Page tree
Skip to end of metadata
Go to start of metadata

PROGIS 2.0: An Integrated Approach to Planetary Rover Image Visualisation and Analysis Using an Open Source Web-GIS
MExLab Planetary Geoportal:
3D-access to Lunar rover archive data

SpeakerGiodano, Michele
Karachevtseva, Irina
AuthorsJ.G. Morley a , M. Giordano a, J. P. Muller b, Y. Tao b, J. Sprinks a, R. Barnes c, S. Gupta c, C. Traxler d, G. Paar e

a Nottingham Geospatial Institute, University of Nottingham, Triumph Road, Nottingham NG7 2TU -
b Mullard Space Science Laboratory, University College London -
c Imperial College London -
d VRVis, Vienna, Austria
e Joanneum Reasearch Institute, Graz, Austria
ScheduledSession 1 - Introduction
AbstractThe EU FP7 project PRoViDE (Planetary Robotics Vision Data Exploitation) is processing a major portion of the imaging data gathered so far from planetary surface missions (of Mars and the Moon) into unique databases, bringing them into a 3D spatial context and providing access to a complete set of 3D vision products. A different approach is needed to represent these data for scientific use: we aim not to replicate a desktop GIS with all its complexity but to create a web interface, PRoGIS, with minimal controls focusing on the usability and visibility of data, to allow planetary geologists to share annotated surface observations. Our aim is to use only Open Source components that integrate Open Web Services for planetary data; a WebGIS interface; a 3D viewer for derived data; and the capability to make and share annotations. We use Python and Django for the server-side framework and Open Layers 3 for the WebGIS client. For good performance previewing 3D data (point clouds, pictures on the surface and panoramas) we employ ThreeJS, a WebGL Javascript library. Additionally, user and group controls allow scientists to store and share their observations. PRoGIS not only displays data but can also launch sophisticated 3D vision reprocessing (PRoVIP) and an immersive 3D analysis environment (PRo3D).

The research leading to these results has received funding from the European Community's Seventh Framework Programme (FP7/2007-2013) under grant agreement n° 312377 PRoViDE.