Identifying saline wetlands in an arid desert climate using Landsat remote sensing imagery. Application on Ouargla Basin
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ORIGINAL PAPER
Identifying saline wetlands in an arid desert climate using Landsat remote sensing imagery. Application on Ouargla Basin, southeastern Algeria Fethi Medjani 1 & Belkacem Aissani 1 & Sofiane Labar 2 & Mohamed Djidel 1 & Danielle Ducrot 3 & Antoine Masse 3 & C. Mei-Ling Hamilton 4
Received: 14 December 2015 / Accepted: 17 March 2017 # Saudi Society for Geosciences 2017
Abstract Supervised and unsupervised satellite image classifications have progressed greatly in recent years. However, discrimination difficulties still remain among classes that directly affecting data extraction and surface mapping accuracy. The Ouargla region in southeastern Algeria is intersected by wadis, where direct communication between the shallow groundwater table and these dry, overlying ephemeral stream beds exists. Underflowing groundwater exfiltrates into lowlying aeolian blowouts or endorheic basins forming oases, chotts, and sebkhas, commonly known as saline wetlands. These wetlands are becoming increasingly vulnerable to anthropogenic stress, resulting in significant water degradation. Wetland microclimates are very important to arid regions, as they promote oasis ecosystem sustainability and preservation. High water salinity in these ecosystems, however, directly affects flourishing habitat and undermines successful desert oasis development. The objective of this work is to choose the best classification method to identify saline wetlands by comparison between the different results of land use mapping within the Ouargla basin. Landsat ETM+ (2000) satellite imagery, using visual analysis with colored compositions, has
* Fethi Medjani [email protected]
1
Laboratory of Geology of the Sahara, University Kasdi Merbah Ouargla, BP 511 30000, Ouargla, Algeria
2
Faculty of Natural and Life Sciences, University of Chadli Bendjedid El-Tarf, P73, 36000, El-Tarf, REDD Lab, Annaba, Algeria
3
Biosphere Space Studies Centre BCESBIO^, University of Paul Sabatier, 18 Avenue E. Belin, bpi 2801, 31401 Toulouse Cedex 9, France
4
P.O. Box 10271, Bakersfield, CA 93389, USA
identified various forms of saline wetlands in the Ouargla region desert environment in southeast Algeria. The results show that supervised classification is validated in the identification of Saharan saline wetlands, and that support vector machine (SVM) algorithm presents the best overall accuracy. Keywords Remote sensing . Classification . Mapping . Sebkha . Wet saline soils . Sahara
Introduction The Ramsar Convention, also known as the BConvention of Wetlands,^ has great international importance. It is an intergovernmental treaty which provides the framework for national action and international cooperation for the conservation and wise use of wetlands and their resources. As such, the Ramsar classification system has been used to inventory wetlands areas on a global scale. The several hundred countries that have signed the convention since 1971 have used it for environmental purposes. Yet, wetland identification and delineation still remain vague (Cos
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