AI Medical Compendium Topic:
Environmental Monitoring

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Water level prediction using soft computing techniques: A case study in the Malwathu Oya, Sri Lanka.

PloS one
Hydrologic models to simulate river flows are computationally costly. In addition to the precipitation and other meteorological time series, catchment characteristics, including soil data, land use, land cover, and roughness, are essential in most hy...

Cooperative simultaneous inversion of satellite-based real-time PM and ozone levels using an improved deep learning model with attention mechanism.

Environmental pollution (Barking, Essex : 1987)
Ground-level fine particulate matter (PM) and ozone (O) are air pollutants that can pose severe health risks. Surface PM and O concentrations can be monitored from satellites, but most retrieval methods retrieve PM or O separately and disregard the s...

Deep learning mapping of surface MDA8 ozone: The impact of predictor variables on ozone levels over the contiguous United States.

Environmental pollution (Barking, Essex : 1987)
The limited number of ozone monitoring stations imposes uncertainty in various applications, calling for accurate approaches to capturing ozone values in all regions, particularly those with no in-situ measurements. This study uses deep learning (DL)...

A fuzzy logic-based approach for groundwater vulnerability assessment.

Environmental science and pollution research international
Groundwater vulnerability assessment systems have been developed to protect groundwater resources. The DRASTIC model calculates the vulnerability index of the aquifer based on seven effective parameters. The application of expert opinion in rating an...

Fuzzy-based models' performance on qualitative and quantitative land suitability evaluation for cotton cultivation in Sarayan County, South Khorasan Province, Iran.

Environmental monitoring and assessment
Using appropriate models in the land use planning process will help increase the accuracy and precision of decisions made by designers. The aim of this study was to investigate and compare fuzzy-based models (fuzzy set theory, fuzzy-AHP, and fuzzy-AN...

Analysis and forecasting of national marine litter based on coastal data in South Korea from 2009 to 2021.

Marine pollution bulletin
In this study, statistical analysis and forecasting were performed using coastal litter data of Korea. The analysis indicated that rope and vinyl accounted for the highest proportion of coastal litter items. The statistical analysis of the national c...

Detection of marine oil-like features in Sentinel-1 SAR images by supplementary use of deep learning and empirical methods: Performance assessment for the Great Barrier Reef marine park.

Marine pollution bulletin
Continuous monitoring of oil discharges in coastal and open ocean waters using Earth Observation (EO) has undeniably contributed to diminishing their occurrence wherever a detection system was in place, such as in Europe (EMSA's CleanSeaNet) or in th...

Modelling vegetation land fragmentation in urban areas of Western Province, Sri Lanka using an Artificial Intelligence-based simulation technique.

PloS one
Vegetation land fragmentation has had numerous negative repercussions on sustainable development around the world. Urban planners are currently avidly investigating vegetation land fragmentation due to its effects on sustainable development. The lite...

Efficacy of GIS-based AHP and data-driven intelligent machine learning algorithms for irrigation water quality prediction in an agricultural-mine district within the Lower Benue Trough, Nigeria.

Environmental science and pollution research international
Agricultural productivity can be impaired by poor irrigation water quality. Therefore, adequate vulnerability assessment and identification of the most influential water quality parameters for accurate prediction becomes crucial for enhanced water re...

Ocean oil spill detection from SAR images based on multi-channel deep learning semantic segmentation.

Marine pollution bulletin
One of the major threats to marine ecosystems is pollution, particularly, that associated with the offshore oil and gas industry. Oil spills occur in the world's oceans every day, either as large-scale spews from drilling-rig or tanker accidents, or ...