Convolutional neural networks for global human settlements mapping from Sentinel-2 satellite imagery
Spatially consistent and up-to-date maps of human settlements are crucial for addressing
policies related to urbanization and sustainability, especially in the era of an increasingly …
policies related to urbanization and sustainability, especially in the era of an increasingly …
Comparing CNNs and random forests for Landsat image segmentation trained on a large proxy land cover dataset
Land cover mapping from satellite images has progressed from visual and statistical
approaches to Random Forests (RFs) and, more recently, advanced image recognition …
approaches to Random Forests (RFs) and, more recently, advanced image recognition …
Spatio-temporal deep learning approach to map deforestation in amazon rainforest
We address the task of mapping deforested areas in the Brazilian Amazon. Accurate maps
are an important tool for informing effective deforestation containment policies. The main …
are an important tool for informing effective deforestation containment policies. The main …
Pseudo-labeling approach for land cover classification through remote sensing observations with noisy labels
Satellite data allows us to solve a wide range of challenging tasks remotely, including
monitoring changing environmental conditions, assessing resources, and evaluating …
monitoring changing environmental conditions, assessing resources, and evaluating …
Snow detection in alpine regions with Convolutional Neural Networks: discriminating snow from cold clouds and water body
Y Lu, T James, C Schillaci, A Lipani - GIScience & Remote …, 2022 - Taylor & Francis
Accurately monitoring the variation of snow cover from remote sensing is vital since it assists
in various fields including prediction of floods, control of runoff values, and the ice regime of …
in various fields including prediction of floods, control of runoff values, and the ice regime of …
[HTML][HTML] Benchmark for building segmentation on up-scaled Sentinel-2 imagery
Currently, we can solve a wide range of tasks using computer vision algorithms, which
reduce manual labor and enable rapid analysis of the environment. The remote sensing …
reduce manual labor and enable rapid analysis of the environment. The remote sensing …
Towards Amazon forest restoration: automatic detection of species from UAV imagery
MM Moura, LES de Oliveira, CR Sanquetta, A Bastos… - Remote Sensing, 2021 - mdpi.com
Precise assessments of forest species' composition help analyze biodiversity patterns,
estimate wood stocks, and improve carbon stock estimates. Therefore, the objective of this …
estimate wood stocks, and improve carbon stock estimates. Therefore, the objective of this …
[HTML][HTML] U-Net convolutional neural network models for detecting and quantifying placer mining disturbances at watershed scales
Placer mining is a mineral extraction method in floodplains that involves the removal of earth
material to access mineral-laden sediments, a process that can have significant and long …
material to access mineral-laden sediments, a process that can have significant and long …
[HTML][HTML] Crop classification of satellite imagery using synthetic multitemporal and multispectral images in convolutional neural networks
The demand for new tools for mass remote sensing of crops, combined with the open and
free availability of satellite imagery, has prompted the development of new methods for crop …
free availability of satellite imagery, has prompted the development of new methods for crop …
Forest segmentation with spatial pyramid pooling modules: a surveillance system based on satellite images
FX Ru, MA Zulkifley, SR Abdani, M Spraggon - Forests, 2023 - mdpi.com
The global deforestation rate continues to worsen each year, and will eventually lead to
various negative consequences for humans and the environment. It is essential to develop …
various negative consequences for humans and the environment. It is essential to develop …