Review article
https://doi.org/10.32909/kg.24.43.3
Use of Remote Sensing and GIS to Diagnose and Assess the Current Situation of Acacia Raddiana Stands / Case of the Maider BV (Morocco)
Otman Tamri
; Department of Geology, College of Geosceinces, University of Ibn Tofaïl, Kenitra, Morocco
*
Saïd Chakiri
; Department of Geology, College of Geosceinces, University of Ibn Tofaïl, Kenitra, Morocco
Allal Labriki
orcid.org/0009-0002-3328-740X
; Department of Geology, College of Geosciences and Applications, University of Sciences Ben M'Sik, Casablanca, Morocco
Mohammed Amine Zerdeb
; Department of Geology, College of Geosceinces, University of Ibn Tofaïl, Kenitra, Morocco
* Corresponding author.
Abstract
The Maider region in southeastern Morocco is a hyper-arid zone where annual rainfall rarely exceeds 120 mm. Its sparse natural vegetation is dominated by Acacia raddiana, a keystone species vital for local ecological stability. This study aims to assess the current status and spatial dynamics of Acacia stands using high-resolution Landsat 9 imagery and GIS tools, to inform conservation strategies against ongoing degradation.
Results reveal that Acacia covers approximately 370,287 hectares, representing 31% of the lower Maider basin. Sparse annual vegetation, mainly xerophytic Chenopodiaceae, is located along the slopes of the Saghro and Ougnate ranges, whereas much of the terrain is bare soil. Commune-level analysis highlights significant qualitative vegetation decline in the southeastern basin, confirmed by high-resolution imagery. However, long-term NDVI GIMMS/AVHRR data were limited in detecting these localized changes due to their coarse spatial resolution and sensitivity to ephemeral vegetation.
This study’s originality lies in the integration of recent Landsat 9 data with a 25-year NDVI time series to monitor the dynamics of Acacia raddiana in a degraded arid environment. The combined use of density-based vegetation classification and spatial analysis at the administrative level offers novel insights into vegetation loss and contributes to practical land restoration planning.
Keywords
Acacia Raddiana; GIS, Landsat Images; Maider Basin; Remote sensing
Hrčak ID:
334225
URI
Publication date:
2.6.2025.
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