Spatio temporal analysis of vegetation by vegetation indices from multi-dates satellite images: Application to a semi arid area in ALGERIA

摘要

The vegetation index is considered a good indicator of vegetation behavior and can contribute to explain the evolution of vegetation. Hence the problem of our research: to what extent the analysis of the spatial and temporal evolution of vegetation index on a semi-arid region, allows us to understand its evolution and its relationship with the phenomenon of urbanization? The objectives of the study is to analyze the spatio-temporal variations of the vegetation dynamics from a series of available multi-dates satellite images (MSS, LANDSAT ETM +) covering the Laghouat city which is a semi arid area of Algeria (from 1987 to 2006) and to describe the context of overall vegetation indices (NDVI, SAVI, TSAV1) to make a comparative study of fourths vegetation indices, to choose the best index according to the study area using. There are two approaches that reduce the specific contribution of the ground so that the sensitivity of the index for the vegetation: One is based on a modified formulation of the normalized difference vegetation index (NDVI) differentiation respective contributions of red and near infrared bands i.e. SAVI index. On comparing the (NDVI) index with (TVI) which is designed to eliminate negative values and stabilize the variance, we note a clear description of the spectral behavior of vegetation by (TVI) according to its spectral spreading of vegetation histogram which is more important than the (NDVI). As for the (SAVI) index designed for low vegetation cover by chlorophyll is used to reduce the spectral contribution of soil best suited to the semi-arid region. We note an improvement in spectral spreading vegetation compared to the NDVI and TVI, thus improving the description of the vegetation index SAVI. By adopting the adjusted vegetation index SAVI ground and classifying thematic images as following: the 1987 blue, green 2001 and the 2006 red and superposition of three layers, one obtains a thematic map representing the vegetation change from 1987 to 2006. The choice of these three dates specifically related to the fact that the analysis is sensitive to vegetation season (vegetation different from one season to another). To make a comparative study one must choose images, the acquisition dates of which are very close (the same month). This diachronic study (spatio-temporal) allows us the analysis of the rate/rhythm of the extension and the distribution of vegetation.