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
Annual land-cover mapping based on multi-temporal cloud-contaminated landsat images
TL;DR: The novel multi-temporal Landsat classification method presented in this paper can deal with the cloud-contamination problem and produce accurate annual land-cover mapping using multi- Temporal cloud- Contaminated images, which is of importance for regional and global land- cover mapping.
Journal ArticleDOI
A Framework of Spatio-Temporal Fusion Algorithm Selection for Landsat NDVI Time Series Construction
TL;DR: Phenological stability analysis demonstrated that the Landsat NDVI time series established by multiple spatio-temporal algorithms could effectively avoid phenological fluctuations in the time series constructed by a single fusion algorithm.
Posted ContentDOI
Complementarity Between Sentinel-1 and Landsat 8 Imagery for Built-Up Mapping in Sub-Saharan Africa
TL;DR: In this paper, the authors assess the complementarity of the Landsat 8 and Sentinel-1 sensors to map built-up areas in twelve Sub-Saharan African urban areas, using a pixel-level supervised classification based on the Random Forest classifier.
Journal ArticleDOI
Automated Mosaicking of Sentinel-2 Satellite Imagery
TL;DR: The Tmask algorithm for cloud detection is improved by using a parallax method to produce an initial cloud layer and by using an object-based cloud and shadow approach to remove false cloud detections.
Journal ArticleDOI
Impacts of Aerosols on the Retreat of the Sierra Nevada Glaciers in California
Hesham El-Askary,Hesham El-Askary,J. Li,Wenzhao Li,Thomas C. Piechota,Tommy Ta,Ariane Jong,Xinyi Zhang,Tiantian Yang +8 more
TL;DR: In this article, the authors evaluated changes in the snowpack during the winter and summer seasons from 2000 till 2016 and determined the relationship between aerosols and the retreat of glaciers in the Sierra Nevada.
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.