In recent years, black-box machine learning approaches have become a dominant modeling
paradigm for knowledge extraction in remote sensing. Despite the potential benefits of …

This systematic literature review employs the Preferred Reporting Items for Systematic
Reviews and Meta-Analyses (PRISMA) methodology to investigate recent applications of …

Determination of the dominant factors which affect soil moisture (SM) predictions for drought
analysis is an essential step to assess the reliability of the prediction results. However …

Soil moisture (SM) is a crucial land surface variable that links cyclic processes between the
land surface and the atmosphere. Accurate SM prediction holds great significance for …

This article examines the impact of Artificial Intelligence (AI) on the comprehensive
rehabilitation of post-cancer patients, specifically in the areas of psychological support and …

Unconfined compressive strength (UCS) is an important parameter of rock and soil
mechanical behavior in foundation engineering design and construction. In this study …

In recent years, artificial intelligence (AI) rapidly accelerated its influence and is expected to
promote the development of Earth system science (ESS) if properly harnessed. In …

How to consider the spatiotemporal distribution of rainfall and hydrologic uncertainty is
crucial to enhance flood forecasting accuracy. This study integrates a spatiotemporal dual …

Soil moisture (SM) is essential for energy and water exchange between soil and
atmosphere. Accurate prediction of its spatio-temporal occurrence is critical for climate …

Accurate temperature prediction is essential for economic production and human society's
daily life. However, most current methods only focus on time-series temperature modeling …