Data on global near-surface CO2 during 2015–2021 based on remote sensing and machine learning model

Published: 29 April 2025| Version 1 | DOI: 10.17632/yp8xvzjktn.1
Contributors:
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Description

Data for the manuscript entitled "Estimation, spatiotemporal variations, and impact factors of global near-surface CO2 during 2015–2021 based on remote sensing and machine learning model"

Files

Steps to reproduce

Build the dataset, develop the inversion model, validate the model, predict the near-surface CO2, and analyze the spatiotemperal variation patterns and influencing factors.

Institutions

  • Shandong University - Qingdao Campus
    Shandong, Qingdao

Categories

Remote Sensing, Carbon Dioxide, Greenhouse Gas

Funders

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