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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Cloud detection on small satellites based on lightweight U-net and image compression
TL;DR: The experiment results on advanced RISC machines-based embedded platform illustrate that by taking advantage of a mature image compression system in small satellites; the time cost and peak memory cost required by the neural network will be reduced significantly while the segment accuracy is only slightly decreased.
Journal ArticleDOI
Towards a polyalgorithm for land use change detection
Rishu Saxena,Layne T. Watson,Randolph H. Wynne,Evan B. Brooks,Valerie A. Thomas,Yang Zhiqiang,Robert E. Kennedy +6 more
TL;DR: The foundation of the proposed TSA based ‘polyalgorithm’ for LULCC is three algorithms (BFAST, EWMACD, and LandTrendR), precisely described mathematically, and chosen to be fundamentally distinct from each other in design and in the phenomena they capture.
Journal ArticleDOI
Identifying Biases in Global Tree Cover Products: A Case Study in Costa Rica
TL;DR: It is indicated that, in tropical regions, the GFC product is most accurate in areas with high, aseasonal rainfall, low relief, and low cropland area, indicating that forest product errors are spatially distributed along biophysical gradients and researchers should account for these spatial biases when attempting to analyze or generate forest map products.
Journal ArticleDOI
Unlocking the Australian Landsat Archive – From dark data to High Performance Data infrastructures
Matthew B. J. Purss,Adam Lewis,Simon Oliver,Alex Ip,Joshua Sixsmith,Ben Evans,Roger Edberg,Glenn Frankish,Lachlan Hurst,Tai Chan +9 more
TL;DR: The Unlocking the Landsat Archive project was set up in 2011 to address this issue and to help realize the true value and potential of these data as mentioned in this paper, which was the key outcome of the project was the migration of the raw Landsat data that was housed in tape archives at Geoscience Australia to High Performance Data facilities hosted by the National Computational Infrastructure (a super computer facility located at the Australian National University).
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P_Segnet and NP_Segnet: New Neural Network Architectures for Cloud Recognition of Remote Sensing Images
TL;DR: A realization of cloud recognition of remote sensing imagery based on SegNet architecture is described and the results have demonstrated the feasibility and practicality of using deep learning approach for cloud recognition in remote sensing images.
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.
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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.
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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.