Results 11 to 20 of about 17,569,314 (273)
SPECTRAL UNMIXING ANALYSIS OF TIME SERIES LANDSAT 8 IMAGES [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2018 Temporal analysis of Landsat 8 images opens up new opportunities in the unmixing procedure. Although spectral analysis of time series Landsat imagery has its own advantage, it has rarely been studied.
R. Zhuo, L. Xu, J. Peng, Y. Chen
doaj +5 more sources
Robust Landsat-based crop time series modelling
Remote Sensing of Environment, 2020 Abstract Reliable satellite monitoring of agriculture is often difficult because surface variations occur rapidly compared to the cloud-free satellite observation frequency. Harmonic time series models, i.e., superimposed sequences of sines and cosines, have an established provenance for fitting satellite vegetation index time series to coarse ...
David Roy
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Landsat Time Series Reconstruction Using a Closed-Form Continuous Neural Network in the Canadian Prairies Region [PDF]
SensorsThe Landsat archive stands as one of the most critical datasets for studying landscape change, offering over 50 years of imagery. This invaluable historical record facilitates the monitoring of land cover and land use changes, helping to detect trends in
Masoud Babadi Ataabadi +3 more
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Characterizing Forest Change Using Community-Based Monitoring Data and Landsat Time Series. [PDF]
PLoS ONE, 2016 Increasing awareness of the issue of deforestation and degradation in the tropics has resulted in efforts to monitor forest resources in tropical countries.
Ben DeVries +4 more
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A Framework of Spatio-Temporal Fusion Algorithm Selection for Landsat NDVI Time Series Construction
ISPRS International Journal of Geo-Information, 2020 Spatio-temporal fusion algorithms dramatically enhance the application of the Landsat time series. However, each spatio-temporal fusion algorithm has its pros and cons of heterogeneous land cover performance, the minimal number of input image pairs, and ...
Yangnan Guo +4 more
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Continuous monitoring of land disturbance based on Landsat time series
Remote Sensing of Environment, 2020 Abstract We developed a new algorithm for COntinuous monitoring of Land Disturbance (COLD) using Landsat time series. COLD can detect many kinds of land disturbance continuously as new images are collected and provide historical land disturbance maps retrospectively.
Zhiqiang Yang, Shi Qiu, Zhe Zhu
exaly +3 more sources
A LANDSAT TIME-SERIES STACKS MODEL FOR DETECTION OF CROPLAND CHANGE [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2017 Global, timely, accurate and cost-effective cropland monitoring with a fine spatial resolution will dramatically improve our understanding of the effects of agriculture on greenhouse gases emissions, food safety, and human health.
J. Chen, J. Chen, J. Chen, J. Zhang
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Spatiotemporal Transformer Network for Reconstructing Historical Landsat Time Series
Reconstructing dense and temporally continuous Landsat time series remains challenging due to low temporal revisit, sparse and irregular clear-sky observations due to clouds and shadows, and sensor-specific artifacts such as the Landsat 7 Scan Line Corrector (SLC) failure.
Masoud Babadi Ataabadi +3 more
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Interpolation and Gap Filling of Landsat Reflectance Time Series [PDF]
IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018 Products derived from a single multispectral sensor are hampered by a limited spatial, spectral or temporal resolutions. Image fusion in general and downscaling/blending in particular allow to combine different multiresolution datasets. We present here an optimal interpolation approach to generate smoothed and gap-free time series of Landsat ...
Álvaro Moreno-Martínez +6 more
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Science of Remote Sensing, 2021 An increase in the temporal revisit of satellite data is often sought to increase the likelihood of obtaining cloud- and shadow-free observations as well as to improve mapping of rapidly- or seasonally-changing features. Currently, as a tandem, Landsat-7
Michael A. Wulder +4 more
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