fire risk assessment (both are related to pre-fire
management), fire detection (during the fire),
and fire effects assessment (post-fire). A brief
description of the work carried out in these
areas follows.
2. SHORT-TERM FIRE RISK MAPPING
Better methods to evaluate the probability of
fire out breaks would significantly reduce fire
incidence by intensifying aerial or terrestrial
vigilance, by forbidding certain risky activities
or by adapting the level of alertness of fire
suppression resources. Fire danger estimation
demands frequent monitoring of vegetation
stress. Vegetation moisture is a particularly
difficult parameter to estimate as it accounts for
little spectral variation with respect to other
environmental factors (Cohen, 1991).
However, spectral characterisation of
vegetation stress is possible if temporal profiles
are derived, and the contrast between living
and dead components is emphasised.
The most common methodology for the
estimation of vegetation water stress has been
the analysis of vegetation indices (VI)
multitemporal series. VI has proven to be
related to critical physiological variables, such
as absorbed radiation (APAR), Green biomass
or Leaf Area Index (LAI). Therefore, these VI
provide a good indication of vegetation
healthiness. On the other hand, decrements of
VI are related to reduction of plant vigour and
greenness which are also linked with vegetation
moisture content (Paltridge and Barber, 1988).
An alternative to the use of VI series for
vegetation moisture estimation is to follow the
thermal dynamism of the vegetation cover.
Ratio of actual and potential evapotranspiration
(LE/LEp) appears to be a good indicator of
canopy water status. This index has been
successfully applied to fuel moisture estimation
from NOAA-AVHRR data (Vidal et al.,
1994). A combination of surface temperature
and NDVI has also been successfully applied to
46
fire danger estimation in the South of France
(Prosper-Laget et al., 1994).
3. LONG-TERM FIRE RISK MAPPING
Long-term risk refers to permanent factors
associated to fire ignition or propagation, such
as topography, vegetation structure, human
activities or weather patterns. Therefore, the
integration — capabilities of Geographic
Information Systems (GIS) makes them a
suitable tool for mapping fire risk. These maps
are quite critical for a rational management of
forest areas, since fire protection programs will
be spatially and temporally oriented to the areas
labelled as having high risk.
Several GIS applications have been developed
in the last decade to improve management of
fire risk, specially to the generation of GIS-
based risk maps. Most of these models are
locally oriented, so they cover a small area at
high resolution (typically from 50 to 100 meter
grid size: Burgan and Shasby, 1984; Yool et
al., 1985; Chuvieco and Congalton, 1989).
However, there are also some experiences with
global, low resolution, fire danger maps
(Werth et al., 1985; McKinley et al., 1985).
The critical point of these systems is the
vegetation layer. Several studies have found a
close correlation between the spread and
intensity of the fire and fuel characteristics,
such as size, plant moisture, compactness and
density (Burgan and Rothermel, 1984). Several
papers have explored the use of satellite remote
sensing to generate these fuel models through
digital image processing. Most have worked
with Landsat-MSS or TM images (Salazar,
1982), but there are also interesting experiences
using low resolution sensors like NOAA-
AVHRR (Miller and Johnston, 1985). Finally,
radar data can provide complementary
information too for fuel mapping, particularly
at local scale, since it is very sensitive to
temporal and spatial variation of the canopy
biomass.
International Archives of Photogrammetry and Remote Sensing. Vol. XXXI, Part B6. Vienna 1996
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