The presence of clouds prevents optical satellite imaging systems from obtaining useful
Earth observation information and negatively affects the processing and application of …

The discipline of land change science has been evolving rapidly in the past decades.
Remote sensing played a major role in one of the essential components of land change …

Formal planning and development of what became the first Landsat satellite commenced
over 50 years ago in 1967. Now, having collected earth observation data for well over four …

We developed the Function of mask (Fmask) 4.0 algorithm for automated cloud and cloud
shadow detection in Landsats 4–8 and Sentinel-2 images. Three major innovative …

We developed a new algorithm for COntinuous monitoring of Land Disturbance (COLD)
using Landsat time series. COLD can detect many kinds of land disturbance continuously as …

We proposed a new image compositing algorithm (MAX-RNB) based on the maximum ratio
of Near Infrared (NIR) to Blue band (RNB), and evaluated it together with nine other …

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 …

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 …

Frequent cloud cover and fast regrowth often hamper topical forest disturbance monitoring
with optical data. This study aims at overcoming these limitations by combining dense time …

Anthropogenic and natural disturbances can cause degradation of ecosystems, reducing
their capacity to sustain biodiversity and provide ecosystem services. Understanding the …