Progress in fluvial geomorphology and trend: A brief review
Significance As an important branch in earth system science, fluvial geomorphology is the study of fluvial erosion-transport-accumulation processes (source-to-sink system), temporal-spatial change in fluvial landscapes, and impact of tectonic, climate ...
Xianyan WANG, Yang YU
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Architecture and geomorphology of fluvial channel systems in the Arabian Basin [PDF]
The architecture and geomorphology of fluvial channel system plays an important role in the interpretation of its sedimentary processes and characterization of the ability for subsurface storage.
Dicky Harishidayat +2 more
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Quantitative architectural analysis of meandering fluvial point bar of Gudong oilfield in Zhanhua Sag Bohai Bay basin China [PDF]
In order to extract the remaining oil from the reservoir during the late stage of development, there is an increasing demand for precise research on the internal architecture of the reservoir.
Yupeng Qiao +10 more
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Global classification of river morphology based on inland water dynamics characterization and digital elevation data [PDF]
Classifying river morphology is crucial for fluvial geomorphology and hydrology. River morphology reflects hydrodynamic and sedimentary processes, providing critical insights into the diversity of global river systems.
Yilin Li +6 more
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Fluvial geomorphology on Earth-like planetary surfaces: A review [PDF]
VÍCTOR R Baker +2 more
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THE EVOLUTION OF THE AISNE FLOODPLAIN (ARDENNE, BELGIUM) DURING THE LAST CENTURIES STUDIED WITH THE MICROSLAG DATING METHOD [PDF]
In the Ardenne massif (south Belgium) many traces of metallurgical activity are present. An intensive development of iron industry took place from the Middle Ages until the middle of the 19th century.
Geoffrey Houbrechts +4 more
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Machine Learning to Estimate Surface Roughness from Satellite Images
We apply the Support Vector Regression (SVR) machine learning model to estimate surface roughness on a large alluvial fan of the Kosi River in the Himalayan Foreland from satellite images.
Abhilash Singh +3 more
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We propose a hybrid machine learning algorithm (i.e., P2CA−PSO−ANN) to model malaria outbreak in three districts (Barmer, Bikaner, and Jodhpur) of Rajasthan in the Western India.
Abhilash Singh +5 more
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We evaluate the penetration depth of synthetic aperture radar (SAR) signals into the ground surface at different frequencies. We applied dielectric models (Dobson empirical, Hallikainen, and Dobson semi-empirical) on the ground surface composed of ...
Abhilash Singh +3 more
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Deep learning and data fusion to estimate surface soil moisture from multi-sensor satellite images
We propose a new architecture based on a fully connected feed-forward Artificial Neural Network (ANN) model to estimate surface soil moisture from satellite images on a large alluvial fan of the Kosi River in the Himalayan Foreland.
Abhilash Singh, Kumar Gaurav
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