A meteosat second generation receiving, processing and storing images system developed by engineer students

Beaudoin, Laurent; Charbardes, L.-A.; Cornebise, J.; Dufour, Charles Laurier; Florczak, Kristine L.; Gachot, F.; Schott, Pierre

doi:10.1109/igarss.2005.1526510

Cited by 3 publications

(4 citation statements)

References 1 publication

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“…This work follows through the previous pedagogical experience presented in 2005 [12]. The first results are encouraging and multiple ways of improvement are planned.…”

Section: Discussionmentioning

confidence: 99%

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Near real time detection of hot spots on Meteosat Second Generation images : from forest fires to volcanic eruptions

Beaudoin¹,

Gademer²,

Amir

et al. 2007

2007 IEEE International Geoscience and Remote Sensing Symposium

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“…This work follows through the previous pedagogical experience presented in 2005 [12]. The first results are encouraging and multiple ways of improvement are planned.…”

Section: Discussionmentioning

confidence: 99%

“…The lowcost receiving station has been developed by a previous generation of students and this work has already been presented in the 2005 IGARSS Symposium [12]. So, the present work is in fact a next step of this pedagogical experience.…”

Section: The Datamentioning

confidence: 99%

Near real time detection of hot spots on Meteosat Second Generation images : from forest fires to volcanic eruptions

Beaudoin¹,

Gademer²,

Amir

et al. 2007

2007 IEEE International Geoscience and Remote Sensing Symposium

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“…Our first attempts to receive images directly from satellites occurred in 2002 [6]. These stations were analogical stations and in 2004 we developed digital receiving stations [7] to be able to receive the latest generation of meteorological satellites (Meteosat Second Generation). In recent years, we have extended the reception to polar satellites like METOP.…”

Section: The Meteosat Second Generation Databasementioning

confidence: 99%

Real time detection of forest fires and volcanic eruptions from Meteosat Second Generation images using a neural network

Avanthey¹,

Germain²,

Gademer³

et al. 2010

2010 IEEE International Geoscience and Remote Sensing Symposium

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One of the most important parameters in the estimation of the evolution of global change is the gas composition of the atmosphere and its temporal variation. Amongst the various and complex processes that absorb or produce gases, the biomass burning has very important short and long term effects [1]. Remote sensing plays a key role in monitoring these effects [2], but you have to make a compromise in temporal, spectral and spatial resolution [3,4]. As burning savannas represents the main contribution to global biomass burning, monitoring Africa becomes a priority. Because of its near real time imaging capacities and its position over the African Continent, Meteosat Second Generation (MSG) appears to be a very adapted satellite to efficiently do this task [5].The approach described in this article is based on an undergraduate project which test the potentiality of neural network for hot spot detection in MSG images. The main authors are the undergraduate student that have achieved this promising project.

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“…The Meteosat Second Generation and, specifically, the SEVIRI sensor have brought great improvements in radiometric, spatial and temporal resolution (12 channels, 1-3 km, 5 -15 minutes) that allows the use of these data for the numerical prediction by computer [2]. The instant access to data allows the development of new applications of prediction models by the use of meteorological MSG data.…”

Section: Introductionmentioning

confidence: 98%

Meteosat second Generation Surface Temperature assimilation for WRF model over Canary Islands domain

Martín

Perera

Eugênio

et al. 2012

2012 IEEE International Geoscience and Remote Sensing Symposium

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The use of weather forecasting models in energy applications has proven to be an effective tool in the management of renewable energy sources in power distribution networks which requires precise predictions and high-resolution of solar radiation and wind speed data. Therefore, the use of data from meteorological satellites such as Meteosat second Generation (MSG) can produce improvements in weather forecasting results. The integration of satellite data in weather prediction models is a developing field, because the assimilated data for these types of models mainly proceed from in-situ data at multiple stations, with low spatial resolution. The objective of this work has been the integration of data from the MSG satellite in the assimilation of meteorological model Weather Research and Forecasting (WRF-ARW), trying to improve results in meteorology predictions used in renewable power applications.

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A meteosat second generation receiving, processing and storing images system developed by engineer students

Cited by 3 publications

References 1 publication

Near real time detection of hot spots on Meteosat Second Generation images : from forest fires to volcanic eruptions

Near real time detection of hot spots on Meteosat Second Generation images : from forest fires to volcanic eruptions

Real time detection of forest fires and volcanic eruptions from Meteosat Second Generation images using a neural network

Meteosat second Generation Surface Temperature assimilation for WRF model over Canary Islands domain

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