IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (Jan 2024)

MSAVI-Enhanced CASA Model for Estimating the Carbon Sink in Coastal Wetland Area: A Case Study of Shandong Province

  • Huaqiao Xing,
  • Yuqing Zhang,
  • Linye Zhu,
  • Na Xu,
  • Xin Lan

DOI
https://doi.org/10.1109/JSTARS.2024.3485642
Journal volume & issue
Vol. 17
pp. 19698 – 19712

Abstract

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Coastal wetland ecosystem is vital for carbon sequestration, making the accurate carbon sink estimation essential for its protection and management. Traditional carbon sink estimation methods have overlooked the influence of moist soil on sparse vegetation, resulting in the inaccurate estimation of net primary productivity (NPP), especially in coastal areas with mixed wetlands and vegetation. To address this challenge, this study proposed an improved Carnegie–Ames–Stanford approach model for NPP estimation, which utilizes the modified soil-adjusted vegetation index (MSAVI) to eliminate the background noise of moist soils and calculate the fraction of photosynthetically active radiation. By using MOD17A3 as reference data for comparative experiment, the accuracy of NPP results is improved by 89.6 gC·m−2. The proposed model was then used for carbon sink estimation and analysis of Shandong coastal area. The results indicate the following: First, the average NPPMSAVI across Shandong coastal area was improved by 99.12 gC·m−2, 36.17%, and 60.53 gC·m−2 in BIAS, relative bias, and root-mean-square error, respectively. Second, the spatial distribution of net ecosystem productivity (NEP) in Shandong coastal area is higher in the east and lower in the west, with mean values of approximately 210 gC·m−2 in the east and 60 gC·m−2 in the west. The seasonal differences in NEP among different land types are significant. Third, NEP exhibits a strong correlation with temperature, precipitation, and solar radiation, with mean r of 0.78, 0.8, and 0.84, respectively.

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