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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High-resolution mapping of global surface water and its long-term changes
TL;DR: Using three million Landsat satellite images, this globally consistent, validated data set shows that impacts of climate change and climate oscillations on surface water occurrence can be measured and that evidence can be gathered to show how surface water is altered by human activities.
Journal ArticleDOI
Improvement and expansion of the Fmask algorithm: cloud, cloud shadow, and snow detection for Landsats 4–7, 8, and Sentinel 2 images
TL;DR: In this article, a new cirrus band was introduced for detecting clouds, especially for thin cirrus clouds, and a new version of the Fmask algorithm was developed for use with Landsat 8 images.
Journal ArticleDOI
Continuous change detection and classification of land cover using all available Landsat data
Zhe Zhu,Curtis E. Woodcock +1 more
TL;DR: In this article, a two-step cloud, cloud shadow, and snow masking algorithm is used for eliminating noisy observations and a time series model that has components of seasonality, trend, and break estimates surface reflectance and brightness temperature.
Journal ArticleDOI
Optical remotely sensed time series data for land cover classification: A review
TL;DR: In this article, the authors present the issues and opportunities associated with generating and validating time-series informed annual, large-area, land cover products, and identify methods suited to incorporating time series information and other novel inputs for land cover characterization.
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Cloud detection algorithm comparison and validation for operational Landsat data products
Steve Foga,Pat L. Scaramuzza,Song Guo,Zhe Zhu,Zhe Zhu,Ronald D. Dilley,Tim Beckmann,Gail L. Schmidt,John L. Dwyer,M. Joseph Hughes,Brady Laue +10 more
TL;DR: A workflow to evaluate cloud and cloud shadow masking algorithms using cloud validation masks manually derived from both Landsat 7 Enhanced Thematic Mapper Plus and Landsat 8 OLI/TIRS data is created, finding that CFMask, C code based on the Function of Mask (Fmask) algorithm, and its confidence bands have the best overall accuracy among the many algorithms tested using validation data.
References
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Cloud detection in Landsat imagery of ice sheets using shadow matching technique and automatic normalized difference snow index threshold value decision
TL;DR: This work presents a new algorithm designed to detect clouds in satellite visible and infrared (IR) imagery of ice sheets through the use of the normalized difference snow index (NDSI).
Journal Article
Automated Detection and Removal of Clouds and Their Shadows from Landsat TM Images
TL;DR: The scheme uses the image fusion technique to automatically recognize and remove contamination of clouds and their shadows, and integrate complementary information into the composite image from multitemporal images.
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Use of Markov Random Fields for automatic cloud/shadow detection on high resolution optical images
TL;DR: An automatic detection algorithm for cloud/shadow on remote sensing optical images based on physical properties of clouds and shadows, namely for a cloud and its associated shadow, which is formalized using Markov Random Field (MRF) framework at two levels.
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Corection of thin cirrus path radiances in the 0.4–1.0 μm spectral region using the sensitive 1.375 μm cirrus detecting channel
TL;DR: In this article, an empirical algorithm for removing thin cirrus effects from AVIRIS (airborne visible infrared imaging spectrometer) images at any wavelength in the region 0.4-1 μm using narrow channels near 1.38, 1.24, and 0.66 μm.
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Implementation on Landsat Data of a Simple Cloud-Mask Algorithm Developed for MODIS Land Bands
TL;DR: This letter assesses the performance on Landsat-7 images of a modified version of a cloud-masking algorithm originally developed for clear-sky compositing of Moderate Resolution Imaging Spectroradiometer images at northern midlatitudes and shows that the proposed algorithm performs on par with the ACCA both in terms of scene cloud fraction and pixel-level mask agreement.