Feature extraction and tracking for large-scale geospatial data

Lina Yu, Feiyu Zhu, Hongfeng Yu, Jun Wang, Kwo Sen Kuo

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Feature extraction and tracking is a fundamental operation used in many geoscience applications. In this paper, we present a scalable method for computing and tracking features on distributed memory machines for large-scale geospatial data. We carefully apply new communication schemes to minimize the data exchanged among the computing nodes in building and updating the global connectivity information of features. We present a theoretical complexity analysis, and show that our method can significantly reduce the communication cost compared to the traditional method.

Original languageEnglish (US)
Title of host publication2016 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1504-1507
Number of pages4
ISBN (Electronic)9781509033324
DOIs
StatePublished - Nov 1 2016
Event36th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016 - Beijing, China
Duration: Jul 10 2016Jul 15 2016

Publication series

NameInternational Geoscience and Remote Sensing Symposium (IGARSS)
Volume2016-November

Other

Other36th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016
CountryChina
CityBeijing
Period7/10/167/15/16

Keywords

  • Feature extraction and tracking
  • geospatial data
  • large-scale data
  • parallel and distributed computing

ASJC Scopus subject areas

  • Computer Science Applications
  • Earth and Planetary Sciences(all)

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