Multispectral satellite imagery and machine learning for the extraction of shoreline indicators

E McAllister, A Payo, A Novellino, T Dolphin… - Coastal …, 2022‏ - Elsevier
Abstract Analysis of shoreline change is fundamental to a broad range of investigations
undertaken by coastal scientists, coastal engineers, and coastal managers. Multispectral …

Coastal pollution analysis for environmental health and ecological safety using deep learning technique

T Sathish, SU Maheswari, V Balaji, P Nirupama… - … in Engineering Software, 2023‏ - Elsevier
Environmental degradation and loss of biodiversity occur widely in marine and coastal
regions. The coastal ecosystems have diverse components, including mammals …

A deep learning method of water body extraction from high resolution remote sensing images with multisensors

M Li, P Wu, B Wang, H Park, H Yang… - IEEE Journal of Selected …, 2021‏ - ieeexplore.ieee.org
Water body extraction from remote sensing images is an important task. Deep learning has
become a more popular method for extracting water bodies from remote sensing images …

Assessing the accuracy of Sentinel-2 instantaneous subpixel shorelines using synchronous UAV ground truth surveys

N Pucino, DM Kennedy, M Young… - Remote Sensing of …, 2022‏ - Elsevier
Due to recent technological advancements in the field of cloud-based satellite remote
sensing, the barriers to global analysis ready dataset access and processing have lowered …

[HTML][HTML] Coastal wetland shoreline change monitoring: A comparison of shorelines from high-resolution WorldView Satellite imagery, aerial Imagery, and field surveys

KEL Smith, JF Terrano, JL Pitchford, MJ Archer - Remote Sensing, 2021‏ - mdpi.com
Shoreline change analysis is an important environmental monitoring tool for evaluating
coastal exposure to erosion hazards, particularly for vulnerable habitats such as coastal …

Machine learning prediction of ore deposit genetic type using magnetite geochemistry

P Zhang, Z Zhang, J Yang, Q Cheng - Natural Resources Research, 2023‏ - Springer
Magnetite geochemistry is crucial for the discrimination of ore deposit genetic type.
Traditional two-dimensional discrimination diagrams based on particular data for limited …

[HTML][HTML] Coast type based accuracy assessment for coastline extraction from satellite image with machine learning classifiers

Oİ Çelik, C Gazioğlu - The Egyptian Journal of Remote Sensing and Space …, 2022‏ - Elsevier
Abstract Machine learning (ML) classifiers provide convenience and accuracy in coastline
extraction compared to traditional methods and image processing techniques. In literature …

Comparing activation functions in modeling shoreline variation using multilayer perceptron neural network

JC Chen, YM Wang - Water, 2020‏ - mdpi.com
The study has modeled shoreline changes by using a multilayer perceptron (MLP) neural
network with the data collected from five beaches in southern Taiwan. The data included …

[HTML][HTML] Improving the accuracy of satellite-derived bathymetry using multi-layer perceptron and random forest regression methods: A case study of Tavşan Island

Oİ Çelik, G Büyüksalih, C Gazioğlu - Journal of Marine Science and …, 2023‏ - mdpi.com
The spatial and spectral information brought by the Very High Resolution (VHR) and
multispectral satellite images present an advantage for Satellite-Derived Bathymetry (SDB) …

RETRACTED ARTICLE: Research on image classification method based on convolutional neural network

D Li, L Deng, Z Cai - Neural Computing and Applications, 2021‏ - Springer
Image classification method is currently the more popular image technology, but it still has
certain problems in practice. In order to improve the image classification effect, this study …