Building Predictive Models for Noisy and Heterogeneous Data: An Application in Global Monitoring of Inland Water Dynamics

Anuj Karpatne; Vipin Kumar

doi:10.1109/ICDMW.2015.217

Building Predictive Models for Noisy and Heterogeneous Data: An Application in Global Monitoring of Inland Water Dynamics

Anuj Karpatne, Vipin Kumar

Computer Science and Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Scopus citations

Abstract

Freshwater, which is only available in inland water bodies such as lakes, reservoirs, and rivers, is increasingly becoming scarce across the world and this scarcity is posing a global threat to human sustainability. A global monitoring of inland water bodies is necessary for policy-makers and the scientific community to address this problem. The promise of data-driven approaches coupled with availability of remote sensing data presents opportunities as well as challenges for global monitoring. My research aims at developing predictive models that address the challenges in analyzing remote sensing data for creating the first global monitoring system of inland water dynamics.

Original language	English (US)
Title of host publication	Proceedings - 15th IEEE International Conference on Data Mining Workshop, ICDMW 2015
Editors	Xindong Wu, Alexander Tuzhilin, Hui Xiong, Jennifer G. Dy, Charu Aggarwal, Zhi-Hua Zhou, Peng Cui
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1530-1531
Number of pages	2
ISBN (Electronic)	9781467384926
DOIs	https://doi.org/10.1109/ICDMW.2015.217
State	Published - Jan 29 2016
Event	15th IEEE International Conference on Data Mining Workshop, ICDMW 2015 - Atlantic City, United States Duration: Nov 14 2015 → Nov 17 2015

Publication series

Name	Proceedings - 15th IEEE International Conference on Data Mining Workshop, ICDMW 2015

Other

Other	15th IEEE International Conference on Data Mining Workshop, ICDMW 2015
Country/Territory	United States
City	Atlantic City
Period	11/14/15 → 11/17/15

Bibliographical note

Publisher Copyright:
© 2015 IEEE.

Keywords

Remote sensing
classification
ensemble learning
local learning

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1109/ICDMW.2015.217

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Karpatne, A., & Kumar, V. (2016). Building Predictive Models for Noisy and Heterogeneous Data: An Application in Global Monitoring of Inland Water Dynamics. In X. Wu, A. Tuzhilin, H. Xiong, J. G. Dy, C. Aggarwal, Z.-H. Zhou, & P. Cui (Eds.), Proceedings - 15th IEEE International Conference on Data Mining Workshop, ICDMW 2015 (pp. 1530-1531). Article 7395852 (Proceedings - 15th IEEE International Conference on Data Mining Workshop, ICDMW 2015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICDMW.2015.217

Building Predictive Models for Noisy and Heterogeneous Data: An Application in Global Monitoring of Inland Water Dynamics. / Karpatne, Anuj; Kumar, Vipin.
Proceedings - 15th IEEE International Conference on Data Mining Workshop, ICDMW 2015. ed. / Xindong Wu; Alexander Tuzhilin; Hui Xiong; Jennifer G. Dy; Charu Aggarwal; Zhi-Hua Zhou; Peng Cui. Institute of Electrical and Electronics Engineers Inc., 2016. p. 1530-1531 7395852 (Proceedings - 15th IEEE International Conference on Data Mining Workshop, ICDMW 2015).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Karpatne, A & Kumar, V 2016, Building Predictive Models for Noisy and Heterogeneous Data: An Application in Global Monitoring of Inland Water Dynamics. in X Wu, A Tuzhilin, H Xiong, JG Dy, C Aggarwal, Z-H Zhou & P Cui (eds), Proceedings - 15th IEEE International Conference on Data Mining Workshop, ICDMW 2015., 7395852, Proceedings - 15th IEEE International Conference on Data Mining Workshop, ICDMW 2015, Institute of Electrical and Electronics Engineers Inc., pp. 1530-1531, 15th IEEE International Conference on Data Mining Workshop, ICDMW 2015, Atlantic City, United States, 11/14/15. https://doi.org/10.1109/ICDMW.2015.217

Karpatne A, Kumar V. Building Predictive Models for Noisy and Heterogeneous Data: An Application in Global Monitoring of Inland Water Dynamics. In Wu X, Tuzhilin A, Xiong H, Dy JG, Aggarwal C, Zhou ZH, Cui P, editors, Proceedings - 15th IEEE International Conference on Data Mining Workshop, ICDMW 2015. Institute of Electrical and Electronics Engineers Inc. 2016. p. 1530-1531. 7395852. (Proceedings - 15th IEEE International Conference on Data Mining Workshop, ICDMW 2015). doi: 10.1109/ICDMW.2015.217

Karpatne, Anuj ; Kumar, Vipin. / Building Predictive Models for Noisy and Heterogeneous Data : An Application in Global Monitoring of Inland Water Dynamics. Proceedings - 15th IEEE International Conference on Data Mining Workshop, ICDMW 2015. editor / Xindong Wu ; Alexander Tuzhilin ; Hui Xiong ; Jennifer G. Dy ; Charu Aggarwal ; Zhi-Hua Zhou ; Peng Cui. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 1530-1531 (Proceedings - 15th IEEE International Conference on Data Mining Workshop, ICDMW 2015).

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abstract = "Freshwater, which is only available in inland water bodies such as lakes, reservoirs, and rivers, is increasingly becoming scarce across the world and this scarcity is posing a global threat to human sustainability. A global monitoring of inland water bodies is necessary for policy-makers and the scientific community to address this problem. The promise of data-driven approaches coupled with availability of remote sensing data presents opportunities as well as challenges for global monitoring. My research aims at developing predictive models that address the challenges in analyzing remote sensing data for creating the first global monitoring system of inland water dynamics.",

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Building Predictive Models for Noisy and Heterogeneous Data: An Application in Global Monitoring of Inland Water Dynamics

Abstract

Publication series

Other

Bibliographical note

Keywords

UN SDGs

Access

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