214
Regional Environmental Changes: Application to Soil Erosion Modeling
The statistical comparison of the different land cover classes between 1977 and
1993 shows that maritime Syria experienced a severe decrease in vegetation cover
mainly due to increased agricultural and urban activities because of rapidly
expanding population. In the 1977-1993 time interval, twelve percent of the forest
vegetation (high and medium density) changed class with a trend from a forestmaquis to a maquis-grassland signature, accounted for by physical processes such
as fire, lightning, disease. Non-vegetable elements which we define as regrouping
urban infrastructures and bare soils show a surface increase in the range of 7%
between 1977 and 1993. The multi-temporal NDVI analysis demonstrates the
important changes brought about in maritime Syria during the 1977-1993 period.
These changes reveal a continuous trend towards degradation of the vegetation
cover. This phenomenon can be explained by man's direct or indirect action.
Through a mechanism of bio-geophysical retroaction, the increase in bare areas
due to man's action can generate significant climatic changes (Hobbs, 1990). This
study permits an appreciation of the magnitude of the degradation processes in
maritime Syria over the last 16 years. This situation underlines the importance of
constant monitoring of the land surface state in Mediterranean regions. Multitemporal remotely sensed data are likely to make an important contribution to a
better understanding of global and regional environmental change.
KEYWORDS
Remote sensing, Mediterranean region, degradation, vegetation cover, satellite
image processing, GIS, vegetation index, ecosystems, biodiversity, forest
degradation.
REFERENCES
[I]
Abi-Saleh, B., Etude phytosociologique, phytodynamique et ecologique des peuplements
sylvatiques du Liban. These Univ. Aix-Marseille. 185p. (1978).
[2]
Graetz, P., Remote sensing of terrestrial ecosystem structure: an ecologist's pragmatic view.
In Remote Sensing of biosphere functioning, R.Hobbs and H. Mooney eds. Springer-Verlag,
New York, pp 5-30 (1990).
[3]
Hobbs, R., Remote sensing of spatial and temporal dynamics of vegetation. In Remote
Sensing of biosphere functioning. R. Hobbs and H. Mooney eds. Springer-Verlag, New
York, pp 203-219 (1990).
[4]
Khreim, J.F., Lacaze, B., Cartographie de la vegetation forestiere mediterraneenne dans la
region du Baer-Bassit (Nord-Ouest de la Syrie) a partir des donnees Landsat-TM multidates.
Bull. Comite Fran~ais de Cartographie, 127-128: 130-135 (1991).
[5]
Quezel, P., Barbero, M., Carte de la vegetation potentielle de la region mediterraneenne.
Feuille N 1: Mediterranee Orientale. CNRS Ed. France (1985).
[6]
Rouse, J.W., Haas, R.H., Shell, J.A., Deering, D.W. and Harlan, J.C., Monitoring the vernal
advancement and retrogradation (Greenwave effect) of natural vegetation. NASNGDFC TYPE
III Final Report, Greenbelt, Mol, 371 p. (1974).
[7]
Sader, S.A., Winne, J.e., RGB-NDVI color composite for visualizing forest change
dynamics. Int. J. Remote Sensing, vol 13, 16:3055-3067 (1992).
[8]
Schott, J.R., Salaggio, C., Volcoch, W.J., Radiometric scene normalization using
pseudoinvariant features. Remote Sensing of Environment, 26: 1-16 (1988).
[9]
Singh, A., Digital change detection techniques using remotely sensed data. Int. J. remote
Sensing, vol 10, 6:989-1003 (1989).
Regional Environmental Changes: Application to Soil Erosion Modeling
The statistical comparison of the different land cover classes between 1977 and
1993 shows that maritime Syria experienced a severe decrease in vegetation cover
mainly due to increased agricultural and urban activities because of rapidly
expanding population. In the 1977-1993 time interval, twelve percent of the forest
vegetation (high and medium density) changed class with a trend from a forestmaquis to a maquis-grassland signature, accounted for by physical processes such
as fire, lightning, disease. Non-vegetable elements which we define as regrouping
urban infrastructures and bare soils show a surface increase in the range of 7%
between 1977 and 1993. The multi-temporal NDVI analysis demonstrates the
important changes brought about in maritime Syria during the 1977-1993 period.
These changes reveal a continuous trend towards degradation of the vegetation
cover. This phenomenon can be explained by man's direct or indirect action.
Through a mechanism of bio-geophysical retroaction, the increase in bare areas
due to man's action can generate significant climatic changes (Hobbs, 1990). This
study permits an appreciation of the magnitude of the degradation processes in
maritime Syria over the last 16 years. This situation underlines the importance of
constant monitoring of the land surface state in Mediterranean regions. Multitemporal remotely sensed data are likely to make an important contribution to a
better understanding of global and regional environmental change.
KEYWORDS
Remote sensing, Mediterranean region, degradation, vegetation cover, satellite
image processing, GIS, vegetation index, ecosystems, biodiversity, forest
degradation.
REFERENCES
[I]
Abi-Saleh, B., Etude phytosociologique, phytodynamique et ecologique des peuplements
sylvatiques du Liban. These Univ. Aix-Marseille. 185p. (1978).
[2]
Graetz, P., Remote sensing of terrestrial ecosystem structure: an ecologist's pragmatic view.
In Remote Sensing of biosphere functioning, R.Hobbs and H. Mooney eds. Springer-Verlag,
New York, pp 5-30 (1990).
[3]
Hobbs, R., Remote sensing of spatial and temporal dynamics of vegetation. In Remote
Sensing of biosphere functioning. R. Hobbs and H. Mooney eds. Springer-Verlag, New
York, pp 203-219 (1990).
[4]
Khreim, J.F., Lacaze, B., Cartographie de la vegetation forestiere mediterraneenne dans la
region du Baer-Bassit (Nord-Ouest de la Syrie) a partir des donnees Landsat-TM multidates.
Bull. Comite Fran~ais de Cartographie, 127-128: 130-135 (1991).
[5]
Quezel, P., Barbero, M., Carte de la vegetation potentielle de la region mediterraneenne.
Feuille N 1: Mediterranee Orientale. CNRS Ed. France (1985).
[6]
Rouse, J.W., Haas, R.H., Shell, J.A., Deering, D.W. and Harlan, J.C., Monitoring the vernal
advancement and retrogradation (Greenwave effect) of natural vegetation. NASNGDFC TYPE
III Final Report, Greenbelt, Mol, 371 p. (1974).
[7]
Sader, S.A., Winne, J.e., RGB-NDVI color composite for visualizing forest change
dynamics. Int. J. Remote Sensing, vol 13, 16:3055-3067 (1992).
[8]
Schott, J.R., Salaggio, C., Volcoch, W.J., Radiometric scene normalization using
pseudoinvariant features. Remote Sensing of Environment, 26: 1-16 (1988).
[9]
Singh, A., Digital change detection techniques using remotely sensed data. Int. J. remote
Sensing, vol 10, 6:989-1003 (1989).