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Victor Hugo da Motta Paca, Everaldo Barreiros de Souza, Joaquim Carlos Barbosa Queiroz and Gonzalo E. Espinoza-Dávalos
The aim of this study was to assess precipitation (P) and actual evapotranspiration (ET) by analyzing data from in situ stations compared with remote sensing products. Climate Hazards Center InfraRed Precipitation (CHIRP) and Climate Prediction Center mo...
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Yacine Mohia, Rafik Absi, Mourad Lazri, Karim Labadi, Fethi Ouallouche and Soltane Ameur
To estimate rainfall from remote sensing data, three machine learning-based regression models, K-Nearest Neighbors Regression (K-NNR), Support Vector Regression (SVR), and Random Forest Regression (RFR), were implemented using MSG (Meteosat Second Genera...
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Jonatan Pendiuk, María Florencia Degano, Luis Guarracino and Raúl Eduardo Rivas
The practical utility of remote sensing techniques depends on their validation with ground-truth data. Validation requires similar spatial-temporal scales for ground measurements and remote sensing resolution. Evapotranspiration (ET) estimates are common...
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Charles Whittaker and Robert Leconte
For the past few decades, remote sensing has been a valuable tool for deriving global information on snow water equivalent (SWE), where products derived from space-borne passive microwave radiometers are favoured as they respond to snow depth, an importa...
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Robert Luetkemeier, Lina Stein, Lukas Drees and Stefan Liehr
Drought is one of the major threats to societies in Sub-Saharan Africa, as the majority of the population highly depends on rain-fed subsistence agriculture and traditional water supply systems. Hot-spot areas of potential drought impact need to be ident...
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Shaowei Ning, Hiroshi Ishidaira, Parmeshwar Udmale and Yutaka Ichikawa
This study is designed to demonstrate use of free remote sensing data to analyze response of water resources and grassland vegetation to a climate change induced prolonged drought in a sparsely gauged semi-arid region. Water resource changes over Hulun L...
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