rental
1997.
ugust
g and
as, 49
d by
n the
digäo
imum
heme
on, J.
offers
zes in
mmon
mmon
fires
zation
(OAA
S-1C
Indian
tellite
des a
green
f the
short-
e
S
spectrum, and a spatial resolution of 70 m in t
wave infra-red (SW IR).
FIRE AREA
oF
Figure 1. (a) LISS-3 image before the fire; (b) LISS
image after the fie.
However, the SW IR was not available due to after launch
problems in the LISS-3 sensor. Imagery before (1* of
August, 1997) and after the fire (12^ of October, 997
was acquired and used in this study. Pre- and po
images showing the area where the fire took place are
presented in Figures 1 (a) and (b) respectively.
Although the location of the fire was know, the ability
the contextual algorithm for fire detection developed t
Flasse and Ceccato (1996) was tested in this re gic
Given the large size of the fire, the fire was easily
detected by the algorithm. This algorithm will be used in
the very near future for fire detection across the
Mediterranean basin. A pilot study to test the potential of
this algorithm for fire detection in Mediterr
landscapes is being carried out at the mom ent with
statistics provided by the AEA over the A
region.
ES
ic on.
A methodology for burnt area mapping
Miguel-Ayanz et al. (1998) was tested on
methodology consists in the use of a pre-fire ima
used to select forested areas by means of th
spectral transform. Next, a post-fire image is
discriminate potential burnt areas by means of a spectral
transformation named Burnt Index (BI). The intersection
of both masks results therefore in the forested areas that
have been burnt. This result is then intersect |
CORINE layer to evaluate the fire damage.
Intemational Archives of Photogrammetry and
>
ote densing. Vol. AAXL, art
Ren
10