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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Remote sensing for wetland classification: a comprehensive review
TL;DR: The most important conclusions drawn from the literature are that the red edge and near-infrared bands are the best optical bands for wetland delineation and small incidence angles, long wavelengths, and horizontal transmission and reception polarization are appropriate for mapping forested wetlands.
Journal ArticleDOI
Seasonal composite Landsat TM/ETM+ images using the medoid (a multi-dimensional median)
TL;DR: An alternative based on the medoid (in reflectance space) over the time period is proposed, which is robust against extreme values, and appears to be better at producing imagery which is representative of the timeperiod.
Journal ArticleDOI
Automated Detection of Cloud and Cloud Shadow in Single-Date Landsat Imagery Using Neural Networks and Spatial Post-Processing
M. Joseph Hughes,Daniel J. Hayes +1 more
TL;DR: A novel algorithm to identify and classify clouds and cloud shadow, SPARCS: Spatial Procedures for Automated Removal of Cloud and Shadow, is developed, which provides a measure of uncertainty in its classification that can be exploited by other algorithms that require clear sky pixels.
Journal ArticleDOI
Mapping forest change using stacked generalization: An ensemble approach
Sean P. Healey,Warren B. Cohen,Zhiqiang Yang,C. Kenneth Brewer,Evan B. Brooks,Noel Gorelick,Alexander J. Hernandez,Chengquan Huang,M. Joseph Hughes,Robert E. Kennedy,Thomas R. Loveland,Gretchen G. Moisen,Todd A. Schroeder,Stephen V. Stehman,James E. Vogelmann,Curtis E. Woodcock,Limin Yang,Zhe Zhu +17 more
TL;DR: Stacking using a Random Forests model cut omission and commission error rates in half in many cases in relation to individual change detection algorithms, and cut error rates by one quarter compared to more conventional parametric stacking.
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Mass data processing of time series Landsat imagery: pixels to data products for forest monitoring
Txomin Hermosilla,Michael A. Wulder,Joanne C. White,Nicholas C. Coops,Geordie W. Hobart,Lorraine B. Campbell +5 more
TL;DR: A project characterizing the change history of Canada’s forested ecosystems with a time series of data representing 1984–2012 is summarized, providing baseline information and nationally consistent data source to quantify and characterize changes in foresting ecosystems.
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.