Predicting Water Quality Distribution of Lakes through Linking Remote Sensing–Based Monitoring and Machine Learning Simulation

Improving Inland Water Quality Monitoring through Remote Sensing Techniques

Chlorophyll-a (chl-a) levels in lake water could indicate the presence of cyanobacteria, which can be a concern for public health due to their potential to produce toxins. Monitoring of chl-a has been an important practice in aquatic systems, especially in those used for human services, as they imply an increased risk of exposure. Remote sensing technology is being increasingly used to monitor ...

Evaluation of remote sensing indicators in drought monitoring using machine learning algorithms (Case study: Marivan city)

Remote sensing indices are used to analyze the Spatio-temporal distribution of drought conditions and to identify the severity of drought. This study, using various drought indices generated from Madis and TRMM satellite data extracted from Google Earth Engine (GEE) platform. Drought conditions in Marivan city from February to November for the years 2001 to 2017 were analyzed based on spatial a...

the effect of vocabulary instruction through semantic mapping on learning and recall of efl learners

چکیده ندارد.

Water exploitation of Karoon River for fish culturing through monitoring and simulation systems

Heavy metal pollution dispersion simulation in rivers and predicting spatial and temporal variations of pollutants can be used to determine the precise place and to schedule water withdrawal time for drinking, agriculture, aquaculture and ecosystem studies. To study the movement of heavy metal pollution through Karoon flow model, MIKE 11 was employed fpr simulation of the flow model of Karoon R...

Water quality estimation by optical remote sensing in boreal lakes