Deep learning and data fusion to estimate surface soil moisture from multi-sensor satellite images

A Singh, K Gaurav - Scientific Reports, 2023 - nature.com
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 …

PIML-SM: Physics-informed machine learning to estimate surface soil moisture from multi-sensor satellite images by leveraging swarm intelligence

A Singh, K Gaurav - IEEE Transactions on Geoscience and …, 2024 - ieeexplore.ieee.org
We introduce a physics-informed machine learning (PIML) algorithm based on a feed-
forward neural network (FFNN) to estimate surface soil moisture from limited in situ …

A 20 m spatial resolution peatland extent map of Alaska

MJ Lara, R Michaelides, D Anderson, W Chen, EC Hall… - Scientific Data, 2025 - nature.com
Peatlands are prevalent across northern regions, including bogs, fens, marshes, meadows,
and select tundra wetlands that all vary in size (eg, 0.01 s to 10 s km2) and shape (eg …

[HTML][HTML] Evaluation and improvement of spatiotemporal estimation and transferability of multi-layer and profile soil moisture in the Qinghai Lake and Heihe River …

J Qian, J Yang, W Sun, L Zhao, L Shi, H Shi, L Liao… - Geoderma, 2025 - Elsevier
The machine learning regression (MLR) algorithms have brought new insights into soil
moisture (SM) estimation. However, few studies have explored the potential of MLR …

Non-destructive detection of wheat moisture content with frequency modulated continuous wave system under L and S bands

X Kuang, Z Zhu, J Guo, S **ang - Computers and Electronics in Agriculture, 2024 - Elsevier
Wheat moisture content is a critical indicator for evaluating quality. The microwave free
space measurement method can achieve nondestructive and efficient measurement of …

[CITAAT][C] The InflateSAR Campaign

P Lanz