Journal ArticleDOI
Object-based cloud and cloud shadow detection in Landsat imagery
Zhe Zhu,Curtis E. Woodcock +1 more
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TLDR
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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Combining SAR and optical satellite image time series for tropical forest monitoring
TL;DR: In this article, the authors presented a novel multi-sensor time series correlation and fusion (MulTiFuse) approach that was applied to fuse Landsat NDVI and ALOS PALSAR time series.
Journal ArticleDOI
Beyond deforestation: Differences in long-term regrowth dynamics across land use regimes in southern Amazonia
Hannes Müller,Philippe Rufin,Patrick Griffiths,Letícia de Barros Viana Hissa,Patrick Hostert +4 more
TL;DR: In this article, the authors used a 29-year time series of Landsat images to extract regrowth extent, duration, lag time between deforestation and regrowth, and frequency of regrowth cycles.
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Estimating burn severity and carbon emissions from a historic megafire in boreal forests of China.
TL;DR: This study combined field and remote sensing data to map four burn severity classes and calculated combustion efficiency in terms of the biomass immediately consumed in the fire to provide an important basis for carbon emission estimation and understanding the impacts of megafires.
Journal ArticleDOI
Spatially-Explicit Prediction of Wildfire Burn Probability Using Remotely-Sensed and Ancillary Data
TL;DR: In this article, the authors present spatially-explicit forest disturbance history and forest structure estimated using remotest forest structure estimates using a remote forest surveyor, which is a critical process shaping the structure and composition of forest landscapes of western Canada.
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Confidence Levels, Sensitivity, and the Role of Bathymetry in Coral Reef Remote Sensing
TL;DR: Analysis indicates that derived benthic reflectance is most sensitive to errors in bathymetry at shallower depths, yet remains significant at all depths, which confirms the suitability of the model for deriving water depth in complex coral reef environments, and expands the ability to achieve automated widespread mapping and monitoring of global coral reefs.
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.