ACM SIGSPATIAL Workshop on Data Mining for Geoinformatics, Nov 2, San Jose (Early Reg by Oct 14)

ACM SIGSPATIAL International Workshop on Data Mining for Geoinformatics (DMG) 2010

in conjunction with

18th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL GIS 2010)

November 2, 2010, San Jose, CA, USA
cervone.gmu.edu/research/ACM-DMGI-10.html

CALL FOR PARTICIPATION

Studying, understanding and protecting the earth and its environment are issues of crucial importance for the sustainment and development of our society. Global climate change, severe weather, and catastrophic natural hazards such as volcanic eruptions, earthquakes, hurricanes, floods, etc, require new scientific methodologies for their study. Understanding their governing dynamics and striving towards their timely detection, prediction, and prevention can help protect lives and properties, and minimize economic impact. The field of Geoinformatics focuses on the development of novel scientific algorithms and the implementation of computational methods to provide solutions to pressing earth-related problems.

Recent advances in ground, air- and space-borne sensor technologies have provided scientists from different disciplines an unprecedented access to earth-related data. These developments are quickly leading towards a data-rich but information-poor environment. The rate at which geospatial data are being generated clearly exceeds our ability to organize and analyze them to extract patterns critical for understanding in a timely manner a dynamically changing world.

These massive amounts of data require the use of an integrated framework based on Geographic information science (GIS) to address a variety of scientific questions, such as identifying strong patterns, clustering similar data points, detecting anomalies, and abstracting relevant information from sequences of satellite imagery. The scope of this workshop is to provide a forum for the exchange of ideas and the establishment of synergistic activities among scientists working in fields such as geographic information science (GIS), data mining, machine learning, geoinformatics, remote sensing, as well as natural hazards, earth and atmospheric sciences. During this one-day event we aim to bring together these scientific communities, which are overlapping but not always interacting.

For more information and accepted papers, see

cervone.gmu.edu/research/ACM-DMGI-10.html