Quasi-global machine learning-based soil moisture estimates at high spatio-temporal scales using CYGNSS and SMAP observations

F Lei, V Senyurek, M Kurum, AC Gurbuz, D Boyd… - Remote Sensing of …, 2022 - Elsevier
Global soil moisture mapping at high spatial and temporal resolution is important for various
meteorological, hydrological, and agricultural applications. Recent research shows that the …

[PDF][PDF] A Review of Flood Detection Systems

MA Baballe, Z Abbati - … on Engineering and Applied Natural Sciences, 2022 - academia.edu
One of the most harmful natural disasters that naturally occurs is flooding, which occurs with
an increase in water level. The damage caused by the flood will be more harmful and the …

Investigating Correlations and the Validation of SMAP-Sentinel L2 and In Situ Soil Moisture in Thailand

A Jotisankasa, K Torsri, S Supavetch… - Sensors, 2023 - mdpi.com
Soil moisture plays a crucial role in various hydrological processes and energy partitioning
of the global surface. The Soil Moisture Active Passive-Sentinel (SMAP-Sentinel) remote …

Spatial gap-filling of SMAP soil moisture pixels over Tibetan plateau via machine learning versus geostatistics

C Tong, H Wang, R Magagi, K Goïta… - IEEE Journal of …, 2021 - ieeexplore.ieee.org
Soil moisture (SM) is a key variable in ecology, environment, agriculture, and hydrology. The
Soil Moisture Active Passive (SMAP) satellite provides global SM products with reliable …

Sentinel-1 backscatter analysis and radiative transfer modeling of dense winter wheat time series

T Weiß, T Ramsauer, T Jagdhuber, A Löw, P Marzahn - Remote Sensing, 2021 - mdpi.com
This study evaluates a temporally dense VV-polarized Sentinel-1 C-band backscatter time
series (revisit time of 1.5 days) for wheat fields near Munich (Germany). A dense time series …

Soil moisture-based global liquefaction model (SMGLM) using soil moisture active passive (SMAP) satellite data

A Farahani, M Ghayoomi - Soil Dynamics and Earthquake Engineering, 2024 - Elsevier
The role of soil saturation condition on the liquefaction occurrence highlights the need for a
tool to track the ground-truth soil moisture content involved in this seismic phenomenon. Soil …

Understanding root-zone soil moisture in agricultural regions of Central Mexico using the ensemble Kalman filter, satellite-derived information, and the THEXMEX-18 …

HE Huerta-Bátiz, DE Constantino-Recillas… - … Journal of Digital …, 2022 - Taylor & Francis
ABSTRACT An Ensemble Kalman Filter (EnKF)-based assimilation algorithm was
implemented to estimate root-zone soil moisture (RZSM) using a Soil-Vegetation …

[HTML][HTML] Application of soil moisture active passive (SMAP) satellite data in seismic response assessment

A Farahani, M Moradikhaneghahi, M Ghayoomi… - Remote Sensing, 2022 - mdpi.com
The proven relationship between soil moisture and seismic ground response highlights the
need for a tool to track the Earth's surface soil moisture before and after seismic events. This …

60-meter resolution soil moisture estimation based on a multi-sensor feedforward neural network model

G Portal, M Vall-Llossera… - IEEE Journal of …, 2024 - ieeexplore.ieee.org
Understanding soil moisture (SM) at high spatio-temporal resolution provides crucial
insights across various societal disciplines due to its direct impact on environmental and …

Evaluation of global seamless soil moisture products over China: A perspective of soil moisture sensitivity to precipitation

X Hong, S Jia, W Zhu, Z Song - Journal of Hydrology, 2024 - Elsevier
Accurate and timely information about soil moisture (SM) is not only critical to the study of
climate change, but is also significant for agricultural production, drought monitoring, and …