28 hasil untuk "Imane Sebari"
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Artikel Jurnal
Utilisation des Systèmes d’Informations Géographiques pour l’analyse spatio-temporelle des effets des changements climatiques sur la disponibilité des ressources halieutiques au Maroc
Les changements des variables climatiques telles que la température affectent directement les conditions de vie des espèces marines y compris les espèces de poissons. Dans ce travail, nous avons examiné le niveau d’exposition de la distribution de trois espèces de Sardina pilchardus, Merluccius…
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A Hybrid Multi-Scale Phase-Correlation Framework for Subpixel Registration of Multi-Temporal Very-High-Resolution Remote Sensing Images
This paper proposes a hybrid phase-correlation framework with a new multiscale detector, Fusion. Using a combination of FAST and Shi–Tomasi keypoints, followed by a probabilistic Hough transform and Canny edge detection, this detector improves repeatability. In addition, due to the limited ability…
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Automatic Sub-Pixel Co-Registration of Remote Sensing Images Using Phase Correlation and Harris Detector
In this paper, we propose a new approach for sub-pixel co-registration based on Fourier phase correlation combined with the Harris detector. Due to the limitation of the standard phase correlation method to achieve only pixel-level accuracy, another approach is required to reach sub-pixel matching…
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IFCInfra4OM: An Ontology to Integrate Operation and Maintenance Information in Highway Information Modelling
Building information modelling (BIM) is increasingly appropriate for infrastructure projects, and in particular for transport infrastructure. It is a digital solution that integrates the practices of the construction industry in facility management during the whole life cycle. This integration is…
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Thermal Infrared and Visual Inspection of Photovoltaic Installations by UAV Photogrammetry—Application Case: Morocco
Being sustainable, clean, and eco-friendly, photovoltaic technology is considered as one of the most hoped solutions face to worldwide energetic challenges. Morocco joins this context with the inauguration of numerous clean energy projects. However, one key factor in making photovoltaic…
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Towards a Multi-Temporal Deep Learning Approach for Mapping Urban Fabric Using Sentinel 2 Images
The major part of the population lives in urban areas, and this is expected to increase in the future. The main challenges faced by cities currently and towards the future are the rapid urbanization, the increase in urban temperature and the urban heat island. Mapping and monitoring urban fabric…
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Vers une extension du Building Information Modeling aux projets d’infrastructure routière: Cas d’étude d’un échangeur autoroutier au Maroc
Le Building Information Modeling (BIM) est une révolution de la technologie dans le secteur du bâtiment où il a fait ses preuves tout au long du cycle de vie d’un bâtiment. Cette réalité a mené depuis quelques années, à une extension de ce concept au secteur du Génie Civil pour les projets…
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Extending the IFC Standard to Enable Road Operation and Maintenance Management through OpenBIM
Open Building Information Modelling (OpenBIM) is a collaborative project management process. Its application to road infrastructures is currently limited. OpenBIM standards for infrastructure are still under development. One of these standards is the Industry Foundation Classes (IFC), which is a…
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Extraction automatique des zones irriguées dans la région du Gharb par analyse d'image basée-objets des images Landsat 8
Le Maroc a déployé d’immenses efforts en matière d’irrigation. Cependant, le manque d’informations concernant la localisation et la délimitation précise des zones irriguées affecte de plus en plus le suivi et le contrôle des agriculteurs. L’objectif principal de cette étude est d’évaluer l’apport…
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Machine and Deep Learning for Wetland Mapping and Bird-Habitat Monitoring: A Systematic Review of Remote-Sensing Applications (2015–April 2025)
Wetlands, among the most productive ecosystems on Earth, shelter a diversity of species and help maintain ecological balance. However, they are witnessing growing anthropogenic and climatic threats, which underscores the need for regular and long-term monitoring. This study presents a systematic…
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Opportunités d’utilisation de la technologie drone au niveau des écosystèmes forestiers
Au cours de la dernière décennie, la technologie drone a suscité un grand intérêt et a été largement utilisée pour des applications civiles. Ainsi, les drones ont rapidement prouvé leurs efficiences dans les ressources naturelles, l’environnement, l’agriculture et notamment la foresterie. Etant une…
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A Validation-Controlled Label-Efficient Framework for Coastal Wetland Habitat Mapping Using Multi-Season Sentinel-1 and Sentinel-2 Data
Reliable coastal wetland habitat mapping is often constrained by the scarcity and the cost of reliable reference data, especially in data-limited coastal environments. We propose a validation-controlled, label-efficient framework pairing multi-season Sentinel-1 and Sentinel-2 predictors with a…
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Enhancing Urban Resource Management Through Urban and Peri-Urban Agriculture
Urbanization is one of the most important challenges contributing to the trend of replacing agricultural land with high-value land uses, such as housing, as well as industrial and commercial activities, as a result of significant population growth. To face these challenges and improve urban…
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Mapping and Monitoring Peri-Urban Territorial Dynamics Using Multi-Source Geospatial Data: A Case of the Casablanca Region
Peri-urbanization is one of the most complex and rapidly territorial phenomena in African metropolitan areas, including Morocco. This dynamic, characterized by unplanned urban growth, presents significant challenges in terms of land management and sustainable territorial planning. In this context…
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Recalage d'images avec la corrélation d'images basée sur la méthode de Fourier
Le recalage d'images est une technique importante dans de nombreuses applications de vision par ordinateur, telles que la fusion d'images, le suivi d'objets, la reconnaissance de visages, la détection de changements, etc. Les composantes principales du processus de recalage à savoir l’espace des…
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Mapping Wheat Dry Matter and Nitrogen Content Dynamics and Estimation of Wheat Yield Using UAV Multispectral Imagery Machine Learning and a Variety-Based Approach: Case Study of Morocco
Our work aims to monitor wheat crop using a variety-based approach by taking into consideration four different phenological stages of wheat crop development. In addition to highlighting the contribution of Red-Edge vegetation indices in mapping wheat dry matter and nitrogen content dynamics, as…
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Towards a Holistic Approach for UAV-Based Large-Scale Photovoltaic Inspection: A Review on Deep Learning and Image Processing Techniques
This paper provides an in-depth literature review on image processing techniques, focusing on deep learning approaches for anomaly detection and classification in photovoltaics. It examines key components of UAV-based PV inspection, including data acquisition protocols, panel segmentation and…
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Towards Smart Irrigation: A Literature Review on the Use of Geospatial Technologies and Machine Learning in the Management of Water Resources in Arboriculture
Agriculture consumes an important ratio of the water reserve in irrigated areas. The improvement of irrigation is becoming essential to reduce this high water consumption by adapting supplies to the crop needs and avoiding losses. This global issue has prompted many scientists to reflect on…
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A new integrated neurosymbolic approach for crop-yield prediction using environmental data and satellite imagery at field scale
Crop-yield is a crucial metric in agriculture, essential for effective sector management and improving the overall production process. This indicator is heavily influenced by numerous environmental factors, particularly those related to soil and climate, which present a challenging task due to the…
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UrbanTree3D: An Open Dataset for Urban Tree Species Classification Using Airborne LiDAR and Field Inventory Data
The increasing availability of airborne LiDAR data supports advanced three-dimensional analysis of urban vegetation. However, the development of deep learning methods for tree species classification remains limited by the lack of annotated datasets at the individual-tree level. This study presents…