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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Bag-of-Words and Object-Based Classification for Cloud Extraction From Satellite Imagery
Yi Yuan,Xiangyun Hu +1 more
TL;DR: A method of automatic cloud detection is proposed based on object classification of image features based on the bag-of-words (BOW) model to deal with the highly varying patterns of clouds.
Journal ArticleDOI
Assessing spatial-temporal dynamics of urban expansion, vegetation greenness and photosynthesis in megacity Shanghai, China during 2000-2016
TL;DR: In this paper, the authors quantified the changes in impervious surface area (ISA) and assessed the impacts of urbanization on vegetation greenness (enhanced vegetation index (EVI)), and gross primary production (GPP) in megacity Shanghai during 2000-2016.
Journal ArticleDOI
Cloud detection algorithm for multi-modal satellite imagery using convolutional neural-networks (CNN)
TL;DR: A convolutional neural network algorithm for the detection of cloud and cloud shadow fields in multi-channel satellite imagery from World-View-2 and Sentinel-2, using their Red, Green, Blue, and Near-Infrared (RGB, NIR) channels.
Journal ArticleDOI
BAMS: A Tool for Supervised Burned Area Mapping Using Landsat Data
Aitor Bastarrika,Maite Alvarado,Karmele Artano,Maria Pilar Martinez,Amaia Mesanza,Leyre Torre,Rubén Ramo,Emilio Chuvieco +7 more
TL;DR: A new supervised burned area mapping software named BAMS (Burned Area Mapping Software) is presented in this paper, which computes several of the spectral indexes most commonly used in burned area detection and implements a two-phase supervised strategy to map areas burned between two Landsat multitemporal images.
Journal ArticleDOI
Monthly estimation of the surface water extent in France at a 10-m resolution using Sentinel-2 data
Xiucheng Yang,Xiucheng Yang,Qiming Qin,Qiming Qin,Herve Yesou,Thomas Ledauphin,Mathieu Koehl,Pierre Grussenmeyer,Zhe Zhu +8 more
TL;DR: In this article, the authors proposed a rule-based superpixel (RBSP) approach on the Google Earth Engine platform to generate the surface water extent at the national scale and 10m spatial scale.
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.