Trindade, Alice Ferreira, Carla Mora, Gonçalo Vieira, Marc Oliva, Marco Jorge and Mário Neves
CG/UC - Adriane Machado, Ivo Alves and Teresa Barata
UNIS - Hanne Christiansen
Summary
One of the most intriguing aspects of the surface of Mars is the extensive presence of polygonal networks. These are geomorphologic features defined by a duality (an edge and an interior), that gives rise to a somewhat geometric arrangement on the ground. The contrast between the two components can be expressed topographically, in reflectance terms, or both. The appearance that these networks show on the surface of Mars can be extremely diverse, and their dimensions vary between the hundreds and less than five meters, though they are somewhat constant within a given network. Their distribution on the surface has been correlated with the presence of ice in the Martian soil, and the most accepted hypothesis for their presence takes into account their similarities to polygonal networks on the Earth, which occur in periglacial areas. However, there are still many questions that remain to be answered about these features.
One of the teams involved in this project has conducted research into the automated identification and characterization of these networks, achieving very good results. The areas studied contain thousands of polygons, thus ensuring that the results have statistical significance, and that the geometric and topological parameters extracted can serve the purpose of distinguishing between different types of network. The methodology used is based on the processing of images of the surface of the planet acquired by diverse probes and their cameras, at different spatial resolutions. The one aspect of this work that can be improved is related to the validation of the results, which on Mars is dependent on a visual, and thus subjective, interpretation of the orbital images.
Other teams involved in the project have a large field experience about permafrost and periglacial processes on the Earth, and one has conducted research on terrestrial polygonal networks, collecting data on the field. The combination of all this expertise will be fully exploited: the core of this project is the coupling of remotely acquired images (subject to adequate processing) and field data of the same area, a kind of study that has not been done before in relation to polygonal networks.
This will happen through an integrated study of an example of terrestrial polygonal network (occurring on an area to be selected in the Svalbard Islands, Norway), achieving a number of objectives. The most immediate will be: the adaptation of the automated methodology for identification and characterization of polygonal networks to the conditions prevailing on Earth (and the type of images available from the sensors orbiting our planet); and the thorough validation of the methodology, in terms of the accuracy of the mapping of the networks (resulting in a robust geometric and topological characterization). However, the cross-fertilization of ideas and methods that will take place between the various teams will surely lead to important insights into the features under scrutiny, both on the Earth and Mars. Clues about genetic processes, precise mechanisms of formation and evolution, relation between morphological characteristics and environmental conditions can be found through the detailed analysis of the results of this project and the input of the diverse teams. Ultimately, this can lead to a full understanding of what this type of features can tell us about climate evolution on two planets that share so many characteristics.