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Correlation Analysis of CO2 Concentration Based on DMSP-OLS and NPP-VIIRS Integrated Data
- Source :
- Remote Sensing, Vol 14, Iss 17, p 4181 (2022)
- Publication Year :
- 2022
- Publisher :
- MDPI AG, 2022.
-
Abstract
- In view of global warming, caused by the increase in the concentration of greenhouse gases, China has proposed a series of carbon emission reduction policies. It is necessary to obtain the spatiotemporal distribution of carbon emissions accurately. Nighttime light data is recognized as an important basis for carbon emission estimation. A large number of research results show that there is a positive correlation between nighttime light intensity and carbon emission. However, in the current context of China’s industrial reforms, this positive relationship may not be entirely correct. First, we correct the nighttime light data from different satellites and established a long-term series data set. Then, we verify the positive correlation between nighttime light and carbon emission. However, the time scale of emission data often lags, and the carbon concentration data are released earlier and are more accurate than emission data. Therefore, we propose to investigate the relationship between nighttime light and carbon concentration. It is found that there may be different correlations between nighttime light and the carbon concentration, due to different urban industrial structure and development planning. Therefore, by exploring the relationship between nighttime light and the carbon concentration, the existing carbon emission estimation model can be modified to improve the accuracy of the emission model.
- Subjects :
- DMSP-OLS
NPP-VIIRS
CO2 emissions
CO2 concentration
Science
Subjects
Details
- Language :
- English
- ISSN :
- 20724292
- Volume :
- 14
- Issue :
- 17
- Database :
- Directory of Open Access Journals
- Journal :
- Remote Sensing
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.28ded24b5bde4c59991cc4ec09056842
- Document Type :
- article
- Full Text :
- https://doi.org/10.3390/rs14174181