Please use this identifier to cite or link to this item: https://dspace.univ-ghardaia.edu.dz/xmlui/handle/123456789/5696
Title: Utilisation des systèmes d’information géographique (SIG) et de la télédétection dans la gestion des ressources naturelles en milieu saharien: Cas de la région de Ghardaïa
Other Titles: Use of the geographic information systems (GIS) and remote sensing in natural resources management on Saharan environment: Case of Ghardaia region
استخدام نظم المعلوماتية الجغرافية (GIS) والاستشعار عن بعد في إدارة الموارد الطبيعية في البيئة الصحراوية: دراسة حالة منطقة غرداية.
Authors: OULAD HEDDAR, Meriem
Keywords: SIG, sensibilité, ensablement, MEDALUS, Télédétection, régions arides, Ghardaïa
GIS, sensitivity, silting, MEDALUS, Remote sensing, arid regions, Ghardaïa
نظم المعلوماتية الجغرافية ، الحساسية ، زحف الرمال ، MEDALUS ، الاستشعار عن بعد ، المناطق الجافة، غرداية.
Issue Date: 21-Oct-2021
Publisher: Faculté des Sciences de la Nature et de la Vie et Sciences de la Terre - Université de Ghardaïa
Abstract: The region of Ghardaïa, located in the northern Algerian Sahara has experienced hazards linked to silting up which have continued to increase in recent years. This problem constitutes an obstacle to the development of the region since it faces a large erg (erg El Anaguer). The MEDALUS model was used in this present work to assess the sensitivity of areas to silting up. The mapping of the sensitivity index was developed following the weighted combination of four major indicators directly linked to the phenomenon studied. The quality indices for each layer of information (climate, soil, vegetation and development) were compiled to subsequently obtain a thematic summary map. The results of the sensitivity map lead us to note that 86.31% of the mapped area are considered to be fragile areas (sensitive to silting up), while 9.30% of the areas are critical (very sensitive to silting up). The so-called potential zones represent only 4.39% of the total area in this present study. Remote sensing has been also employed in this present work using supervised post-classification methods in order to detect changes in land cover classes between the two periods 2000 and 2015 using Landsat satellite images from two different sensors (ETM + and OLI8). The results obtained show an expansion of 166.4% of urban areas, mainly linked to the population explosion, industrial and agricultural activities.
URI: https://dspace.univ-ghardaia.edu.dz/xmlui/handle/123456789/5696
Appears in Collections:Thèses de Doctorat

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