Active fire monitoring with level 1.5 MSG satellite images

17Citations
Citations of this article
5Readers
Mendeley users who have this article in their library.

Abstract

The first of the new generation of Meteosat satellites, known as Meteosat Second Generation (MSG-1), was launched in August 2002. As with the current Meteosat series, MSG is spinstabilized and capable of greatly enhanced Earth observations. The satellite's 12-channel imager, known formally as the Spinning Enhanced Visible and Infrared Imager (SEVIRI), observes the full disk of the Earth with an unprecedented repeat cycle of 15 min in 12 spectral wavelength regions or channels. Our goal is to collect maximum MSG images data with our real time acquisition system, to trust the continuous observation of the Earth's full disk with a multi-spectral imager. This research gives an overview of the MSG SEVIRI instrument, the general approach for the active fire monitoring and the description of the algorithm together with the practical application of the tests and the algorithm. The AFMA algorithm (Active Fire Monitoring Algorithm) developed in this work is able to detect most of the existing active fires with a minimum of false alarms. The AFMA algorithm distinguishes between Diurnal and Nocturnal periods of day. The algorithm itself is based on a simple threshold algorithm. A few results are described and discussed. © 2009 Science Publications.

Figures

  • Fig. 1: Global synoptic of MSG acquisition system
  • Fig. 2: Schematic of the scaling of level 1.5 Counts
  • Fig. 3: AFMA algorithm: Pixel to be classified as a diurnal fire pixel
  • Table 2: Thresholds for the four fire tests separated for day/night periods
  • Fig. 4: AFMA algorithm: Pixel to be classified as a Nocturnal fire pixel
  • Fig. 5: The flowchart of the fire-detection algorithm for use with MSG SEVIRI data
  • Table 3: Calibration Coefficients of scan 1 and scan 2 extracted from the header part of each image files
  • Fig. 6a: Scan 1: The twelve raw images acquired from MSG-1 satellite on 2006. August 1st. at 13:15 UTC

References Powered by Scopus

An enhanced contextual fire detection algorithm for MODIS

1467Citations
N/AReaders
Get full text

The MODIS fire products

1056Citations
N/AReaders
Get full text

Evaluation of global fire detection algorithms using simulated avhrr infrared data

213Citations
N/AReaders
Get full text

Cited by Powered by Scopus

A spatiotemporal contextual model for forest fire detection using Himawari-8 satellite data

53Citations
N/AReaders
Get full text

RST-FIRES, an exportable algorithm for early-fire detection and monitoring: description, implementation, and field validation in the case of the MSG-SEVIRI sensor

47Citations
N/AReaders
Get full text

A spatio-temporal model for forest fire detection using HJ-IRS satellite data

22Citations
N/AReaders
Get full text

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Cite

CITATION STYLE

APA

Hassini, A., Benabdelouahed, F., Benabadji, N., & Belbachir, A. H. (2009). Active fire monitoring with level 1.5 MSG satellite images. American Journal of Applied Sciences, 6(1), 157–166. https://doi.org/10.3844/ajas.2009.157.166

Readers over time

‘16‘19‘20‘22‘2300.511.52

Readers' Seniority

Tooltip

PhD / Post grad / Masters / Doc 2

67%

Researcher 1

33%

Readers' Discipline

Tooltip

Earth and Planetary Sciences 2

67%

Environmental Science 1

33%

Save time finding and organizing research with Mendeley

Sign up for free
0