Given the interdependence of climate change (CLC) and urban expansion (URE) on
ecosystem productivity in China and India, hybrid physics-based models were fitted in this …

In this study, we combined machine learning and remote sensing techniques to estimate the
value of chlorophyll-a concentration in a freshwater ecosystem in the South American …

Phytoplankton is considered a strong predictor of the environmental quality of lakes, while
Chlorophyll-a is an indicator of primary productivity. In this study, 25 LANDSAT images …

Turbidity is associated with the loss of water transparency due to the presence of particles,
sediments, suspended solids, and organic or inorganic compounds in the water, of natural …

In this study, we employ in situ, meteorological, and remote sensing data to estimate
chlorophyll-a concentration at different depths in a South American freshwater ecosystem …

The world's water ecosystems have been affected by various human activities. Artificial
intelligence techniques, especially machine learning, have become an important tool for …

This study examines the dynamics of limnological parameters of a South American lake
located in southern Chile with the objective of predicting chlorophyll-a levels, which are a …

Rice-crayfish field (ie, RCF) distribution mapping is crucial for the adjustment of the local
crop cultivation structure and agricultural development. The single-temporal images of two …

This study aimed to utilize hybrid physics-based models that allow for a comprehensive
evaluation of how solar–meteorological variables influence the fraction of absorbed …

The high level of fishing activity with small fishing vessels has resulted in relatively high
utilization of marine space in coastal areas, manifesting changes in fishing grounds. Thus …