Webcam2Satellite: Estimating cloud maps from webcam imagery

Calvin Murdock; Nathan Jacobs; Robert Pless

doi:10.1109/WACV.2013.6475021

Webcam2Satellite: Estimating cloud maps from webcam imagery

Calvin Murdock, Nathan Jacobs, Robert Pless

Computer Science

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

12 Scopus citations

Abstract

We consider the problem of estimating the current satellite cloud map from a collection of broadly distributed, ground-based webcams. The approach uses historical, geo-referenced satellite imagery to learn a mapping between the satellite image and the ground imagery. We explore representational choices for inferring the cloud status based on the ground-level imagery and consider several alternatives for spatially interpolating these sparse measurements to give a complete map. Proof of concept results show that this gives plausible estimates of satellite imagery.

Original language	English
Title of host publication	2013 IEEE Workshop on Applications of Computer Vision, WACV 2013
Pages	214-221
Number of pages	8
DOIs	https://doi.org/10.1109/WACV.2013.6475021
State	Published - 2013
Event	2013 IEEE Workshop on Applications of Computer Vision, WACV 2013 - Clearwater Beach, FL, United States Duration: Jan 15 2013 → Jan 17 2013

Publication series

Name	Proceedings of IEEE Workshop on Applications of Computer Vision
ISSN (Print)	2158-3978
ISSN (Electronic)	2158-3986

Conference

Conference	2013 IEEE Workshop on Applications of Computer Vision, WACV 2013
Country/Territory	United States
City	Clearwater Beach, FL
Period	1/15/13 → 1/17/13

Funding

Funders	Funder number
National Science Foundation (NSF)	1065734

ASJC Scopus subject areas

Computer Vision and Pattern Recognition
Computer Science Applications

Access to Document

10.1109/WACV.2013.6475021

Cite this

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title = "Webcam2Satellite: Estimating cloud maps from webcam imagery",

abstract = "We consider the problem of estimating the current satellite cloud map from a collection of broadly distributed, ground-based webcams. The approach uses historical, geo-referenced satellite imagery to learn a mapping between the satellite image and the ground imagery. We explore representational choices for inferring the cloud status based on the ground-level imagery and consider several alternatives for spatially interpolating these sparse measurements to give a complete map. Proof of concept results show that this gives plausible estimates of satellite imagery.",

author = "Calvin Murdock and Nathan Jacobs and Robert Pless",

year = "2013",

doi = "10.1109/WACV.2013.6475021",

language = "English",

isbn = "9781467350532",

series = "Proceedings of IEEE Workshop on Applications of Computer Vision",

pages = "214--221",

booktitle = "2013 IEEE Workshop on Applications of Computer Vision, WACV 2013",

note = "2013 IEEE Workshop on Applications of Computer Vision, WACV 2013 ; Conference date: 15-01-2013 Through 17-01-2013",

}

Murdock, C, Jacobs, N & Pless, R 2013, Webcam2Satellite: Estimating cloud maps from webcam imagery. in 2013 IEEE Workshop on Applications of Computer Vision, WACV 2013., 6475021, Proceedings of IEEE Workshop on Applications of Computer Vision, pp. 214-221, 2013 IEEE Workshop on Applications of Computer Vision, WACV 2013, Clearwater Beach, FL, United States, 1/15/13. https://doi.org/10.1109/WACV.2013.6475021

Webcam2Satellite: Estimating cloud maps from webcam imagery. / Murdock, Calvin; Jacobs, Nathan; Pless, Robert.
2013 IEEE Workshop on Applications of Computer Vision, WACV 2013. 2013. p. 214-221 6475021 (Proceedings of IEEE Workshop on Applications of Computer Vision).

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

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N2 - We consider the problem of estimating the current satellite cloud map from a collection of broadly distributed, ground-based webcams. The approach uses historical, geo-referenced satellite imagery to learn a mapping between the satellite image and the ground imagery. We explore representational choices for inferring the cloud status based on the ground-level imagery and consider several alternatives for spatially interpolating these sparse measurements to give a complete map. Proof of concept results show that this gives plausible estimates of satellite imagery.

AB - We consider the problem of estimating the current satellite cloud map from a collection of broadly distributed, ground-based webcams. The approach uses historical, geo-referenced satellite imagery to learn a mapping between the satellite image and the ground imagery. We explore representational choices for inferring the cloud status based on the ground-level imagery and consider several alternatives for spatially interpolating these sparse measurements to give a complete map. Proof of concept results show that this gives plausible estimates of satellite imagery.

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Webcam2Satellite: Estimating cloud maps from webcam imagery

Abstract

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ASJC Scopus subject areas

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