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Geospatial Image Stream Processing: ...

Rueda-Velasquez, Carlos Alberto.

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Geospatial Image Stream Processing: Models, techniques, and applications in remote sensing change detection.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Geospatial Image Stream Processing: Models, techniques, and applications in remote sensing change detection./
Author:	Rueda-Velasquez, Carlos Alberto.
Description:	123 p.
Notes:	Source: Dissertation Abstracts International, Volume: 69-02, Section: B, page: 1115.
Contained By:	Dissertation Abstracts International69-02B.
Subject:	Computer Science. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3303196
ISBN:	9780549493525

Geospatial Image Stream Processing: Models, techniques, and applications in remote sensing change detection.
Rueda-Velasquez, Carlos Alberto.

Geospatial Image Stream Processing: Models, techniques, and applications in remote sensing change detection. - 123 p.

Source: Dissertation Abstracts International, Volume: 69-02, Section: B, page: 1115.

Thesis (Ph.D.)--University of California, Davis, 2007.

Detection of changes in environmental phenomena using remotely sensed data is a major requirement in the Earth sciences, especially in natural disaster related scenarios where real-time detection plays a crucial role in the saving of human lives and the preservation of natural resources.

ISBN: 9780549493525Subjects--Topical Terms:

626642
Computer Science.

Geospatial Image Stream Processing: Models, techniques, and applications in remote sensing change detection.
LDR:03095nam 2200277 a 45 001 951314
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020 $a 9780549493525
035 $a (UMI)AAI3303196
035 $a AAI3303196
040 $a UMI $c UMI
100 1 $a Rueda-Velasquez, Carlos Alberto. $3 1275295
245 1 0 $a Geospatial Image Stream Processing: Models, techniques, and applications in remote sensing change detection.
300 $a 123 p.
500 $a Source: Dissertation Abstracts International, Volume: 69-02, Section: B, page: 1115.
502 $a Thesis (Ph.D.)--University of California, Davis, 2007.
520 $a Detection of changes in environmental phenomena using remotely sensed data is a major requirement in the Earth sciences, especially in natural disaster related scenarios where real-time detection plays a crucial role in the saving of human lives and the preservation of natural resources.
520 $a Although various approaches formulated to model multidimensional data can in principle be applied to the inherent complexity of remotely sensed geospatial data, there are still challenging peculiarities that demand a precise characterization in the context of change detection, particularly in scenarios of fast changes. In the same vein, geospatial image streams do not fit appropriately in the standard Data Stream Management System (DSMS) approach because these systems mainly deal with tuple-based streams.
520 $a Recognizing the necessity for a systematic effort to address the above issues, the work presented in this thesis is a concrete step toward the foundation and construction of an integrated Geospatial Image Stream Processing framework, GISP. First, we present a data and metadata model for remotely sensed image streams. We introduce a precise characterization of images and image streams in the context of remotely sensed geospatial data. On this foundation, we define spatially-aware temporal operators with a consistent semantics for change analysis tasks. We address the change detection problem in settings where multiple image stream sources are available, and thus we introduce an architectural design for the processing of geospatial image streams from multiple sources. With the aim of targeting collaborative scientific environments, we construct a realization of our architecture based on Kepler, a robust and widely used scientific workflow management system, as the underlying computational support; and open data and Web interface standards, as a means to facilitate the interoperability of GISP instances with other processing infrastructures and client applications. We demonstrate our GISP framework with representative remote sensing applications including land cover detection, wildfire detection, and near real-time validation of surface temperature measurements integrating ground- and satellite-based data.
590 $a School code: 0029.
650 4 $a Computer Science. $3 626642
650 4 $a Remote Sensing. $3 1018559
690 $a 0799
690 $a 0984
710 2 $a University of California, Davis. $3 1018682
773 0 $t Dissertation Abstracts International $g 69-02B.
790 $a 0029
791 $a Ph.D.
792 $a 2007
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3303196