Google Earth Engine for geo-big data applications: A meta-analysis and systematic review

H Tamiminia, B Salehi, M Mahdianpari… - ISPRS journal of …, 2020 - Elsevier
Abstract Google Earth Engine (GEE) is a cloud-based geospatial processing platform for
large-scale environmental monitoring and analysis. The free-to-use GEE platform provides …

Machine learning information fusion in Earth observation: A comprehensive review of methods, applications and data sources

S Salcedo-Sanz, P Ghamisi, M Piles, M Werner… - Information …, 2020 - Elsevier
This paper reviews the most important information fusion data-driven algorithms based on
Machine Learning (ML) techniques for problems in Earth observation. Nowadays we …

Rapid and robust monitoring of flood events using Sentinel-1 and Landsat data on the Google Earth Engine

B DeVries, C Huang, J Armston, W Huang… - Remote Sensing of …, 2020 - Elsevier
Synthetic aperture radar (SAR) sensors represent an indispensable data source for flood
disaster planners and responders, given their ability to image the Earth's surface nearly …

Flash-flood hazard assessment using ensembles and Bayesian-based machine learning models: Application of the simulated annealing feature selection method

FS Hosseini, B Choubin, A Mosavi, N Nabipour… - Science of the total …, 2020 - Elsevier
Flash-floods are increasingly recognized as a frequent natural hazard worldwide. Iran has
been among the most devastated regions affected by the major floods. While the temporal …

A novel deep learning neural network approach for predicting flash flood susceptibility: A case study at a high frequency tropical storm area

DT Bui, ND Hoang, F Martínez-Álvarez, PTT Ngo… - Science of The Total …, 2020 - Elsevier
This research proposes and evaluates a new approach for flash flood susceptibility map**
based on Deep Learning Neural Network (DLNN)) algorithm, with a case study at a high …

Identifying floods and flood-affected paddy rice fields in Bangladesh based on Sentinel-1 imagery and Google Earth Engine

M Singha, J Dong, S Sarmah, N You, Y Zhou… - ISPRS Journal of …, 2020 - Elsevier
Globally, flooding is the leading cause of natural disaster related deaths, especially in
Bangladesh where approximately one third of national area gets flooded annually by …

Applications of Google Earth Engine in fluvial geomorphology for detecting river channel change

RJ Boothroyd, RD Williams, TB Hoey… - Wiley …, 2021 - Wiley Online Library
Cloud‐based computing, access to big geospatial data, and virtualization, whereby users
are freed from computational hardware and data management logistics, could revolutionize …

A network combining a transformer and a convolutional neural network for remote sensing image change detection

G Wang, B Li, T Zhang, S Zhang - Remote Sensing, 2022 - mdpi.com
With the development of deep learning techniques in the field of remote sensing change
detection, many change detection algorithms based on convolutional neural networks …

A method for automatic and rapid map** of water surfaces from sentinel-1 imagery

F Bioresita, A Puissant, A Stumpf, JP Malet - Remote Sensing, 2018 - mdpi.com
Reliable information about the spatial distribution of surface waters is critically important in
various scientific disciplines. Synthetic Aperture Radar (SAR) is an effective way to detect …

Automated extraction of surface water extent from Sentinel-1 data

W Huang, B DeVries, C Huang, MW Lang, JW Jones… - Remote Sensing, 2018 - mdpi.com
Accurately quantifying surface water extent in wetlands is critical to understanding their role
in ecosystem processes. However, current regional-to global-scale surface water products …