[General] Special Issue on Processing Large Geospatial Data

**************************************************************************** ********************** Computers & Graphics: Special Issue on PROCESSING LARGE GEOSPATIAL DATA CALL FOR CONTRIBUTIONS **************************************************************************** ********************** AIM AND SCOPE New emerging data acquisition techniques provide fast and efficient means for multidimensional spatial data collection. Airborne LIDAR surveys, SAR satellites, stereo-photogrammetry and mobile mapping systems are increasingly used for digital reconstruction. All these systems provide point clouds, often enriched with other sensor data, yielding high volumes of raw data. The special issue seeks to present an up-to-date view of approaches for data management, processing and visualization able to provide efficiently significant information contained in large geospatial datasets, and able to derive and visualize important knowledge for the relevant level of decision making. In this context, the special issue of Computers&Graphics calls for contributions on various aspects related to large geospatial data processing, with the intent of stimulating researchers from different fields such as Computer Vision, Computer Graphics, Geomatics, Remote Sensing, HPC and Grid computing working on the common goal of processing 3D data. This will provide a ground for cross-fertilization and stimulate discussions on the future challenges in this important research area. **************************************************************************** ********************** TOPICS The special issue seeks to present an up-to-date view of cutting edge computational approaches for the management, processing and visualization of large geospatial datasets in cloud or grid infrastructures. Original research or practical applications are welcome in all areas related to processing large geospatial data. Suggested topics include, but are not limited to: . Knowledge-driven processing . High-quality co-registration from multiple heterogeneous data sets . Efficient feature extraction and classification . Efficient surface generation and reconstruction . Multi-resolution and level-of-details techniques . High-quality change detection to characterize dynamic events . Visual analysis and inspection . Methods and architectures for data-intensive processing **************************************************************************** ********************** SUBMISSION PROCEDURE Authors planning to send a contribution are kindly invited to send an abstract by email to the guest editors (iqmulus(a)ge.imati.cnr.it) with prospective title, authors and a short summary of the manuscript (deadline: July 30). Full papers (12 pages A4, Computers & Graphics style) should be submitted by September 1st on the Computers & Graphics submission system (http://ees.elsevier.com/cag/). To ensure that all manuscripts are correctly identified for inclusion into the special section you are editing, it is important that authors select "SI: GC Data" when they reach the "Article Type" step in the submission process. **************************************************************************** ********************** GUEST EDITORS Jan Boehm (University College London, UK) Roderik Lindenbergh (Delft University of Technology, NL) Michela Spagnuolo (CNR-MATI, Genoa, IT) **************************************************************************** ********************** TIMELINE Abstract submission: July 30 Paper submission: September 1st Review due - 1st: October 3 Revisions due: November 7 Review due - 2nd: December 3 Final notification: December 5