Remote Sensing Estimates of Particulate Organic Carbon Sources in the Zhanjiang Bay Using Sentinel-2 Data and Carbon Isotopes

Author:

Yu Guo123ORCID,Zhong Yafeng23,Liu Sihai13,Lao Qibin13,Chen Chunqing13,Fu Dongyang2,Chen Fajin134

Affiliation:

1. College of Ocean and Meteorology, Guangdong Ocean University, Zhanjiang 524088, China

2. College of Electronic and Information Engineering, Guangdong Ocean University, Zhanjiang 524088, China

3. College of Chemistry and Environmental Science, Guangdong Ocean University, Zhanjiang 524088, China

4. Key Laboratory of Climate, Resources and Environment in Continental Shelf Sea and Deep Sea of Department of Education of Guangdong Province, Guangdong Ocean University, Zhanjiang 524088, China

Abstract

The source information of coastal particulate organic carbon (POC) with high spatial and temporal resolution is of great significance for the study of marine carbon cycles and marine biogeochemical processes. Over the past decade, satellite ocean color remote sensing has greatly improved our understanding of the spatiotemporal dynamics of ocean particulate organic carbon concentrations. However, due to the complexity of coastal POC sources, remote sensing methods for coastal POC sources have not yet been established. With an attempt to fill the gap, this study developed an algorithm for retrieving coastal POC sources using remote sensing and geochemical isotope technology. The isotope end-member mixing model was used to calculate the proportion of POC sources, and the response relationship between POC source information and in situ remote sensing reflectance (Rrs) was established to develop a retrieval algorithm for POC sources with the following four bands: (Rrs(443)/Rrs(492)) × (Rrs(704)/Rrs(665)). The results showed that the four-band algorithm performed well with R2, mean absolute percentage error (MAPE) and root mean square error (RMSE) values of 0.78, 33.57% and 13.74%, respectively. Validation against in situ data showed that the four-band algorithm derived calculated the proportion of marine POC accurately, with an MAPE and RMSE of 27.49% and 13.58%, respectively. The accuracy of the algorithm was verified based on the Sentinel-2 data, with an MAPE and RMSE of 28.02% and 15.72%, respectively. Additionally, we found that the proportion of marine POC sources was higher outside the Zhanjiang Bay than inside it using in situ survey data, which was consistent with the retrieved results. Influencing factors of POC sources may be due to the occurrence of phytoplankton blooms outside the bay and the impact of terrestrial inputs inside the bay. Remote sensing in combination with carbon isotopes provides important technical assistance in comprehending the biogeochemical process of POC and uncovering spatiotemporal variations in POC sources and their underlying causes.

Funder

National Natural Science Foundation of China

Innovation and Entrepreneurship Project of Shantou

Publisher

MDPI AG

Subject

General Earth and Planetary Sciences

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