Conference proceeding
Feature extraction and tracking for large-scale geospatial data
2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Vol.2016-, pp.1504-1507
07/2016
DOI: 10.1109/IGARSS.2016.7729384
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.
Details
- Title: Subtitle
- Feature extraction and tracking for large-scale geospatial data
- Creators
- Lina Yu - Univ. of Nebraska-Lincoln, Nebraska, IL, USAFeiyu Zhu - Univ. of Nebraska-Lincoln, Nebraska, IL, USAHongfeng Yu - Univ. of Nebraska-Lincoln, Nebraska, IL, USAJun Wang - Univ. of Nebraska-Lincoln, Nebraska, IL, USAKwo-Sen Kuo - Univ. of Maryland, College Park, MD, USA
- Resource Type
- Conference proceeding
- Publication Details
- 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Vol.2016-, pp.1504-1507
- DOI
- 10.1109/IGARSS.2016.7729384
- eISSN
- 2153-7003
- Publisher
- IEEE
- Language
- English
- Date published
- 07/2016
- Academic Unit
- Electrical and Computer Engineering; Civil and Environmental Engineering; Physics and Astronomy; Chemical and Biochemical Engineering
- Record Identifier
- 9984104909502771
Metrics
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