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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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Landscape-wide changes in land use and land cover correlate with, but rarely explain local biodiversity change

TL;DR: In this paper, the authors investigated whether landscape-wide changes in land use and land cover (LULC) are driving bird diversity change, defined as either trends in or abrupt changes in magnitude of photosynthetic activity.
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Monitoring Forest Infestation and Fire Disturbance in the Southern Appalachian Using a Time Series Analysis of Landsat Imagery

TL;DR: The results suggested that the overall performance of NDVI, followed by TCT wetness, was most accurate in detecting both the disturbance timing and hemlock decline intensity, explaining over 90% of the variability in the number of dead hemlocks.
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Mapping Croplands in the Granary of the Tibetan Plateau Using All Available Landsat Imagery, A Phenology-Based Approach, and Google Earth Engine

TL;DR: Zhang et al. as mentioned in this paper developed two pixel and phenology-based algorithms to map croplands using Landsat imagery and the Google Earth Engine platform along the Brahmaputra River and its two tributaries (BRTT) in the Tibet Autonomous Region, also known as the granary of TP, in 2015-2019.
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Comparison of multi-temporal planetscope data with Landsat 8 and Sentinel-2 data for estimating airborne LiDAR derived canopy height in temperate forests

TL;DR: This study evaluates the capabilities of PlanetScope CubeSat data to estimate canopy height derived from airborne Light Detection and Ranging (LiDAR) by comparing estimates using Sentinel-2 and Landsat 8 data and shows that RF models using multi-seasonal composites are 1.4% more accurate than those using harmonic metrics from time-series data in the median.
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Are Northern Lakes in Relatively Intact Temperate Forests Showing Signs of Increasing Phytoplankton Biomass

TL;DR: In this article, a regression model was developed to characterize spatial and temporal variation in chlorophyll-a (Chl-a) as a proxy of phytoplankton biomass in lakes located in the relatively intact northern temperate forest in the Great Lakes-St Lawrence forest region.
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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