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 Christopher Potter

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Average citations per article5.30
Citation Count53
Publication count10
Publication years1991-2014
Available for download4
Average downloads per article746.25
Downloads (cumulative)2,985
Downloads (12 Months)100
Downloads (6 Weeks)8
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October 2014 International Journal of Remote Sensing: Volume 35 Issue 20, 20 October 2014
Publisher: Taylor & Francis, Inc.
Citation Count: 0

2 published by ACM
July 2011 ACM Transactions on Intelligent Systems and Technology (TIST): Volume 2 Issue 4, July 2011
Publisher: ACM
Citation Count: 1
Downloads (6 Weeks): 2,   Downloads (12 Months): 27,   Downloads (Overall): 638

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Forests are a critical component of the planet's ecosystem. Unfortunately, there has been significant degradation in forest cover over recent decades as a result of logging, conversion to crop, plantation, and pasture land, or disasters (natural or man made) such as forest fires, floods, and hurricanes. As a result, significant ...
Keywords: remote sensing, forest cover change, land change, Computational sustainability

December 2008 ICDMW '08: Proceedings of the 2008 IEEE International Conference on Data Mining Workshops
Publisher: IEEE Computer Society
Citation Count: 3

Detection of anomalies in multivariate time series is an important data mining task with potential applications in medical diagnosis, ecosystem modeling, and network traffic monitoring. In this paper, we present a robust graph-based algorithm for detecting anomalies in noisy multivariate time series data. A key feature of the algorithm is ...
Keywords: multivariate time series, anomaly detection, Characterization

4 published by ACM
November 2008 GIS '08: Proceedings of the 16th ACM SIGSPATIAL international conference on Advances in geographic information systems
Publisher: ACM
Citation Count: 0
Downloads (6 Weeks): 1,   Downloads (12 Months): 5,   Downloads (Overall): 180

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This paper presents a case study on the application of data mining to the problem of detecting ecosystem disturbances from vegetation cover data obtained from satellite observations. We describe two anomaly detection approaches-moving average and random walk-for detecting such events. We also illustrate how clustering can be used to locate ...

5 published by ACM
August 2008 KDD '08: Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Publisher: ACM
Citation Count: 6
Downloads (6 Weeks): 1,   Downloads (12 Months): 27,   Downloads (Overall): 1,185

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The study of land cover change is an important problem in the Earth Science domain because of its impacts on local climate, radiation balance, biogeochemistry, hydrology, and the diversity and abundance of terrestrial species. Most well-known change detection techniques from statistics, signal processing and control theory are not well-suited for ...
Keywords: land use, time series, change detection, land cover

May 2007 Computational Discovery of Scientific Knowledge: Introduction, Techniques, and Applications in Environmental and Life Sciences
Publisher: Springer-Verlag
Citation Count: 1

This chapter describes how we used regression rules to improve upon results previously published in the Earth science literature. In such a scientific application of machine learning, it is crucially important for the learned models to be <em>understandable</em>and <em>communicable</em>. We recount how we selected a learning algorithm to maximize communicability, ...

7 published by ACM
August 2003 KDD '03: Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Publisher: ACM
Citation Count: 31
Downloads (6 Weeks): 4,   Downloads (12 Months): 41,   Downloads (Overall): 982

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To analyze the effect of the oceans and atmosphere on land climate, Earth Scientists have developed climate indices, which are time series that summarize the behavior of selected regions of the Earth's oceans and atmosphere. In the past, Earth scientists have used observation and, more recently, eigenvalue analysis techniques, such ...
Keywords: clustering, mining scientific data, singular value decomposition, earth science data, time series

November 2001 DS '01: Proceedings of the 4th International Conference on Discovery Science
Publisher: Springer-Verlag
Citation Count: 11

Research on the computational discovery of numeric equations has focused on constructing laws from scratch, whereas work on theory revision has emphasized qualitative knowledge. In this paper, we describe an approach to improving scientific models that are cast as sets of equations. We review one such model for aspects of ...



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