Artificial intelligence for geoscience: Progress, challenges and perspectives
This paper explores the evolution of geoscientific inquiry, tracing the progression from
traditional physics-based models to modern data-driven approaches facilitated by significant …
traditional physics-based models to modern data-driven approaches facilitated by significant …
Machine learning in agriculture: A comprehensive updated review
The digital transformation of agriculture has evolved various aspects of management into
artificial intelligent systems for the sake of making value from the ever-increasing data …
artificial intelligent systems for the sake of making value from the ever-increasing data …
Land data assimilation: Harmonizing theory and data in land surface process studies
Data assimilation plays a dual role in advancing the “scientific” understanding and serving
as an “engineering tool” for the Earth system sciences. Land data assimilation (LDA) has …
as an “engineering tool” for the Earth system sciences. Land data assimilation (LDA) has …
Two-step fusion method for generating 1 km seamless multi-layer soil moisture with high accuracy in the Qinghai-Tibet plateau
Current remote sensing techniques fail to observe and generate large scale multi-layer soil
moisture (SM) due to the inherent features of the satellite sensors. The lack of …
moisture (SM) due to the inherent features of the satellite sensors. The lack of …
Root-zone soil moisture estimation based on remote sensing data and deep learning
Soil moisture in the root zone is the most important factor in eco-hydrological processes.
Even though soil moisture can be obtained by remote sensing, limited to the top few …
Even though soil moisture can be obtained by remote sensing, limited to the top few …
[HTML][HTML] Improving soil moisture prediction using a novel encoder-decoder model with residual learning
The skillful prediction of soil moisture can provide much help for many practical applications
including ecosystem management and precision agriculture. It presents great challenges …
including ecosystem management and precision agriculture. It presents great challenges …
Accumulated soil moisture deficit better indicates the effect of soil water stress on light use efficiency of grasslands during drought years
Light use efficiency (LUE) models have been widely used in the estimation of gross primary
productivity (GPP). However, many studies indicated that current LUE models generally …
productivity (GPP). However, many studies indicated that current LUE models generally …
How to enhance hydrological predictions in hydrologically distinct watersheds of the Indian subcontinent?
Accurate hydrological predictions are required to prepare for the impacts of climate change,
especially in India, which experiences frequent floods and droughts. However, the complex …
especially in India, which experiences frequent floods and droughts. However, the complex …
A review on snowmelt models: progress and prospect
G Zhou, M Cui, J Wan, S Zhang - Sustainability, 2021 - mdpi.com
The frequency and intensity of flood events have been increasing recently under the
warming climate, with snowmelt floods being a significant part. As an effective manner of …
warming climate, with snowmelt floods being a significant part. As an effective manner of …
[HTML][HTML] A comparison of physical-based and machine learning modeling for soil salt dynamics in crop fields
The physical-based and machine learning (ML) models are two distinctive tools for
predicting soil salt content (SSC). However, few studies have compared their performances …
predicting soil salt content (SSC). However, few studies have compared their performances …