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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Monitoring temperate forest degradation on Google Earth Engine using Landsat time series analysis
Shijuan Chen,Curtis E. Woodcock,Eric L. Bullock,Paulo Arévalo,Paata Torchinava,Siqi Peng,Pontus Olofsson +6 more
TL;DR: In this paper, the authors present an approach, Continuous Change Detection and Classification - Spectral Mixture Analysis (CCDC-SMA), that combines time series analysis and spectral mixture analysis running on GEE for monitoring abrupt and gradual forest degradation in temperate regions.
Journal ArticleDOI
Assessing global Sentinel-2 coverage dynamics and data availability for operational Earth observation (EO) applications using the EO-Compass
TL;DR: An assessment of the metadata for all accessible Sentinel-2 Level-1C scenes acquired in 2017 is presented, enabling the spatio-temporal coverage and availability to be quantified, including scene availability and cloudiness.
Journal ArticleDOI
Imaging Phenology; Scaling From Camera Plots to Landscapes
TL;DR: In this paper, the applicability and accuracy of Landsat derived phenology curves beyond deciduous stands into more mixed stands and conifer dominated forest types in the Rocky Mountains and foothills in Alberta, Canada.
Journal ArticleDOI
Expansion Analysis of Yangtze River Delta Urban Agglomeration Using DMSP/OLS Nighttime Light Imagery for 1993 to 2012
TL;DR: The results show that the urban expansion of the YRDUA occurred at an increasing rate from 1993–2007 and then declined after 2007 with the onset of the global financial crisis.
Journal ArticleDOI
Comparison of Cloud Cover Detection Algorithms on Sentinel–2 Images of the Amazon Tropical Forest
Alber Sanchez,Michelle Cristina Araujo Picoli,Gilberto Camara,Pedro R. Andrade,Michel Eustáquio Dantas Chaves,Sarah Lechler,Anderson R. Soares,Rennan F. B. Marujo,Rolf Simoes,Karine Reis Ferreira,Gilberto Ribeiro de Queiroz +10 more
TL;DR: The results point out that FMask 4 has the best overall accuracy on images of the Amazon region (90%), followed by Sen2Cor’s (79%), MAJA (69%), and S2cloudless (52%).
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.
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.