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ZENODO
Dataset . 2021
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2021
License: CC BY
Data sources: ZENODO
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Dynamic World Expert Consensus Validation Tiles

Authors: Christopher Forrest Brown; Steven P. Brumby; Brookie Guzder-Williams; Tanya Birch; Samantha Brooks Hyde; Joseph Mazzariello; Wanda Czerwinski; +10 Authors

Dynamic World Expert Consensus Validation Tiles

Abstract

From the Dynamic World dataset, DOI: PENDING DYNAMICWORLD DOI These data comprise the expert consensus set of GeoTIFF test tiles used for validating Dynamic World and other LULC maps. A metadata CSV is also included to enable cross-walking between these tiles and the Sentinel-2 L2A used to annotate the tile. The Dynamic World abstract: We developed a new automated approach for globally consistent, high resolution, near real-time (NRT) land use land cover (LULC) mapping leveraging deep learning on 10m Sentinel-2 imagery. When compared to other global LULC datasets, our data exceeded the next best global product agreement with an expert consensus test set by 7.5%. We utilize a highly scalable cloud based system for generating LULC maps and provide an open, continuous feed of LULC in parallel with Sentinel-2 acquisitions. This NRT product accommodates a variety of user needs ranging from extremely up-to-date LULC data to annual global maps. Furthermore, the continuous nature of the product's outputs enables refinement, extension, and even redefinition of the LULC classification. In combination, these unique attributes enable unprecedented flexibility for a diverse community of users across a variety of disciplines.

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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