HABNet: Machine Learning, Remote Sensing-Based Detection of Harmful Algal Blooms (original) (raw)

A Remote Sensing and Machine Learning-Based Approach to Forecast the Onset of Harmful Algal Bloom

Remote Sensing

Learning-Based Algal Bloom Event Recognition for Oceanographic Decision Support System Using Remote Sensing Data

Remote Sensing, 2015

A Machine Learning Based Spatio-Temporal Data Mining Approach for Detection of Harmful Algal Blooms in the Gulf of Mexico

Nicolas Younan

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2011

View PDFchevron_right

DATA MINING AND MACHINE LEARNING IN EARTH OBSERVATION -AN APPLICATION FOR TRACKING HISTORICAL ALGAL BLOOMS

Alexandria Dominique Farias, Computer Science & Information Technology (CS & IT) Computer Science Conference Proceedings (CSCP)

View PDFchevron_right

Spatiotemporal Deep-Learning-Based Algal Bloom Prediction for Lake Okeechobee Using Multisource Data Fusion

Sasha Fung

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

View PDFchevron_right

LSTM Networks to Improve the Prediction of Harmful Algal Blooms in the West Coast of Sabah

NORMAH BTE MAAN FS

International Journal of Environmental Research and Public Health

View PDFchevron_right

Ensemble Methodology Using Multistage Learning for Improved Detection of Harmful Algal Blooms

Nicolas Younan

IEEE Geoscience and Remote Sensing Letters, 2000

View PDFchevron_right

Machine Learning-Based Early Warning Level Prediction for Cyanobacterial Blooms Using Environmental Variable Selection and Data Resampling

Jae-Ki Shin

Toxics

View PDFchevron_right

Deep-Learning-Based Approach for Prediction of Algal Blooms

Subhasish Goswami

Sustainability, 2016

View PDFchevron_right

Development of a Coupled Spatiotemporal Algal Bloom Model for Coastal Areas: A Remote Sensing and Data Mining-Based Approach

mohamed sultan

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2016

View PDFchevron_right

SeaWiFS discrimination of harmful algal bloom evolution

Peter I Miller

International Journal of Remote Sensing, 2006

View PDFchevron_right

Forecasting Algal Blooms at a Surface Water System with Artificial Neural Network

Mary Poulton

2006

View PDFchevron_right

A novel method based on time series satellite data analysis to detect algal blooms

Marcelo Scavuzzo

Ecological Informatics, 2020

View PDFchevron_right

Mapping and Forecasting Onsets of Harmful Algal Blooms Using MODIS Data over Coastal Waters Surrounding Charlotte County, Florida

mohamed sultan

Remote Sensing

View PDFchevron_right

Inland harmful algal blooms (HABs) modeling using internet of things (IoT) system and deep learning

Ather Abbas

Environmental Engineering Research

View PDFchevron_right

Satellite retrievals of Karenia brevis harmful algal blooms in the West Florida shelf using neural networks and impacts of temporal variabilities

Ahmed El-habashi

Journal of Applied Remote Sensing

View PDFchevron_right

Harmful Algal Blooms Monitoring Using SENTINEL-2 Satellite Images

hassan khalili

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2019

View PDFchevron_right

Neural network modelling of coastal algal blooms

A.W. Jayawardena

Ecological Modelling, 2003

View PDFchevron_right

Machine Learning Classification Algorithms for Predicting Karenia brevis Blooms on the West Florida Shelf

Marvin Li

Journal of Marine Science and Engineering

View PDFchevron_right

Predicting Estuarine Algal Blooms Utilising Neural Network Modelling-A Preliminary Investigation

Peter Coad

View PDFchevron_right

Sensitivity of a Satellite Algorithm for Harmful Algal Bloom Discrimination to the Use of Laboratory Bio-optical Data for Training

Vera Veloso

Frontiers in Marine Science, 2020

View PDFchevron_right

Proactive management of estuarine algal blooms using an automated monitoring buoy coupled with an artificial neural network

Peter Coad

2014

View PDFchevron_right

A real time data driven algal bloom risk forecast system for mariculture management

Yahong Dong

Marine Pollution Bulletin, 2020

View PDFchevron_right

Satellite Retrievals of Karenia brevis Harmful Algal Blooms in the West Florida Shelf Using Neural Networks and Comparisons with Other Techniques

Ahmed El-habashi

Remote Sensing, 2016

View PDFchevron_right

Machine learning based marine water quality prediction for coastal hydro-environment management

K.W. Chau

Journal of Environmental Management, 2021

View PDFchevron_right

Coastal water quality prediction based on machine learning with feature interpretation and spatio-temporal analysis

Tomislav Lipic

2021

View PDFchevron_right

Detection of algal blooms in the North Sea using supervised classification of SeaWiFS reflectance imagery

steef peters

View PDFchevron_right

A Machine Learning Based Approach to Predict Ostreopsis Cf. Ovata Bloom Events from Meteo- Marine Forecasts

Ennio Ottaviani

Chemical engineering transactions, 2020

View PDFchevron_right

Towards spatial localisation of harmful algal blooms; statistics-based spatial anomaly detection

Peter I Miller

2005

View PDFchevron_right

Evaluating machine-learning models for coastal waters quality monitoring, bathymetry and coastline detection using remote sensing data

Hafez Ahmad

View PDFchevron_right

An adaptive approach to detect high-biomass algal blooms from EO chlorophyll- a data in support of harmful algal bloom monitoring

Keith Davidson, Keith Davidson, Sarah Swan, Peter I Miller

Remote Sensing Letters, 2012

View PDFchevron_right

HABNet: Machine Learning, Remote Sensing-Based Detection of Harmful Algal Blooms (original) (raw)

Related papers