Journal ArticleDOI
Object-based cloud and cloud shadow detection in Landsat imagery
Zhe Zhu,Curtis E. Woodcock +1 more
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The goal is development of a cloud and cloud shadow detection algorithm suitable for routine usage with Landsat images and as high as 96.4%.About:
This article is published in Remote Sensing of Environment.The article was published on 2012-03-15. It has received 1620 citations till now. The article focuses on the topics: Cloud top & Cloud fraction.read more
Citations
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Journal ArticleDOI
Refined UNet V2: End-to-End Patch-Wise Network for Noise-Free Cloud and Shadow Segmentation
TL;DR: The end-to-end Refined UNet v2 is quantitatively comparable to Refine UNet, but can visually outperform that from the noise-free segmentation perspective, and the comparison of time consumption supports the potential efficiency of the v2.
Journal ArticleDOI
Coastal dynamics of Northern Australia – Insights from the Landsat Data Cube
TL;DR: In this paper, the authors demonstrate the capacity of detailed time-series of remotely sensed data to identify notable changes and trends in coastal morphology and vegetation over the last three decades, and illustrate how these data can help identify drivers of change, and areas that require further investigation.
Journal ArticleDOI
Plume Height Time-Series Retrieval Using Shadow in Single Spatial Resolution Satellite Images
TL;DR: The shadow technique defined here allows downwind plume height profiles and mass discharge rate time series to be built over distances of up to 260 km and periods of 24 h, depending on vent location in the image, wind speed, and direction.
Proceedings ArticleDOI
Cloud filtering for Landsat TM satellite images using multiple temporal mosaicing
TL;DR: A method called multiple temporal mosaicing is proposed as it is mimicking the process of mosacing pieces from images to obtain a whole image and the resulting images show the effectiveness of this method clearly.
Journal ArticleDOI
Multi-season unmixing of vegetation class fractions across diverse Californian ecoregions using simulated spaceborne imaging spectroscopy data
Akpona Okujeni,Clemens Jänicke,Clemens Jänicke,Sam Cooper,David Frantz,Patrick Hostert,Matthew L. Clark,Karl Segl,Sebastian van der Linden +8 more
TL;DR: In this paper, the authors investigated the potential of multi-season unmixing of simulated EnMAP data for vegetation class fraction mapping across diverse natural and semi-natural ecoregions in California, USA.
References
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Book
Morphological Image Analysis: Principles and Applications
TL;DR: This self-contained volume will be valuable to all engineers, scientists, and practitioners interested in the analysis and processing of digital images.
Journal ArticleDOI
A Landsat surface reflectance dataset for North America, 1990-2000
Jeffrey G. Masek,Eric Vermote,Nazmi Saleous,Robert E. Wolfe,Forrest G. Hall,Karl F. Huemmrich,Feng Gao,J. Kutler,Teng-Kui Lim +8 more
TL;DR: Initial comparisons with ground-based optical thickness measurements and simultaneously acquired MODIS imagery indicate comparable uncertainty in Landsat surface reflectance compared to the standard MODIS reflectance product.
Journal ArticleDOI
Discriminating clear sky from clouds with MODIS
Steven A. Ackerman,Kathleen I. Strabala,W. Paul Menzel,Richard A. Frey,Christopher C. Moeller,Liam E. Gumley +5 more
TL;DR: The MODIS cloud mask algorithm as discussed by the authors uses several cloud detection tests to indicate a level of confidence that the MEDIS is observing clear skies, which is ancillary input to MEDIS land, ocean, and atmosphere science algorithms to suggest processing options.
Journal ArticleDOI
Calculation of radiative fluxes from the surface to top of atmosphere based on ISCCP and other global data sets: Refinements of the radiative transfer model and the input data
TL;DR: Zhang et al. as discussed by the authors used a more advanced NASA Goddard Institute for Space Studies (GISS) radiative transfer model and improved ISCCP cloud climatology and ancillary data sets.
Journal ArticleDOI
Spectral signature of alpine snow cover from the Landsat Thematic Mapper.
Jeff Dozier,Jeff Dozier +1 more
TL;DR: In this article, the spectral signatures of the Landsat TM images of the Sierra Nevada were analyzed to distinguish several classes of snow from other surface covers, and a number of TM images were used for automatic analysis of alpine snow cover.