Fas’ın Idmine Ormanı’ndaki Bozulmuş Orman Alanlarının Yerbilim Yeteneklerini Kullanarak Mekansal Analizi

Year 2021, , 1 - 11, 03.04.2021

Said Laarıbya Assmaa Alaouı Sezgin Ayan Abdelkader Benabou

https://doi.org/10.17475/kastorman.908568

Cited By: 1

Abstract

Çalışmanın Amacı: Çalışmanın amacı, 2019 yılının (28/08/2019 tarihli) Sentinel 2 uydu görüntülerini kullanarak CBS ve Uzaktan Algılama yoluyla orman bozulma durumu için bir tanı sunmaktır.
Çalışma Alanı: Çalışma, yarı kurak biyoklimatik bölgede bulunan Güney Batı Fas'taki Idmine orman komününde gerçekleştirilmiştir.
Materyal ve Yöntem: Bu çalışmada, iki yöntem denenmiştir. Bunlar; (i) Vejetasyon indisleri (VIs) [Normalize Fark Vejetasyon İndeksi (NDVI), Normalize Fark Su İndeksi (NDWI), Toprak-uyarlı Vejetasyon İndeksi (SAVI), Parlaklık İndeksi (IB)] ve bunların kombinasyonu ile (ii) Denetimli sınıflandırma ve spektral analizdir.
Temel sonuçlar: Orman degradasyon durumunu tanımlamak için iki yöntem aynı sonuçları (Kappa katsayısı=%90) vermiştir. Sonuç olarak, çalışma alanı içindeki orman degredasyonuna ilişkin üç sınıf; düşük (%34), orta (%44) ve kritik bozulma (%22)’dır.
Araştırma Vurguları: Bu izleme, yöneticilerin orman yönetim planları oluşturmasına ve ormansızlaşma ve orman degredasyonu hızını değerlendirmesine yardımcı olabilir.

Keywords

CBS, Uzaktan Algılama, Vejetasyon Indeksi, Degradasyon

Spatial Analysis of the Degraded Forest Areas in Idmine Forest-Morocco Using Geoscience Capabilities

Abstract

Aim of study: The aim of the study is to present a diagnosis for the state of Argan forest degradation in Morocco through GIS and remote sensing utilizing Sentinel 2 satellite images of the year 2019 (dated 28/08/2019).
Area of study: The study was carried out in a forest commune in Idmine, South West Morocco, which is 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), Soil-Adjusted Vegetation Index (SAVI), Brilliance Index (IB)] and their combination and (ii) the supervised classification and spectral analysis.
Main results: Two methods have given the same results (Kappa coefficient=90%) to describe the state of forest degradation. Consequently, three classes pertaining to forest degradation within the study area were; low (34%), medium (44%) and critical degradation (22%).
Highlights: This monitoring might help managers to create forest management plans and to evaluate the speed of deforestation and degradation.

Keywords

GIS, Remote Sensing, Vegetation Index, Degradation

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