Deep learning and earth observation to support the sustainable development goals: Current approaches, open challenges, and future opportunities
The synergistic combination of deep learning (DL) models and Earth observation (EO)
promises significant advances to support the Sustainable Development Goals (SDGs). New …
promises significant advances to support the Sustainable Development Goals (SDGs). New …
[HTML][HTML] Object detection and image segmentation with deep learning on Earth observation data: A review—Part II: Applications
In Earth observation (EO), large-scale land-surface dynamics are traditionally analyzed by
investigating aggregated classes. The increase in data with a very high spatial resolution …
investigating aggregated classes. The increase in data with a very high spatial resolution …
Deep learning meets SAR: Concepts, models, pitfalls, and perspectives
Deep learning in remote sensing has received considerable international hype, but it is
mostly limited to the evaluation of optical data. Although deep learning has been introduced …
mostly limited to the evaluation of optical data. Although deep learning has been introduced …
Pansharpening by convolutional neural networks in the full resolution framework
In recent years, there has been a growing interest in deep learning-based pansharpening.
Thus far, research has mainly focused on architectures. Nonetheless, model training is an …
Thus far, research has mainly focused on architectures. Nonetheless, model training is an …
Deep learning-based automated forest health diagnosis from aerial images
Global climate change has had a drastic impact on our environment. Previous study showed
that pest disaster occured from global climate change may cause a tremendous number of …
that pest disaster occured from global climate change may cause a tremendous number of …
Extending deep learning approaches for forest disturbance segmentation on very high‐resolution satellite images
DE Kislov, KA Korznikov, J Altman… - Remote Sensing in …, 2021 - Wiley Online Library
Accurate remote detection of various forest disturbances is a challenge in global
environmental monitoring. Addressing this issue is crucial for forest health assessment …
environmental monitoring. Addressing this issue is crucial for forest health assessment …
Amazon forest cover change mapping based on semantic segmentation by U-Nets
L Bragagnolo, RV da Silva, JMV Grzybowski - Ecological Informatics, 2021 - Elsevier
Deforestation remains a major concern with regard to climate change and the maintenance
of biodiversity. Meanwhile, the development of new image processing techniques and the …
of biodiversity. Meanwhile, the development of new image processing techniques and the …
GEDI elevation accuracy assessment: a case study of southwest Spain
Information about forest structures is becoming crucial to earth's global carbon cycle, forest
habitats, and biodiversity. The Global Ecosystem Dynamics Investigation (GEDI) provides 25 …
habitats, and biodiversity. The Global Ecosystem Dynamics Investigation (GEDI) provides 25 …
Deep learning and machine learning for Malaria detection: overview, challenges and future directions
To have the greatest impact, public health initiatives must be made using evidence-based
decision-making. Machine learning Algorithms are created to gather, store, process, and …
decision-making. Machine learning Algorithms are created to gather, store, process, and …
[HTML][HTML] A detail-preserving cross-scale learning strategy for CNN-based pansharpening
The fusion of a single panchromatic (PAN) band with a lower resolution multispectral (MS)
image to raise the MS resolution to that of the PAN is known as pansharpening. In the last …
image to raise the MS resolution to that of the PAN is known as pansharpening. In the last …