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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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Fine Land-Cover Mapping in China Using Landsat Datacube and an Operational SPECLib-Based Approach

TL;DR: The case study in China indicates that the proposed SPECLib method is an operational and accurate method for regional/global fine land-cover mapping at a spatial resolution of 30 m.
Journal ArticleDOI

Making Landsat Time Series Consistent: Evaluating and Improving Landsat Analysis Ready Data

TL;DR: This study evaluated the temporal consistency of this new dataset and recommended several processing streamlines for improving data consistency, including single-resampled data (ARD), and recommended using Landsat ARD with the improved cloud and cloud shadow detection approach, and with BRDF correction for routine time series analysis.
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An ESTARFM Fusion Framework for the Generation of Large-Scale Time Series in Cloud-Prone and Heterogeneous Landscapes

TL;DR: The results show that the ESTARFM framework can accurately produce high temporal resolution time series while keeping the spatial detail in such a heterogeneous, cloud-prone region and establish the basis for large-scale research on various geoscientific questions related to land degradation, changes in land surface phenology or agriculture.
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Enhancing the Detectability of Clouds and Their Shadows in Multitemporal Dryland Landsat Imagery: Extending Fmask

TL;DR: A new two-step approach for automated masking of clouds and their shadows in Landsat imagery, specifically designed for use in water-limited dryland areas, where event-based precipitation is predominant.
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Methods for Mapping Forest Disturbance and Degradation from Optical Earth Observation Data: a Review

TL;DR: A review of the current state of the art in remote sensing-based monitoring of forest disturbances and forest degradation from optical Earth Observation data revealed that a wide variety of methods for the detection of forest degradation is already available.
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.
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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.
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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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