LAND COVER CHANGE DETECTION IN A
MEDITERRANEAN AREA (MARITIME SYRIA)
FROM REMOTELY SENSED DATA
lean-Franfois KHREIM and Bernard LACAZE}
Centre d'Ecologie Fonctionnelle et Evolutive, CNRS-BP 5051, 34033
Montpellier Cedex, France
ABSTRACT
In order to detect land cover changes in maritime Syria over the past 16 years
(1977-1993), a multi-temporal normalized difference vegetation index (NDVl)
analysis computed from MSS-Landsat data was performed. A RGB-NDVI image
composite technique was applied to visualize NDVI changes between three
acquisition dates (March 1977, April 1986, March 1993). Qualification of change
was obtained by a combination of this method with a simple classification
comparison procedure. Our results are summarized in a synthetical map revealing
a trend towards a global degradation of vegetation cover.
Detection d'un Changement du Couvert Vegetal des Zones
Mediterraneennes par Teledetection (Syrie Maritime)
RESUME
A partir de trois scenes MSS-Landsat acquises entre 1977 et 1993, une analyse
multidate de l'indice de vegetation normalise (NDVl) a ete realisee afin de
caracteriser Ie changement des grandes unites de l'occupation des sols dans la
region de Syrie maritime. La visualisation en composition coloree rouge vert et
bleu (RVB) combinee a une methode simple de classification a permis de suivre
!'evolution du NDVI et de quantifier l'importance du changement observe. Les
resultats obtenus font ['objet d'une carte syntMtique montrant une degradation
globale de la vegetation dans la region consideree.
1 INTRODUCTION
Nowadays, everyone is aware that the future of the Earth is threatened by the
degradation of ecosystems, the loss of biodiversity and the irrational use of natural
resources. These processes are very pronounced in the Mediterranean Basin where
fragile ecosystems result from the confluence of natural and anthropogenic
factors, leading to erosion, desertification, deforestation, overgrazing, over1 To whom correspondence may be addressed
C. Bardinet et al. (eds.), Geosciences and Water Resources: Environmental Data Modeling
© Springer-Verlag Berlin Heidelberg 1997
MEDITERRANEAN AREA (MARITIME SYRIA)
FROM REMOTELY SENSED DATA
lean-Franfois KHREIM and Bernard LACAZE}
Centre d'Ecologie Fonctionnelle et Evolutive, CNRS-BP 5051, 34033
Montpellier Cedex, France
ABSTRACT
In order to detect land cover changes in maritime Syria over the past 16 years
(1977-1993), a multi-temporal normalized difference vegetation index (NDVl)
analysis computed from MSS-Landsat data was performed. A RGB-NDVI image
composite technique was applied to visualize NDVI changes between three
acquisition dates (March 1977, April 1986, March 1993). Qualification of change
was obtained by a combination of this method with a simple classification
comparison procedure. Our results are summarized in a synthetical map revealing
a trend towards a global degradation of vegetation cover.
Detection d'un Changement du Couvert Vegetal des Zones
Mediterraneennes par Teledetection (Syrie Maritime)
RESUME
A partir de trois scenes MSS-Landsat acquises entre 1977 et 1993, une analyse
multidate de l'indice de vegetation normalise (NDVl) a ete realisee afin de
caracteriser Ie changement des grandes unites de l'occupation des sols dans la
region de Syrie maritime. La visualisation en composition coloree rouge vert et
bleu (RVB) combinee a une methode simple de classification a permis de suivre
!'evolution du NDVI et de quantifier l'importance du changement observe. Les
resultats obtenus font ['objet d'une carte syntMtique montrant une degradation
globale de la vegetation dans la region consideree.
1 INTRODUCTION
Nowadays, everyone is aware that the future of the Earth is threatened by the
degradation of ecosystems, the loss of biodiversity and the irrational use of natural
resources. These processes are very pronounced in the Mediterranean Basin where
fragile ecosystems result from the confluence of natural and anthropogenic
factors, leading to erosion, desertification, deforestation, overgrazing, over1 To whom correspondence may be addressed
C. Bardinet et al. (eds.), Geosciences and Water Resources: Environmental Data Modeling
© Springer-Verlag Berlin Heidelberg 1997