Remotely Sensed Phenology Monitoring and Land-cover Classification for the Localization of the Endemic Argan Tree in the Southern-west of Morocco

Sebbar, Badr-eddine; Moumni, Aicha; Lahrouni, A.; Chehbouni, Abdelghani; Belghazi, Tarik; Maksoudi, B.

doi:10.1080/10549811.2021.1897018

Cited by 9 publications

(6 citation statements)

References 19 publications

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“…After preprocessing, the data was ready for classification. Support Vector Machine (SVM) classification was used in this step to categorize different land cover or vegetation types based on the available data layers (El Moussaoui et al 2021, Sebbar et al 2022.…”

Section: Svm Classification and Accuracy Assessmentmentioning

confidence: 99%

“…Our efforts encompass a range of methodologies involving machine learning algorithms, all aimed at identifying the optimal approach to achieve the highest classification accuracy. One such study authored by Sebbar et al (2022) focused on the accurate mapping and precise localization of argan trees in the Smimou region. To achieve this, optical data from Sentinel-2 imagery was used and a dual classification process was performed to overcome the separability challenges.…”

Section: Introductionmentioning

confidence: 99%

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Assessing the influence of different Synthetic Aperture Radar parameters and Digital Elevation Model layers combined with optical data on the identification of argan forest in Essaouira region, Morocco

El Moussaoui,

Moumni,

Lahrouni

2024

iForest

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Forest resource conservation necessitates a deeper understanding of forest ecosystem processes and how future management decisions and climate change may affect these processes. Argania spinosa (L.) Skeels is one of the most popular species in Morocco. Despite its ability to survive under harsh drought, it is endangered due to soil land removal and a lack of natural regeneration. Remote sensing offers a powerful resource for mapping, assessing, and monitoring the forest tree species at high spatio-temporal resolution. Multi-spectral Sentinel-2 and Synthetic Aperture Radar (SAR) time series combined with Digital Elevation Model (DEM) over the Argan forest in Essaouira province, Morocco, were subjected to pixel-based machine learning classification and analysis. We investigated the influence of different SAR data parameters and DEM layers on the performance of machine learning algorithms. In addition, we evaluated the synergistic effects of integrating remote sensing data, including optical, SAR, and DEM data, for identifying argan trees in the Smimou area. We collected data from Sentinel-2, Sentinel-1, SRTM DEM, and ground truth sources to achieve our goal. Testing different SAR parameters and integrating DEM layers of different resolutions with other remote sensing data showed that the Lee Sigma filter with a size of 11×11 and a DEM layer of 30 m resolution gave the best results using the Support Vector Machine algorithm. Significant improvements in overall accuracy (OA) and kappa index (K) were observed in the following phase. After applying a smoothing technique, the combined use of two Sentinel constellation products improved map accuracy and quality. For the best scenario (VV+NDVI), the OA was 88.32% (K = 0.85), while for scenarios NDVI+DEM and VH+NDVI+DEM, the OAs were 93.25% (K = 0.91) and 93.01% (K = 0.91), respectively. Integrating a DEM layer with SAR and optical data has significantly improved the accuracy in the classification of vegetation types, especially in our study area which is characterized by high environmental heterogeneity.

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Section: Svm Classification and Accuracy Assessmentmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Assessing the influence of different Synthetic Aperture Radar parameters and Digital Elevation Model layers combined with optical data on the identification of argan forest in Essaouira region, Morocco

El Moussaoui,

Moumni,

Lahrouni

2024

iForest

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“…However, the overexploitation of the argan tree and the climate change has led to a regression of its surface, supplemented with the rarity of natural regeneration (Defaa et al, 2015;Ferradous, 2018). So, to preserve and promote the sustainability of the current argan ecosystem forest, the only solution is reforestation (Hachemi et al, 2021;Sebbar et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Argan (Argania spinosa (L.) Skeels) Bazı Termal Şok Ön İşlemleri Altında Tohum Çimlenmesi

ALI

HACHEMI

Moumni

et al. 2022

Kastamonu Üniversitesi Orman Fakültesi Dergisi

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Aim of study:The objective of this study was to optimize the germination of A. spinosa seeds after different physical pretreatments by thermal shock to establish a simple, effective, and less expensive procedure.Area of study: The study was conducted in the laboratory on seeds from four regions of Morocco (Aoulouz, Essaouira, Sidi Bou Othmane, and Boulaouane).Material and methods: The seeds were dried and stored. Before the launching of the experimental protocol, they were dehulled and applied each their pre-treatment for the four provenances. The pretreatment used are the following. C: control without thermal shock, HC1: freezing, HC2: hot water, HC3: freezing + hot water.Main results: The results showed that the onset of germination of argan seeds subjected to pretreatment HC3 was reduced by 2 days on mean compared to seeds that were subjected to pretreatment (C). The application of the cold or hot pretreatment allowed us to reach up to 82% of the final percentage of germination. However, the combination of two pretreatments allowed us to reach up to 100% of the final germination percentage.Highlights: Freezing combined with hot water significantly improved the germination of A. spinosa seeds. This pretreatment could be recommended in the nursery for practitioners.

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“…Is likely confronted with enhanced climate variability, climate change and socio-economic constraints in the future [9]. The current exploitation methods only aggravate the ecological situation of the natural resources in this reserve, where the argan trees are the main component threatened by the overexploitation of plant resources, the clearing of soils, and the absence of natural regeneration [10]. Confronted with the problem of the degradation of the vegetation cover, the Provincial Directorate of Water and Forests and the Fight against Desertification of Agadir (DPEFLCD) has launched a programme for the regeneration and development of the argan trees plantation through permanently fencing of some places of the argan trees reserve.…”

Section: Introductionmentioning

confidence: 99%

Fencing land impacts on plant biodiversity and argan trees dynamic in the Ida-Ou-Tanane (central western of Morocco)

Haddou

Caid

Aydda

et al. 2022

IOP Conf. Ser.: Earth Environ. Sci.

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The argan trees are subject to strong anthropgenic pressure that prevents its natural regeneration. This study aims to evaluate the effect of lands fencing on the redynamization of the argan trees through analyzing and comparing the specific richness in two closer parcels. The first parcel have been fenced since 2004, whereas the second one is an open land. In this study, the floristic diversity indices were investigated and compared based on field inventory from both parcels. The results obtained show the beneficial effect of the fence on the dynamics of the vegetation. The plant specific richness is higher for the fenced parcel than unfenced parcel (37 and 21 species, respectively). For the fenced parcel, the maximum diversity index is about 3.61, while it is about 3.04 for the unfenced parcel. The Shannon-Weaver index (H’) and the evenness (E) are also higher for the fenced parcel where the cover rate is 57% compared to 32% for the unfenced parcel. The average of the computed argan trees, in the fenced parcel, is 116 trees/ha of size ranging between 2 to 5 m. For the unfenced parcel, the average is 83 trees/ha of size of 4 m. Additionally, inside the fenced parcel, the natural regeneration by seedling is well marked, where considerable number of argan trees towere identified during field survey. These results highlight the importance to use fencing in the generation of the endemic plants.

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Remotely Sensed Phenology Monitoring and Land-cover Classification for the Localization of the Endemic Argan Tree in the Southern-west of Morocco

Cited by 9 publications

References 19 publications

Assessing the influence of different Synthetic Aperture Radar parameters and Digital Elevation Model layers combined with optical data on the identification of argan forest in Essaouira region, Morocco

Assessing the influence of different Synthetic Aperture Radar parameters and Digital Elevation Model layers combined with optical data on the identification of argan forest in Essaouira region, Morocco

Argan (Argania spinosa (L.) Skeels) Bazı Termal Şok Ön İşlemleri Altında Tohum Çimlenmesi

Fencing land impacts on plant biodiversity and argan trees dynamic in the Ida-Ou-Tanane (central western of Morocco)

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