Zobrazeno 1 - 10
of 16
pro vyhledávání: '"Willem Marais"'
Publikováno v:
Atmospheric Measurement Techniques, Vol 13, Pp 5459-5480 (2020)
Current cloud and aerosol identification methods for multispectral radiometers, such as the Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS), employ multichannel spectral tests on individual
Autor:
Min Oo, Angela Benedetti, Jeff McQueen, Edward J. Hyer, Robert E. Holz, Juli I. Rubin, Peng Xian, Steven D. Miller, Brent N. Holben, Jianglong Zhang, Willem Marais, Thomas F. Eck, Amanda Gumber, Peter Calarco, Taichu Tanaka, Jun Wang, Jeffrey S. Reid
Publikováno v:
IGARSS
Various forms of global compositional forecasting are now commonplace across the world's operational centers. Biomass burning smoke is often forecast just like other aspects of our weather to support numerous applications such as air quality, transpo
Publikováno v:
EPJ Web of Conferences, Vol 237, p 06012 (2020)
We have adapted the Poisson Total Variation lidar signal processing technique for Micro-Pulse DIAL water vapor estimates. This processing technique ingests data at 10 second-37.5 meter resolution where it adaptively adjusts the retrieval resolution b
Autor:
Willem Marais, Rebecca Willett
Publikováno v:
CAMSAP
This paper considers the denoising and reconstruction of images corrupted by Poisson noise. Poisson noise arises in the context of counting the emission or scattering of photons. In various application domains, such as astronomy and medical imaging,
Autor:
Marian B. Clayton, Robert E. Holz, Richard Ferrare, Sharon P. Burton, Detlef Müller, Rob K. Newsom, Willem Marais, John E. M. Goldsmith, Ralph Kuehn, Eduard Chemyakin, Tyler J. Thorsen, Edwin W. Eloranta
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1360bd3cde7fab46f9d296d11d3e3afd
https://doi.org/10.2172/1413741
https://doi.org/10.2172/1413741
Autor:
Waldo Kleynhans, Willem Marais, T. L. Grobler, Konrad J Wessels, Jan C. Olivier, F. van den Bergh, Brian P. Salmon
Publikováno v:
IEEE Transactions on Geoscience and Remote Sensing. 52:5072-5087
The extraction of information on land cover classes using unsupervised methods has always been of relevance to the remote sensing community. In this paper, a novel criterion is proposed, which extracts the inherent information in an unsupervised fash