Share Email Print
cover

Proceedings Paper

Data fusion of CO2 retrieved from GOSAT and AIRS using regression analysis and fixed rank kriging
Author(s): Cong Zhou; Runhe Shi; Wei Gao
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

This paper proposes an improved statistical method for fusing carbon dioxide (CO2) data retrieved from two major instruments, the Greenhouse gases Observing SATellite (GOSAT) and the Atmospheric Infrared Sounder (AIRS). These two datasets were fused to obtain CO2 concentrations near the surface, which is a region that is especially important for studies on carbon sources and sinks. Overall, the CO2 monthly average values from GOSAT are all lower than those from AIRS from 2010 to 2012. The datasets show the similar seasonal cycles of carbon dioxide and show an increasing trend with a determination coefficient of 0.45. A strong correlation was determined by adding the climatic factors as independent variables for regression analysis. The correlation coefficients between the CO2 values from AIRS and GOSAT significantly increased in response. The true CO2 data processes were then predicted using the fixed rank kriging method. This showed that the data-fusion CO2 product provides more reasonable information and that the corresponding mean squared prediction errors are smaller than those from the single GOSAT CO2 dataset.

Paper Details

Date Published: 4 September 2015
PDF: 9 pages
Proc. SPIE 9610, Remote Sensing and Modeling of Ecosystems for Sustainability XII, 96101A (4 September 2015); doi: 10.1117/12.2187493
Show Author Affiliations
Cong Zhou, East China Normal Univ. (China)
Institute of Remote Sensing and Digital Earth (China)
Colorado State Univ. (United States)
Runhe Shi, East China Normal Univ. (China)
Institute of Remote Sensing and Digital Earth (China)
Colorado State Univ. (United States)
Wei Gao, East China Normal Univ. (China)
Institute of Remote Sensing and Digital Earth (China)
Colorado State Univ. (United States)


Published in SPIE Proceedings Vol. 9610:
Remote Sensing and Modeling of Ecosystems for Sustainability XII
Wei Gao; Ni-Bin Chang; Jinnian Wang, Editor(s)

© SPIE. Terms of Use
Back to Top