The quality and accuracy of remote sensing instruments continue to increase, allowing
geoscientists to perform various quantitative retrieval applications to observe the …

Quantitative retrieval is a growing area in remote sensing due to the rapid development of
remote instruments and retrieval algorithms. The aerosol optical depth (AOD) is a significant …

The quality and accuracy of remote sensing instruments have been improved significantly,
however, rapid processing of large-scale remote sensing data becomes the bottleneck for …

Spatiotemporal residual noise in terrestrial earth observation products, often caused by
unfavorable atmospheric conditions, impedes their broad applications. Most users prefer to …

Applications of satellite data in areas such as weather tracking and modeling, ecosystem
monitoring, wildfire detection, and land-cover change are heavily dependent on the tradeoffs …

Geographic phenomena evolve in a four-dimensional spatiotemporal world. To capture the
geographical phenomena at different scales, large amount of data (big data) are produced …

Massive, large-region coverage, multi-temporal, multi-spectral remote sensing (RS) datasets
are employed widely due to the increasing requirements for accurate and up-to-date …

Database support for multidimensional arrays is an area of growing importance; a variety of
highvolume applications such as spatio-temporal data management and statistics/OLAP …

With the remarkable development and progress of earth-observation techniques, remote
sensing data keep growing rapidly and their volume has reached exabyte scale. However …

With the rapid advancement of Earth Observation systems, Earth Observation data has been
collected and accumulated at an unprecedented fast rate. Earth Observation Big Data …