Abstract
Providing constantly updated information on vegetation serves as a basis for studies of natural resources and ecological issues. This paper discusses the question related to an appropriate season(s) for classification vegetation cover in the Mediterranean region and detecting its changes using Landsat imagery. Autumn, spring, and multi-seasonal satellite images, captured in 2017, were used to classify vegetation cover in a part of the Lattakia province, Syria. The satellite images were classified using the random forest algorithm, and high spatial resolution satellite images Google Earth Pro were used as reference data. The results indicate better effectiveness of the autumn images over spring ones for vegetation cover classification with 73.6% and 62.4% overall accuracy, respectively. In addition, a comparison of autumn and multi-seasonal Landsat images indicates no significant statistical difference in the accuracy of vegetation cover classification at the significance level of 0.05, which illustrates the effectiveness of using autumn images to classify the vegetation cover of the Mediterranean region. Furthermore, the obtained results show the necessity of using additional features as the spectral channels may not be sufficient for mapping vegetation cover in the Mediterranean region with high accuracy.
Highlights
The vegetation cover of the Earth, being a source of valuable biological resources, simultaneously performs several functions as a regulator of fundamental processes of energy and substance exchange on the planet, plays an important ecological and sociocultural role for humanity [1]
The calculated value of |z|=5.36 is higher than |z|=1.95 – the tabulated value. These results indicate a significant statistical difference in the accuracy of using autumn and spring satellite images for vegetation cover classification at the significance level of 0.05
The best results to classify the vegetation cover in the study area were obtained using multi-seasonal satellite images with an overall accuracy of 76.4%, followed by autumn images – 73.6%, and spring ones – 62.4%
Summary
The vegetation cover of the Earth, being a source of valuable biological resources, simultaneously performs several functions as a regulator of fundamental processes of energy and substance exchange on the planet, plays an important ecological and sociocultural role for humanity [1]. Landsat images are one of the most widely used data for mapping vegetation cover and detecting its changes for the following reasons: 1) High quality of geometric and radiometric corrections of Landsat data, which allows their use without the need for initial processing procedures. The main problem with this approach lies in the difficulty of obtaining homogeneous multi-season images in different years, which leads to restrictions in the use of multi-season images to detect changes in vegetation cover
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