Google earth engine cloud computing platform for remote sensing big data applications: A comprehensive review
M Amani, A Ghorbanian, SA Ahmadi… - IEEE Journal of …, 2020 - ieeexplore.ieee.org
Remote sensing (RS) systems have been collecting massive volumes of datasets for
decades, managing and analyzing of which are not practical using common software …
decades, managing and analyzing of which are not practical using common software …
Google Earth Engine for geo-big data applications: A meta-analysis and systematic review
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 …
large-scale environmental monitoring and analysis. The free-to-use GEE platform provides …
Multi-sensor remote sensing for drought characterization: current status, opportunities and a roadmap for the future
Satellite based remote sensing offers one of the few approaches able to monitor the spatial
and temporal development of regional to continental scale droughts. A unique element of …
and temporal development of regional to continental scale droughts. A unique element of …
Benefits of the free and open Landsat data policy
Abstract The United States (US) federal government provides imagery obtained by federally
funded Earth Observation satellites typically at no cost. For many years Landsat was an …
funded Earth Observation satellites typically at no cost. For many years Landsat was an …
Deep learning classification of land cover and crop types using remote sensing data
Deep learning (DL) is a powerful state-of-the-art technique for image processing including
remote sensing (RS) images. This letter describes a multilevel DL architecture that targets …
remote sensing (RS) images. This letter describes a multilevel DL architecture that targets …
How can Big Data and machine learning benefit environment and water management: a survey of methods, applications, and future directions
AY Sun, BR Scanlon - Environmental Research Letters, 2019 - iopscience.iop.org
Big Data and machine learning (ML) technologies have the potential to impact many facets
of environment and water management (EWM). Big Data are information assets …
of environment and water management (EWM). Big Data are information assets …
Comprehensive survey of deep learning in remote sensing: theories, tools, and challenges for the community
In recent years, deep learning (DL), a rebranding of neural networks (NNs), has risen to the
top in numerous areas, namely computer vision (CV), speech recognition, and natural …
top in numerous areas, namely computer vision (CV), speech recognition, and natural …
Machine learning classification of mediterranean forest habitats in google earth engine based on seasonal sentinel-2 time-series and input image composition …
The sustainable management of natural heritage is presently considered a global strategic
issue. Owing to the ever-growing availability of free data and software, remote sensing (RS) …
issue. Owing to the ever-growing availability of free data and software, remote sensing (RS) …
Image retrieval from remote sensing big data: A survey
The blooming proliferation of aeronautics and astronautics platforms, together with the ever-
increasing remote sensing imaging sensors on these platforms, has led to the formation of …
increasing remote sensing imaging sensors on these platforms, has led to the formation of …
Learning deep semantic segmentation network under multiple weakly-supervised constraints for cross-domain remote sensing image semantic segmentation
Due to its wide applications, remote sensing (RS) image semantic segmentation has
attracted increasing research interest in recent years. Benefiting from its hierarchical abstract …
attracted increasing research interest in recent years. Benefiting from its hierarchical abstract …