Continuous Monitoring of Forest Fires in the Mediterranean Area Using MSG

Fires represent one of the main factors of degradation and destruction of the Mediterranean forest heritage. According to fire-fighting agencies, a satellite-based fire-detection system can be considered operationally useful for Mediterranean countries when fires with a minimum extent of 1500 m2 can be detected with a temporal resolution of 30 min. In fact, such a system should be able to detect fires at their first stage when it is possible to extinguish them more easily. The Centro di Ricerca Progetto San Marco has been analyzing for several years the possibility of using images acquired by the Spinning Enhanced Visible and Infrared Imager sensor onboard the geostationary satellite Meteosat Second Generation for this purpose. A new processing approach exploiting the increase in both spatial and temporal resolution (15 min) with respect to previous meteosat systems is described in this paper. The idea is based on the use of a change-detection technique to maximize the detection capabilities of the system in spite of its limited spatial resolution. This technique consists of comparing two or more images acquired at 15-min intervals, for which any temperature change can be attributed to fast dynamic phenomena, such as fires, when natural changes are modeled and removed. An assessment of the performances of this algorithm is carried out comparing its results with the report made available by Italian fire-fighting agencies and with fire products based on higher resolution sensors such as the Moderate Resolution Imaging Spectroradiometer

[1]  Carlo Ulivieri,et al.  A split window algorithm for estimating land surface temperature from satellites , 1994 .

[2]  H. Fischer,et al.  Land surface temperature and emissivity estimation from passive sensor data: Theory and practice-current trends , 2002 .

[3]  E. Prins,et al.  Trends in South American biomass burning detected with the GOES visible infrared spin scan radiometer atmospheric sounder from 1983 to 1991 , 1994 .

[4]  Z. Wan,et al.  Evaluation of Six Methods for Extracting Relative Emissivity Spectra from Thermal Infrared Images , 1999 .

[5]  Eric A. Smith,et al.  Simultaneous Land Surface Temperature–Emissivity Retrieval in the Infrared Split Window , 1999 .

[6]  Ying Li,et al.  A hybrid contextual approach to wildland fire detection using multispectral imagery , 2005, IEEE Transactions on Geoscience and Remote Sensing.

[7]  C. O. Justicea,et al.  The MODIS fire products , 2002 .

[8]  Pietro Ceccato,et al.  A contextual algorithm for AVHRR fire detection , 1996 .

[9]  R. Lasaponara,et al.  Evaluation of a new satellite-based method for forest fire detection , 2001 .

[10]  Z. Wan.  MODIS Land-Surface Temperature Algorithm Theoretical Basis Document (LST ATBD) , 1999 .

[11]  François Petitcolin,et al.  Land surface reflectance, emissivity and temperature from MODIS middle and thermal infrared data , 2002 .

[12]  C. DaCamara,et al.  Land surface temperature and emissivity estimation based on the two-temperature method: sensitivity analysis using simulated MSG/SEVIRI data , 2004 .

[13]  Jennifer Robinson,et al.  Fire from space : global fire evaluation using infrared remote sensing , 1991 .

[14]  Patrick Minnis,et al.  Surface spectral emissivity derived from MODIS data , 2003, SPIE Asia-Pacific Remote Sensing.

[15]  Lucien M. Biberman.  Electro-optical imaging : system performance and modeling , 2001 .

[16]  Shunlin Liang,et al.  An optimization algorithm for separating land surface temperature and emissivity from multispectral thermal infrared imagery , 2001, IEEE Trans. Geosci. Remote. Sens..

[17]  Yoram J. Kaufman,et al.  A Review of AVHRR-based Active Fire Detection Algorithms: Principles, Limitations, and Recommendations , 2000 .

[18]  Alberto W. Setzer,et al.  AVHRR monitoring of vegetation ? res in the tropics: toward the development of a global product , 1996 .

[19]  E. Prins,et al.  Geostationary satellite detection of bio mass burning in South America , 1992 .