Using Image Processing Techniques to Identify and Quantify Spatiotemporal Carbon Cycle Extremes-Reference-Cited by-同舟云学术

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Using Image Processing Techniques to Identify and Quantify Spatiotemporal Carbon Cycle Extremes

Published:2022-11 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE International Conference on Data Mining Workshops (ICDMW)
language:
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Author:

Sharma Bharat¹^ORCID,Kumar Jitendra²^ORCID,Ganguly Auroop R.³^ORCID,Hoffman Forrest M.¹^ORCID

Affiliation:

1. Oak Ridge National Laboratory,Computational Earth Sciences Group,Oak Ridge,USA

2. Oak Ridge National Laboratory,Environmental Sciences Division,Oak Ridge

3. Northeastern University,Department of Civil and Environmental Engineering,Boston,USA

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10029378/10029381/10031163.pdf?arnumber=10031163

Reference23 articles.

1. A Global, 0.05-Degree Product of Solar-Induced Chlorophyll Fluorescence Derived from OCO-2, MODIS, and Reanalysis Data

2. Scaling carbon fluxes from eddy covariance sites to globe: synthesis and evaluation of the FLUXCOM approach

3. Evaluation of Cascading Infrastructure Failures and Optimal Recovery from a Network Science Perspective

4. Arbitrary-Order Conservative and Consistent Remapping and a Theory of Linear Maps: Part II

5. Arbitrary-Order Conservative and Consistent Remapping and a Theory of Linear Maps: Part I

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Carbon cycle extremes accelerate weakening of the land carbon sink in the late 21st century;Biogeosciences;2023-05-22

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