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Journal ArticleDOI

Object-based cloud and cloud shadow detection in Landsat imagery

Zhe Zhu, +1 more
- 15 Mar 2012 - 
- Vol. 118, pp 83-94
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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.

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Citations
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Journal ArticleDOI

Automated cloud, cloud shadow, and snow detection in multitemporal Landsat data: An algorithm designed specifically for monitoring land cover change

TL;DR: The goal is development of a cloud, cloud shadow, and snow detection algorithm that results in a multitemporal stack of images that is free of “noise” factors and thus suitable for detection of land cover change.
Journal ArticleDOI

Continuous monitoring of forest disturbance using all available Landsat imagery

TL;DR: In this article, a change detection algorithm for continuous monitoring of forest disturbance at high temporal frequency is developed using all available Landsat 7 images in two years, time series models consisting of sines and cosines are estimated for each pixel for each spectral band.
Journal ArticleDOI

Comparing Landsat water index methods for automated water classification in eastern Australia

TL;DR: In this paper, the authors compared the accuracy of seven water index methods for classifying water in 30m resolution Landsat TM/ETM+/OLI imagery from eastern Australia.
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The Global Mangrove Watch—A New 2010 Global Baseline of Mangrove Extent

TL;DR: This study presents a new global baseline of mangrove extent for 2010 and has been released as the first output of the Global Mangrove Watch (GMW) initiative, the first study to apply a globally consistent and automated method for mapping mangroves.
Journal ArticleDOI

Water observations from space: Mapping surface water from 25 years of Landsat imagery across Australia

TL;DR: A water detection algorithm was used based on a decision tree classifier, and a comparison methodology using a logistic regression was used to map the presence of surface water across the entire continent from every observation of 27 years of satellite imagery as mentioned in this paper.
References
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Book

Morphological Image Analysis: Principles and Applications

Pierre Soille
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

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

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.

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.
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