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[HTML][HTML] An accurate snow cover product for the Moroccan Atlas Mountains: Optimization of the MODIS NDSI index threshold and development of snow fraction …
In semi-arid Mediterranean areas, a significant proportion of the population living
downstream depends on water resources from snowmelt and precipitation as their main …
downstream depends on water resources from snowmelt and precipitation as their main …
Assessment of the impact of climate change on Argan tree in the Mediterranean GIAHS site, Morocco: Current and future distributions
Climate change significantly challenges the sustainability of forest ecosystems, with broad
socio-ecological impacts insufficiently assessed. This study examines one such critical …
socio-ecological impacts insufficiently assessed. This study examines one such critical …
Predictive modelling on Spatial–temporal Land Use and Land Cover changes at the Casablanca-Settat Region in Morocco
Urban Population growth coupled with human activities are the main drivers inducing land
use and land cover changes (LU/LCC), which impact earth's landscapes dynamics. In the …
use and land cover changes (LU/LCC), which impact earth's landscapes dynamics. In the …
Physics-informed neural networks for enhanced reference evapotranspiration estimation in Morocco: Balancing semi-physical models and deep learning
Reference evapotranspiration (ET o) is essential for agricultural water management, crop
productivity, and irrigation systems. The Penman-Monteith (PM) equation is the standard …
productivity, and irrigation systems. The Penman-Monteith (PM) equation is the standard …
Modeling the impact of climate change on wheat yield in Morocco based on stacked ensemble learning
Climate change increases the frequency and intensity of extreme events such as droughts,
heat waves, and floods, posing a significant challenge to Morocco's agriculture and food …
heat waves, and floods, posing a significant challenge to Morocco's agriculture and food …
[HTML][HTML] Leveraging advanced deep learning and machine learning approaches for snow depth prediction using remote sensing and ground data
Study regions The study area encompasses two distinct sub-basins within the High Atlas
Mountains: Oukaimeden in the Rheraya and Tichki in the Mgoun Valley. Study focus The …
Mountains: Oukaimeden in the Rheraya and Tichki in the Mgoun Valley. Study focus The …
Machine Learning Approaches for Predicting Reference Evapotranspiration: A Comparative Study Using Ground and Gridded Climate Data in Fes Region
Climate data are essential for agricultural planning and water resource management;
however, their availability is limited in numerous regions of Africa. Gridded climate data …
however, their availability is limited in numerous regions of Africa. Gridded climate data …
A Hybrid Surrogate Deep Learning Model for Actual Evapotranspiration Prediction
The estimation of hydrological components on a spatiotemporal scale poses a challenge for
researchers as they develop data-driven tools that can be transferred to different regions …
researchers as they develop data-driven tools that can be transferred to different regions …
Assessing the performance of Random Forest Regression to predict snow depth using Sentinel-1 SAR and field measurements in a sub-arctic alpine region
T Sigurjónsson - 2024 - diva-portal.org
This study aims to investigate the potential of using SAR images from Sentinel-1 to predict
snow depth in sub-arctic alpine regions by employing Random Forest regression. In addition …
snow depth in sub-arctic alpine regions by employing Random Forest regression. In addition …