We can't find the internet
Attempting to reconnect
Something went wrong!
Hang in there while we get back on track
Predicting microplastic accumulation zones and shoreline changes along the Kelantan coast, Malaysia, using integrated GIS and ANN models
AI summary Read the abstract
Researchers combined GIS with an artificial neural network to predict microplastic accumulation zones along Malaysia's Kelantan coast, achieving R=0.972 predictive accuracy and identifying shoreline erosion-prone areas as the primary deposition hotspots for microplastic pollution.
Microplastic pollution in coastal environments is an escalating global concern, yet its spatial distribution and accumulation dynamics remain inadequately addressed. This study pioneers the use of an integrated Geographical Information Systems (GIS) and Artificial Neural Network (ANN) model to predict microplastic accumulation zones along Kelantan's coast, Malaysia. Leveraging key environmental variables including shoreline erosion, tidal influence, and sediment transport which the model demonstrates high predictive accuracy (R = 0.972), identifying erosion-prone areas as significant deposition zones. The strong correlation between tidal dynamics and microplastic abundance highlights the influence of hydrodynamic forces on pollution patterns. As one of the first applications of ANN modeling in Malaysian coastal environments, this research offers a scalable, data-driven tool for coastal managers to optimize pollution control strategies. These findings provide critical insights for targeted marine pollution interventions, contributing to ongoing global efforts to protect vulnerable coastal ecosystems.
More Papers Like This
Microplastic Deposit Predictions on Sandy Beaches by Geotechnologies and Machine Learning Models
AI summary Read the abstract
Researchers used satellite imagery and machine learning to predict where microplastics accumulate on sandy beaches along Brazil's northern coast. They found that beach shape, slope, and proximity to urban areas were strong predictors of microplastic deposits. The study demonstrates that geotechnology tools can help identify pollution hotspots without costly field sampling at every location.
Microplastic deposit predictions on sandy beaches by geotechnologies and machine learning models
AI summary Read the abstract
Researchers used geotechnologies and machine learning models to predict microplastic deposition hotspots on sandy beaches, identifying environmental and anthropogenic variables that drive spatial variation in beach microplastic accumulation.
Mapping the Plastic Legacy: Geospatial Predictions of a Microplastic Inventory in a Complex Estuarine System Using Machine Learning
AI summary Read the abstract
Researchers applied machine learning geospatial modelling to predict microplastic distribution across a complex estuarine system, using sediment samples as a training dataset to generate spatial inventory maps of microplastic accumulation. The model leveraged the estuary's role as a land-sea interface and plastic accumulation bottleneck to produce high-resolution predictions of microplastic hotspots for monitoring and management purposes.
Mapping the plastic legacy: Geospatial predictions of a microplastic inventory in a complex estuarine system using machine learning
AI summary Read the abstract
Researchers applied machine learning techniques to develop geospatial predictions of microplastic inventory in a complex estuarine system, overcoming the limitations of coarse ocean basin models by accounting for the intricate geomorphological and hydrodynamic conditions that govern sediment-associated microplastic distribution.
Microplastic deposits prediction on Urban Sandy Beaches: Integrating Remote Sensing, GNSS Positioning, µ-Raman Spectroscopy, and Machine Learning Models
AI summary Read the abstract
Researchers integrated remote sensing, GNSS altimetric surveys, micro-Raman spectroscopy, and machine learning models to predict microplastic deposition patterns on urban sandy beaches along the central Sao Paulo coastline, finding MP concentrations ranging from 6 to 35 MPs/m2.
Research digests by email
When a large batch of papers lands in the Atlas, we read through it and send a short write-up of what stood out.