A new modelling framework to assess changes in groundwater level
Abstract Study region The Southern African region consists of ten countries including,
Angola, Zambia, Malawi, Namibia, Botswana, Zimbabwe, Mozambique, South Africa …
Angola, Zambia, Malawi, Namibia, Botswana, Zimbabwe, Mozambique, South Africa …
Evaluating groundwater storage change and recharge using GRACE data: A case study of aquifers in Niger, West Africa
Accurately assessing groundwater storage changes in Niger is critical for long-term water
resource management but is difficult due to sparse field data. We present a study of …
resource management but is difficult due to sparse field data. We present a study of …
An assimilated deep learning approach to identify the influence of global climate on hydrological fluxes
The rapid acceleration of the global water cycle caused by changes in global climate trigger
complex processes that make conventional machine learning techniques limited in …
complex processes that make conventional machine learning techniques limited in …
[HTML][HTML] Reconstructing terrestrial water storage anomalies using convolution-based support vector machine
Abstract Study region The Congo River basin in west-central Africa Study focus Traditional
machine learning algorithms are recently being replaced by integrated learning techniques …
machine learning algorithms are recently being replaced by integrated learning techniques …
Exploiting earth observations to enable groundwater modeling in the data-sparse Region of Goulbi Maradi, Niger
Groundwater modeling is a useful tool for assessing sustainability in water resources
planning. However, groundwater models are difficult to construct in regions with limited data …
planning. However, groundwater models are difficult to construct in regions with limited data …
Advancements in remote sensing technologies for accurate monitoring and management of surface water resources in Africa: an overview, limitations, and future …
This review presents a comprehensive examination of recent advancements in utilizing multi-
date satellite data to analyze spatial and temporal variations in seasonal and inter-annual …
date satellite data to analyze spatial and temporal variations in seasonal and inter-annual …
[HTML][HTML] Machine learning assessment of hydrological model performance under localized water storage changes through downscaling
The coarse spatial resolution of the Gravity Recovery and Climate Experiment (GRACE)
data has limited its application in the management of local-scale water resources. To …
data has limited its application in the management of local-scale water resources. To …
Integration of satellite geodetic observations for regional geoid modeling using remove-compute-restore technique
Advanced satellite geodetic systems have contributed to improving knowledge on changes
in global gravity fields in recent years. These systems offer profound opportunities in the …
in global gravity fields in recent years. These systems offer profound opportunities in the …
Tensor partial least squares for hyperspectral image classification
O Okwuashi, CE Ndehedehe… - Geocarto International, 2022 - Taylor & Francis
A hyperspectral image is classically a three-way (or tensor) block of data. In order to extract
information from it, it has to be classified using image classifiers. Since classifiers are …
information from it, it has to be classified using image classifiers. Since classifiers are …
[HTML][HTML] Estimating the seven transformational parameters between two geodetic datums using the steepest descent algorithm of machine learning
This study evaluates the steepest descent algorithm as a tool for root mean square (RMS)
error optimization in geodetic reference systems to improve the integrity of transformation …
error optimization in geodetic reference systems to improve the integrity of transformation …