Vipin Kumar, PI Department of Computer Science and Engineering
4-192, EE/CSci Building
University of Minnesota
Minneapolis, MN 55455
Phone (612) 625 0726
E-mail: kumar at cs.umn.edu URL: http://www.cs.umn.edu/~kumar
Michael Steinbach, Co-PI Department of Computer Science and Engineering
5-225 E, EE/CSci Building
University of Minnesota
Minneapolis, MN 55455
Phone (612) 625-7503
E-mail: steinbach at cs.umn.edu URL: http://www.cs.umn.edu/~steinbac
List of Supported Students and Staff:
Students:
Shyam Boriah (graduate student)
Yashu Chamber (graduate student)
Varun Chandola (graduate student)
Deepthi Cheboli (graduate student)
Marc Dunham (undergraduate, graduate student)
James Faghmous (graduate student)
Ryan Haasken (undergraduate student)
Jaya Kawale (graduate student)
Varun Mithal (undergraduate, graduate student)
Vasudha Mithal (undergraduate student)
Dominick Ormsby (undergraduate student)
Atmananda Persaud (undergraduate student)
Project Award Information:
Award Number:# 0713227
Duration: August
1, 2007 - July
31, 2010
Title: III-CTX: Collaborative Research: Spatio-Temporal Data
Mining For Global Scale Eco-Climatic Data
Keywords: data mining, data mining applications, data
analysis,
spatio-temporal data, Earth science
Project Summary:
The climate and earth sciences have recently undergone a rapid
transformation
from a data-poor to a data-rich environment. In particular,
climate and
ecosystem related observations from remote sensors on satellites,
as well
as outputs of climate or earth system models from large-scale
computational
platforms, provide terabytes of temporal, spatial and
spatio-temporal data.
These massive and information-rich datasets offer huge potential
for
understanding and predicting the behavior of the Earth's ecosystem
and for
advancing the science of climate change. However, mining patterns
from Earth Science
data is a difficult task due to the spatio-temporal nature of the
data.
This project focuses on various challenges involved in the design
of algorithms for finding spatio-temporal patterns from such data
and their applications
in discovering interesting relationships among ecological
variables from
various parts of the Earth. A special focus is on techniques
for land cover change detection (and their use in assessing the
impact
on carbon cycle) and finding teleconnections between ocean and
land variables.
Duration: 3 years.
Publications:
S.
Boriah, V.
Kumar, M. Steinbach, C. Potter, and S. Klooster. Land
Cover
Change Detection: A Case Study. Proceedings
of the 14th ACM SIGKDD International Conference on Knowledge
Discovery
and Data Mining, 2008.
S.
Boriah, V.
Kumar, M. Steinbach, P. Tan, C. Potter, and S. Klooster.
Detecting Ecosystem Disturbances and Land Cover Change using
Data
Mining. In H. Kargupta, J. Han, P. Yu, R. Motwani, and
V. Kumar,
editors, Next Generation of
Data
Mining, CRC Press, 2008.
Caitlin
Race, Michael Steinbach, Auroop Ganguly, Fred Semazzi, and
Vipin Kumar.
A
Knowledge Discovery Strategy for Relating Sea Surface
Temperatures to Frequencies of
Tropical Storms and Generating Predictions of Hurricanes Under
21st-Century Global
Warming Scenarios. In Proceedings
of Annual Conference on Intelligent Data
Understanding (CIDU), October, 2010.
Shyam
Boriah, Varun Mithal, Ashish Garg, Vipin Kumar, Michael
Steinbach, Chris Potter,
Steve Klooster. A Comparative Study of Algorithms for
Land Cover Change. In
Proceedings
of Annual Conference on Intelligent Data Understanding
(CIDU), October, 2010.
J. Kawale, M. Steinbach, and V. Kumar. Discovering Dynamic
Dipoles in Climate Data. SIAM
International Conference on Data Mining (SDM), April
28-30, 2011
Varun Mithal, Shyam Boriah, Ashish
Garg, Michael Steinbach, Christopher Potter, Steven Klooster,
Juan Carlos Castilla-Rubio, and Vipin Kumar, Monitoring Global
Forest Cover Using Data Mining, ACM Transactions on Intelligent Systems and
Technology, Volume 2, Number 4, 2011.
Xi Chen, Varun Mithal, Sruthi
Reddy Vangala, Ivan Brugere, Shyam Boriah, and Vipin Kumar. A
Study of Time Series Noise Reduction Techniques in the Context
of Land Cover Change Detection. Proceedings of the 2011 NASA Conference on
Intelligent Data Understanding, October 2011.
Yashu Chamber, Ashish Garg, Varun
Mithal, Ivan Brugere, Michael Lau, Vikrant Krishna, Shyam
Boriah, Michael Steinbach, Vipin Kumar, Chris Potter and Steve
Klooster. A Novel Time Series Based Approach to Detect
Gradual Vegetation Changes in Forests. Proceedings of the 2011 NASA
Conference on Intelligent Data Understanding, October 2011.
Ashish Garg, Lydia Manikonda,
Shashank Kumar, Vikrant Krishna, Shyam Boriah, Michael
Steinbach, Vipin Kumar, Durga Toshniwal, Chris Potter, and Steve
Klooster. A Model Free Time Series Segmentation Approach
for Land Cover Change Detection. Proceedings of the 2011 NASA Conference on
Intelligent Data Understanding, October 2011.
Varun Mithal, Ashish Garg,
Ivan Brugere, Shyam Boriah, Vipin Kumar, Michael Steinbach,
Christopher Potter, and Steven Klooster. A Scalable Time
Series Change Detection Framework to Identify Global Forest
Disturbances. Proceedings
of the 2011 NASA Conference on Intelligent Data
Understanding, October 2011.
