7th Workshop on Forest Fire Management - EARSeL, European ...
7th Workshop on Forest Fire Management - EARSeL, European ...
7th Workshop on Forest Fire Management - EARSeL, European ...
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110<br />
II - VALIDATION OF RS PRODUCTS FOR FIRE MANAGEMENT<br />
In this work we compare eight different spectral indices from the bibliography,<br />
obtained from MODIS sensor <strong>on</strong> board Terra satellite, as fire risk indicators<br />
in the Galicia regi<strong>on</strong>.<br />
2 - Study site and materials<br />
The study site in this work is the Galicia regi<strong>on</strong> placed at the Northwest of<br />
Spain. About the 70% of the Galician territory is occupied by forest areas.<br />
Despite its humid and rainy climate, Galicia is the Spanish regi<strong>on</strong> with the<br />
largest number of forest fires.<br />
The organisms for the management of fire predicti<strong>on</strong> and extincti<strong>on</strong> tasks<br />
use a grid as a basis dividing Galicia in 360 10-km side squares (UTM 29).<br />
Also, historic fire data are provided at the same spatial resoluti<strong>on</strong>.<br />
Therefore, informati<strong>on</strong> <strong>on</strong> vegetati<strong>on</strong> stage has been adapted to this spatial<br />
resoluti<strong>on</strong>, using the same grid. As seen in Sánchez et al. (2009), the<br />
huge majority of fire events take place from February to October. Thus, the<br />
analysis is c<strong>on</strong>strained to this period. The temporal resoluti<strong>on</strong> chosen is 16<br />
days, as the vegetati<strong>on</strong> stage does not change significantly within this twoweek<br />
period. The vegetati<strong>on</strong> informati<strong>on</strong> is obtained from the products<br />
MOD09 A1 and MOD13 Q1 provided by the MODIS service.<br />
3 - Methodology<br />
3.1 - Pre-processing of the MODIS images<br />
In this work we use images from the MOD09 A1 product, (8 days temporal<br />
resoluti<strong>on</strong> and 500 m spatial resoluti<strong>on</strong>), as well as images from the MOD13<br />
Q1 product (16 days temporal resoluti<strong>on</strong> and 250 m spatial resoluti<strong>on</strong>).<br />
Within a satellite scene, there can be pixels with wr<strong>on</strong>g values due to the<br />
presence of clouds or because of some problem with the detector. Therefore<br />
it is essential to perform a filtering process. We use the informati<strong>on</strong> c<strong>on</strong>tained<br />
in the quality band of each product and informati<strong>on</strong> of the Corine<br />
Land Cover for the filtering process. Afterwards, we carry out a filling. Then<br />
we make a compositi<strong>on</strong> of two c<strong>on</strong>secutive images in order to obtain <strong>on</strong>e<br />
image each 16 days. Finally we apply the 10x10 km grid and calculate a<br />
value for each cell.<br />
3.2 - Relati<strong>on</strong> between fire frequency and the index variati<strong>on</strong>s<br />
The spectral indices chosen for the present study are: NDVI (Rouse et al.,<br />
1974), SAVI (Huete, 1988), NDII (Hunt and Rock, 1989), GEMI (Pinty and<br />
Verstraete, 1992), NDWI (Gao, 1996), VARI (Gitels<strong>on</strong> et al., 2002), EVI<br />
(Huete et al., 2002) and GVMI (Ceccato et al., 2002). This selecti<strong>on</strong> is