Cloud and cloud shadow detection for optical satellite imagery: Features, algorithms, validation, and prospects
The presence of clouds prevents optical satellite imaging systems from obtaining useful
Earth observation information and negatively affects the processing and application of …
Earth observation information and negatively affects the processing and application of …
Advancing 3D point cloud understanding through deep transfer learning: A comprehensive survey
The 3D point cloud (3DPC) has significantly evolved and benefited from the advance of
deep learning (DL). However, the latter faces various issues, including the lack of data or …
deep learning (DL). However, the latter faces various issues, including the lack of data or …
Towards global flood map** onboard low cost satellites with machine learning
Spaceborne Earth observation is a key technology for flood response, offering valuable
information to decision makers on the ground. Very large constellations of small, nano …
information to decision makers on the ground. Very large constellations of small, nano …
HyperLi-Net: A hyper-light deep learning network for high-accurate and high-speed ship detection from synthetic aperture radar imagery
Abstract Ship detection from Synthetic Aperture Radar (SAR) imagery is attracting increasing
attention due to its great value in ocean. However, existing most studies are frequently …
attention due to its great value in ocean. However, existing most studies are frequently …
[LIVRE][B] Deep learning for the Earth Sciences: A comprehensive approach to remote sensing, climate science and geosciences
DEEP LEARNING FOR THE EARTH SCIENCES Explore this insightful treatment of deep
learning in the field of earth sciences, from four leading voices Deep learning is a …
learning in the field of earth sciences, from four leading voices Deep learning is a …
Active fire detection in Landsat-8 imagery: A large-scale dataset and a deep-learning study
GH de Almeida Pereira, AM Fusioka, BT Nassu… - ISPRS Journal of …, 2021 - Elsevier
Active fire detection in satellite imagery is of critical importance to the management of
environmental conservation policies, supporting decision-making and law enforcement. This …
environmental conservation policies, supporting decision-making and law enforcement. This …
Deep learning high resolution burned area map** by transfer learning from Landsat-8 to PlanetScope
High spatial resolution commercial satellite data provide new opportunities for terrestrial
monitoring. The recent availability of near-daily 3 m observations provided by the …
monitoring. The recent availability of near-daily 3 m observations provided by the …
[HTML][HTML] Deep transfer learning of global spectra for local soil carbon monitoring
There is global interest in spectroscopy and the development of large and diverse soil
spectral libraries (SSL) to model soil organic carbon (SOC) and monitor, report, and verify …
spectral libraries (SSL) to model soil organic carbon (SOC) and monitor, report, and verify …
Deep learning for processing and analysis of remote sensing big data: A technical review
In recent years, the rapid development of Earth observation technology has produced an
increasing growth in remote sensing big data, posing serious challenges for effective and …
increasing growth in remote sensing big data, posing serious challenges for effective and …
[HTML][HTML] A hybrid generative adversarial network for weakly-supervised cloud detection in multispectral images
Cloud detection is a crucial step in the optical satellite image processing pipeline for Earth
observation. Clouds in optical remote sensing images seriously affect the visibility of the …
observation. Clouds in optical remote sensing images seriously affect the visibility of the …