This paper reviews some of the challenges posed by the huge growth of experimental data
generated by the new generation of large-scale experiments at UK national facilities at the …

Mapping deforestation is an essential step in the process of managing tropical rainforests. It
lets us understand and monitor both legal and illegal deforestation and its implications …

Cloud detection is a crucial preprocessing step for optical satellite remote sensing (RS)
images. This article focuses on the cloud detection for RS imagery with cloud-snow …

Clouds and cloud shadows heavily affect the quality of the remote sensing images and their
application potential. Algorithms have been developed for detecting, removing, and …

Accurate, automated cloud and cloud shadow detection is a key component of the
processing needed to prepare optical satellite imagery for scientific analysis. Many existing …

The change detection (CD) methods explore the potential of remote sensing (RS) spatial
datasets in various land use/land cover (LU/LC) applications. These methods are used to …

Accurate burned area information is needed to assess the impacts of wildfires on people,
communities, and natural ecosystems. Various burned area detection methods have been …

Identifying high-quality (ie, relatively clear) measurements of surface conditions is a near-
universal first step in working with optical satellite imagery. Many cloud masking algorithms …

Cloud detection is critical in remote sensing image processing, and convolutional neural
networks (CNNs) have significantly advanced this field. However, traditional CNNs primarily …

Global biophysical products at decametric resolution derived from Sentinel-2 imagery have
emerged as a promising dataset for fine-scale ecosystem modeling and agricultural …