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Low Cost Pre-operative Fire Monitoring from Fire Danger to Severity Estimation Based on Satellite MODIS, Landsat and ASTER Data: The Experience of FIRE-SAT Project in the Basilicata Region (Italy)

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Computational Science and Its Applications – ICCSA 2012 (ICCSA 2012)

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Abstract

This paper presents the results we obtained in the context of the FIRE-SAT project focused on the use of satellite data for pre-operational monitoring of fire danger and fire effects in the Basilicata Region. The use of satellite data was manyfold, to obtain: (i) fuel property (type and loading) maps, mainly obtained from satellite Landsat TM data, (ii) fuel moisture estimation (mainly from MODIS), (iii) fire danger/susceptibility indices as well as (iv) post fire effects including fire severity and vegetation recovery assessment. Results obtained during the first year of project (2008) suggested that the integrated model identified the main fire danger zones by means of the integration of fuel types with daily fuel moisture and Greenness maps. MODIS multitemporal data analyses enable us to dynamically estimate fire severity as well as to map fire affected areas and evaluate the vegetation recovery capability over time. The pre-operative use of the integrated model, carried out within the framework of the FIRE-SAT project funded by the Basilicata Region, pointed out that the system enables us to timely monitor spatial and temporal variations of fire susceptibility and promptly provide useful information on both fire severity and post fire regeneration capability.

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© 2012 Springer-Verlag Berlin Heidelberg

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Lanorte, A., De Santis, F., Aromando, A., Lasaponara, R. (2012). Low Cost Pre-operative Fire Monitoring from Fire Danger to Severity Estimation Based on Satellite MODIS, Landsat and ASTER Data: The Experience of FIRE-SAT Project in the Basilicata Region (Italy). In: Murgante, B., et al. Computational Science and Its Applications – ICCSA 2012. ICCSA 2012. Lecture Notes in Computer Science, vol 7335. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31137-6_37

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  • DOI: https://doi.org/10.1007/978-3-642-31137-6_37

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31136-9

  • Online ISBN: 978-3-642-31137-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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