The global volume of digital data is expected to reach 175 zettabytes by 2025. The volume,
variety and velocity of water-related data are increasing due to large-scale sensor networks …

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

Leaf area index (LAI) is a terrestrial essential climate variable that is required in a variety of
ecosystem and climate models. The Global LAnd Surface Satellite (GLASS) LAI product has …

Abstract The PlanetScope CubeSat constellation is providing unprecedented global
coverage, visible to near infrared, atmospherically corrected, 3 m imagery. The revisit …

The advances in remote sensing sensors during the last two decades have led to the
production of very high spatial resolution multispectral images. In order to adapt to this rapid …

One of the major goals of tomorrow's agriculture is to increase agricultural productivity but
above all the quality of production while significantly reducing the use of inputs. Meeting this …

In recent years, deep convolutional neural networks (DCNNs) have made significant
progress in cloud detection tasks, and the detection accuracy has been greatly improved …

Cloud cover is a common and inevitable phenomenon that often hinders the usability of
optical remote sensing (RS) image data and further interferes with continuous cartography …

Applications of digital agricultural services often require either farmers or their advisers to
provide digital records of their field boundaries. Automatic extraction of field boundaries from …

Accurate quantitative precipitation estimation (QPE) is essential for various applications,
including land surface modeling, flood forecasting, drought monitoring and prediction. In situ …