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H. Moutahir et al. 2010. Application of remote sensing to assess wildfire impact
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2. Methodology
2.1 Study area
The chosen area is located about 70 km south east of the city of Valencia (figure 1). The
dominant vegetation type covering the landscape are the evergreen shrublands (with abundance
of Quercus coccifera) and pine woodlands (Pinus halepensis) with different degrees of
development and species compositions (Abdel Malak, 2009). This area suffered several fires in
the last 25 years.
2.2 Methodology
In this research we follow the same methodology used by Chuvieco (1996, 2007) in his study to
measure the landscape structure using remote sensing images. Chuvieco based his research on
only two images in order to compare the landscape structure before and after the fire. However,
for this research twelve Landsat TM and ETM+ images were used in order to obtain a more
accurate assessment of the evolution of landscape structure (table 1).
The twelve satellite images used have been downloaded for free from the USGS Global
Visualization Viewer (http://glovis.usgs.gov/.). We did not perform any geometric correction to
these images because the level of their correction was already satisfactory. Nevertheless, in
order to compare them a radiometric normalization was carried out using the Pseudo-Invariant
Feature Normalization method (Scott et al., 1988).
To detect the burnt area we used a combination of the NDVI bands calculated from the 12
images and stretched between 0 and 200. Displaying the NDVI band of the first year (1984) in
both the red and the blue channels and displaying the rest of the years in the green channel, we
can detect the burnt zone as a magenta colored area due to the low values of NDVI in the green
channel.
In order to quantify the landscape structure two kinds of measures were applied:
-measures applied to the NDVI images as continuous values: (the standard deviation through a
profile) which measures the spatial contrast of the image.
-measures applied to intervals of NDVI which measure the spatial structure of a territory.
3. Results
Analyzing only two images, one image before and one after the fire, we obtained the same
results as Chuvieco did in 1996. In both profiles (10.5km and 4.5km of length) chosen within
two different burnt areas at different times (the first area was burnt in 1986 and the second one
was burnt in 1991), we observed that the standard deviation decrease after the fire: 9% in the
first profile and 3% in the second profile (table 2&3; figure 2&3). This result indicates that the
fire tends to homogenize the landscape. However, analyzing the rest of images we observed that
the NDVI and the standard deviation increase with time while the vegetation recover (table
2&3).
The second type of landscape structure measures was applied to a window of 1473.7 ha of an
area burnt in 1986. These measures were applied to classified images of 10 intervals of NDVI
obtained from an automatic segmentation. The mean area of patches and the index of patch
dominance increased while the number of patches, the density of patches and the mean diversity
Forest Landscapes and Global Change-New Frontiers in Management, Conservation and Restoration. Proceedings of the IUFRO Landscape Ecology
Working Group International Conference, September 21-27, 2010, Bragança, Portugal. J.C. Azevedo, M. Feliciano, J. Castro & M.A. Pinto (eds.)
2010, Instituto Politécnico de Bragança, Bragança, Portugal.