L'atlas des localités du Liban : méthode d'établissement et premiers apports d'une base de données des unités cartographiques élémentaires du Liban

version antépénultième d'un article accepté par le Lebanese Scientific JournalInternational audiencethe territorial knowledge of the whole of Lebanon until recently has been limited to either on global studies implemented at national scales or of mohafazat or cazas, or to very local analyses. The recent date prduced by different administrations allows one to take a new look on the whole of the Lebanese territory at the scale of the cadastral villages. These are pertinent spaces because they allow localizing the limits of municipalities and groups of localities which are wedged on the expropriation of one or several villages. On the other hand, more recent and more reliable statistical data covering the whole of the national territory are produced on the basis of these national entities.L'article présente explique la méthode suivie pour établir un SIG à l'échelle des unités administratives élémentaires du Liban, à partir des circonscriptions foncières délimités par le cadastre et en recoupant et complétant ces informations par des enquêtes auprès d'autres administrations. Ce projet est d'abord comparé brièvement, du point de vue du contexte et des méthodes suivies, à d'autres projets du même type. Une analyse thématique concernant l'avancement de la couverture cadastrale est ensuite proposé à titre d'exemple

Optimal Timing for Capturing Satellite Thermal Images of Asphalt Object

The best extraction of asphalt object from satellite thermal images is the aim of the study. The best original data of thermal images occurred at a specific times during the days of the year. by preventing the gaps in times which give the close and same brightness from different objects. Finally, to achieve easy and efficient extraction of asphalt object from the satellite thermal images and then better analysis. The study were done using seven sample objects, asphalt, concrete, metal, rock, dry soil, vegetation, and water, located at one place carefully investigated in a way that all the objects achieve the homogeneous in acquired data at same time and same weather conditions. The samples of the objects was at roof of building at position taking by global positioning system (GPS) which its geographical coordinates is: Latitude= 33° 37´ 25.402”, longitude= 35° 28´ 57.260", height= 600 m. It has been found that the first choice and the best time for capturing the satellite thermal images for better extraction of the asphalt object in february, march, November is at 1:00 pm, in august, october at 2:00 pm and coincide with the mean. In april, may at 3:00 pm, in june at 4:00 pm and not coincide with mean. It can be noted too that the time 1:00 pm is valid in all the months and coincide with mean

Application of remotely sensed imagery andsocioeconomic surveys to map crop choices in the bekaa valley (Lebanon)

Based on remotely sensed imagery and socioeconomic data, this research analyzes the reasons why farmers choose one crop over another in the Bekaa Valley in Lebanon. This study mapped the area of the cultivated crop in 2017 with Sentinel-2 images. An accurate and new method was developed to extract the field boundaries from the evolution of the normalized difference vegetation index (NDVI) profile throughout the season. We collected 386 GPS locations for fields that are used for crop cultivation, from which the NDVI profile was extracted. The 386 reference fields were separated into two groups: reference locations and test locations. The Euclidean distance (ED) was calculated between these two groups, and the classification was strongly correlated to the known crop type in the field (overall accuracy: 90%). Our study area cultivated wheat (32%), spring potatoes (25%), spring vegetables (27%), orchards (11%), vineyards (7%), and alfalfa (<1%). Socioeconomic surveys showed that farmers favored these crops over others on account of their profitability. Nonetheless, the surveys highlighted a paradox: despite the lack of a political frame for agriculture in Lebanon, farmers’ crop choices strongly depend on a few existing policies

ANALYSIS OF EVOLUTION AND MORPHOLOGY OF URBAN AND ROAD NETWORKS: CASE STUDY LEBANON-NABATIYEH AREA

This study examines the morphology and evolution of urban and road networks and their relationship with topography in the Lebanon-Nabatiyeh area, by using GIS and remote sensing data. and calculate the annual urban growth percentage rate. The results reveal a clear relationship between the morphology of urban and road networks and their evolution over four periods, as well as the influence of the surrounding topography on their configuration. The study recommends that urban areas should be developed in areas with a slope range of 15º or more to improve the urban structure and infrastructure surrounding them. Understanding the evolution and morphology of urban and road networks is essential for urban planners and policymakers to design efficient and sustainable urban development. Future research should use the method employed in this study and supplement it with the creation of a land suitability map using GIS and remote sensing technology to improve current urban planning protocols. The study provides helpful insights for urban developers, planners, and designers in creating successful approaches to urban development and management

Empirical Study of PEFT techniques for Winter Wheat Segmentation

Parameter Efficient Fine Tuning (PEFT) techniques have recently experienced significant growth and have been extensively employed to adapt large vision and language models to various domains, enabling satisfactory model performance with minimal computational needs. Despite these advances, more research has yet to delve into potential PEFT applications in real-life scenarios, particularly in the critical domains of remote sensing and crop monitoring. The diversity of climates across different regions and the need for comprehensive large-scale datasets have posed significant obstacles to accurately identify crop types across varying geographic locations and changing growing seasons. This study seeks to bridge this gap by comprehensively exploring the feasibility of cross-area and cross-year out-of-distribution generalization using the State-of-the-Art (SOTA) wheat crop monitoring model. The aim of this work is to explore PEFT approaches for crop monitoring. Specifically, we focus on adapting the SOTA TSViT model to address winter wheat field segmentation, a critical task for crop monitoring and food security. This adaptation process involves integrating different PEFT techniques, including BigFit, LoRA, Adaptformer, and prompt tuning. Using PEFT techniques, we achieved notable results comparable to those achieved using full fine-tuning methods while training only a mere 0.7% parameters of the whole TSViT architecture. The in-house labeled data-set, referred to as the Beqaa-Lebanon dataset, comprises high-quality annotated polygons for wheat and non-wheat classes with a total surface of 170 kmsq, over five consecutive years. Using Sentinel-2 images, our model achieved a 84% F1-score. We intend to publicly release the Lebanese winter wheat data set, code repository, and model weights

Understanding drought as a physical phenomenon experienced by farmers: a necessity for adaptation management and sustainable rural development. The case of the Central Beqaa in Lebanon

The relationship between agriculture and its natural environment is an important starting point for defining drought from an agricultural perspective. Indeed, farmers may perceive drought, as a climatic risk, differently. This could depend on the physical environment of the farmer, the type and degree of involvement in his agricultural activities as well as the level of impact on his financial well-being (Ashraf and Routray, 2013). In Lebanon and particularly in the Beqaa plain, the majority of agricultural areas are strongly related to groundwater resources during the summer period. Due to the lack of sustainable local development, these resources would be threatened in the case of a probable climate change or a human factor allowing a possible evolution of water stress in the region. Questioning the origin of this phenomenon and its definition from the farmer's point of view can help us to better understand this problem. The objective of this study is therefore to identify the drought by crossing the human and physical elements in the perimeter of the study area.La relation entre l'agriculture et son environnement naturel est un point de départ important pour définir la sécheresse d'un point de vue agricole. En effet, la sécheresse, en tant que risque climatique, peut être perçue différemment par les agriculteurs. Cela pourrait dépendre de l'environnement physique de l'agriculteur, du type et du degré d'implication dans ses activités agricoles ainsi que du niveau d'impact sur son bien-être financier (Ashraf et Routray, 2013). Au Liban et particulièrement dans la plaine de la Beqaa, la majorité des zones agricoles sont fortement liées aux ressources en eau souterraine pendant la période estivale. En raison de l'absence de développement local durable, ces ressources seraient menacées dans le cas d'un probable changement climatique ou d'un facteur humain permettant une possible évolution du stress hydrique dans la région. S'interroger sur l'origine de ce phénomène et sa définition du point de vue de l'agriculteur peut nous aider à mieux comprendre ce problème. L’objectif de cette étude est donc d'identifier la sécheresse en croisant les éléments humains et physiques dans le périmètre de la zone d'étude

Do Fiduciary Duties Contained in Federal Tax Laws Effectively Promote National Health Care Policies and Practices ?

International audienc

Multitemporal Remote Sensing Based on an FVC Reference Period Using Sentinel-2 for Monitoring Eichhornia crassipes on a Mediterranean River

International audienceInvasive aquatic plants are a serious global ecological and socio-economic problem because they can cause local extinction of native species and alter navigation and fishing. Eichhornia crassipes (water hyacinth) is a dangerous invasive floating plant that is widely distributed throughout the world. In Lebanon, it has spread since 2006 in the Al Kabir River. Remote sensing techniques have been widely developed to detect and monitor dynamics and extents of invasive plants such as water hyacinth over large areas. However, they become challenging to use in narrow areas such as the Al Kabir River and we developed a new image-analysis method to extract water hyacinth areas on the river. The method is based on a time series of a biophysical variable obtained from Sentinel-2 images. After defining a reference period between two growing cycles, we used the fractional vegetation cover (FVC) to estimate the water hyacinth surface area in the river. This method makes it possible to monitor water hyacinth development and estimate the total area it colonizes in the river corridor. This method can help ecologists and other stakeholders to map invasive plants in rivers and improve their control

Reflection-coefficient experimental extraction from S21- parameter for radar oil-spill detection application

Oil spill in sea water is one of the main accidents that affect significantly the maritime environment over a long period of time. Knowing the severe influence of oil spills on the ecosystem, it is crucial to have oil spill detecting and monitoring systems for quick intervention and danger containment. In our project, we propose the usage of drones as an oil spill detection system. The drones will be implementing different previously developed multi-frequency approaches for the detection. The effectiveness of such techniques is based on the accuracy of the data collected and their match to the theory. This journal presents a method for the remote extraction of reflection coefficients from multilayer structure modeling an oil spill in sea water. The experimental results for the reflectivity extraction validate the theoretical calculations and allow the implementation of different algorithms based on the statistical information taken directly from the site

Regional Landsat-Based Drought Monitoring from 1982 to 2014

Drought is a serious natural hazard with far-reaching impacts including soil damages, economic losses, and threatening the livelihood and health of local residents. The goal of the present work was to monitor the vegetation health across Lebanon in 2014 using remote sensing techniques. Landsat images datasets, with a spatial resolution of 30 m and from different platforms, were used to identify the VCI (Vegetation Condition Index) and TCI (Temperature Condition Index). The VCI was based on the Normalized Difference Vegetation Index (NDVI) datasets. The TCI used land surface temperature (LST) datasets. As a result, the VHI (Vegetation Health Index) was produced and classified into five categories: extreme, severe, moderate, mild, and no drought. The results show practically no extreme drought (~0.27 km2) in the vegetated area in Lebanon during 2014. Moderate to severe drought mainly occurred in the north of Lebanon (i.e., the Amioun region and the plain of Akkar). The Tyr region and the Bekaa valley experienced a low level of drought (mild drought). This approach allows decision makers to monitor, investigate and resolve drought conditions more effectively