TrDizin İndekslenen Yayınlar

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12597/3198

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Browsing by Author "Abdelkader BENABOU"

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    Prediction by maximum entropy of potential habitat of the cork oak (Quercus suber L.) in Maamora Forest, Morocco
    (2021-01-01) Abdelkader BENABOU; Adnane LABBACI; Said LAARIBYA; Mohamed BIJOU; Assmaa ALAOUI; Halim OUHADDOU; Sezgin AYAN
    In this paper, the maximum entropy (MaxEnt) algorithm was applied to estimate the current and potential distributions of cork oak (Quercus suber L.) in the Maarmora forest of Morocco to provide a basis for its conservation under climate change conditions in the Mediterranean basin. A total of 1,428 field-based spatial records of cork oak locations were used (altitude and 19 bioclimatic environmental variables) to model the potential distribution of the cork oak. The adjusted model had a good predictive quality (area under the curve=0.81). Precipitation during the wettest quarter of the year, seasonality in precipitation, altitude, and seasonal variations in temperature were the key factors determining the distribution of the cork oak in the Maamora forest. Most areas with currently suitable conditions for cork oak were located in the western and central Maamora forest regions, which enjoy a humid bioclimate and receive significant sea spray from the Atlantic Ocean. Moving away from the ocean, the humidity decreases, and the temperature increases, such that the cork oak faces difficulties in adapting and regenerating. The results can be used to identify the high-priority areas for cork oak restoration and conservation of this species against the expected impact of climate change.
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    Spatial Analysis of the Degraded Forest Areas in Idmine ForestMorocco Using Geoscience Capabilities
    (2021-03-01) Abdelkader BENABOU; Sezgin AYAN; Said LAARIBYA; Assmaa ALAOUI
    AbstractAim of study: The aim of the study is to present a diagnosis for the state of Argan forest degradation inMorocco through GIS and remote sensing utilizing Sentinel 2 satellite images of the year 2019 (dated28/08/2019).Area of study: The study was carried out in a forest commune in Idmine, South West Morocco, whichis located in semi-arid bioclimatic region.Material and methods: In the study, two methods were tested. These are; (i) the vegetation indices (VIs)[Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), SoilAdjusted Vegetation Index (SAVI), Brilliance Index (IB)] and their combination and (ii) the supervisedclassification and spectral analysis.Main results: Two methods have given the same results (Kappa coefficient=90%) to describe the stateof forest degradation. Consequently, three classes pertaining to forest degradation within the study areawere; low (34%), medium (44%) and critical degradation (22%).Highlights: This monitoring might help managers to create forest management plans and to evaluate thespeed of deforestation and degradation.