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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Generating High-Quality and High-Resolution Seamless Satellite Imagery for Large-Scale Urban Regions
TL;DR: This study proposes a robust and efficient procedure for generating high-resolution and high-quality seamless satellite imagery for large-scale urban regions and proposes a spatially adaptive method considering the variation of atmospheric scattering and a stepwise replacement method based on local moment matching for removing thin and thick clouds.
Journal ArticleDOI
Comparative Analysis of Edge Information and Polarization on SAR-to-Optical Translation Based on Conditional Generative Adversarial Networks
TL;DR: In this paper, the authors explored the quantitative impact of edge information and polarization on the peak signal-to-noise ratio, structural similarity index measure, correlation coefficient (r), and root mean squared error.
Journal ArticleDOI
Object-based classification of cloudy coastal areas using medium-resolution optical and SAR images for vulnerability assessment of marine disaster
TL;DR: In this article, the authors proposed a framework of combining medium-resolution optical images and synthetic aperture radar (SAR) data with the recently popular object-based image analysis (OBIA) method and used the Landsat Operational Land Imager and Phased Array type L-band Synthetic Aperture Radar (PALSAR) images acquired in Singapore in 2017 as a case study.
Journal ArticleDOI
How up-scaling of remote-sensing images affects land-cover classification by comparison with multiscale satellite images
TL;DR: The results indicate that the effects of resolution cannot be ignored and that resampling data may not be adequate for multi-spatial-scale classification compared with the native satellite images, and it is thus urgent to obtain an effective up-scaling algorithm that sharply reduces the problems caused by spatial heterogeneity.
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Rubber Identification Based on Blended High Spatio-Temporal Resolution Optical Remote Sensing Data: A Case Study in Xishuangbanna
TL;DR: The analysis of the proposed rubber plantation identification method shows that fused optical remote sensing data with high spatio-temporal resolution could map the rubber distribution with high accuracy, and the method is a promising approach for rubber plantation mapping and the detection of changes in rubber plantations in this tropical area.
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.
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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.