INIBIOMA   20415
INSTITUTO DE INVESTIGACIONES EN BIODIVERSIDAD Y MEDIOAMBIENTE
Unidad Ejecutora - UE
congresos y reuniones científicas
Título:
On fire regime modelling using satellite TM time series.
Autor/es:
ODDI F., GHERMANDI L. LANORTE A. AND R. LASAPONARA.
Lugar:
Viena, Austria
Reunión:
Congreso; European Geosciences Union; 2009
Resumen:
Geophysical Research Abstracts,
Vol. 11, EGU2009-13211, 2009
EGU General Assembly 2009
© Author(s) 2009
On Fire regime modelling using satellite TM time series
F. Oddi (1), L . Ghermandi (1), A. Lanorte (2), and R. Lasaponara (2)
(1) IMAA - CNR, Italy (lasaponara@imaa.cnr.it), (2) IMAA - CNR, Italy (lasaponara@imaa.cnr.it)
Wildfires can cause an environment deterioration modifying vegetation dynamics because they have the capacity
of changing vegetation diversity and physiognomy. In semiarid regions, like the northwestern Patagonia, fire
disturbance is also important because it could impact on the potential productivity of the ecosystem. There is
reduction plant biomass and with that reducing the animal carrying capacity and/or the forest site quality with
negative economics implications. Therefore knowledge of the fires regime in a region is of great importance to
understand and predict the responses of vegetation and its possible effect on the regional economy. Studies of
this type at a landscape level can be addressed using GIS tools. Satellite imagery allows detect burned areas and
through a temporary analysis can be determined to fire regime and detecting changes at landscape scale. The
study area of work is located on the east of the city of Bariloche including the San Ramon Ranch (22,000 ha)
and its environs in the ecotone formed by the sub Antarctic forest and the patagonian steppe. We worked with
multiespectral Landsat TM images and Landsat ETM + 30m spatial resolution obtained at different times. For the
spatial analysis we used the software Erdas Imagine 9.0 and ArcView 3.3. A discrimination of vegetation types
has made and was determined areas affected by fires in different years. We determined the level of change on
vegetation induced by fire. In the future the use of high spatial resolution images combined with higher spectral
resolution will allows distinguish burned areas with greater precision on study area. Also the use of digital
terrain models derived from satellite imagery associated with climatic variables will allows model the relationship
between them and the dynamics of vegetation.