Investigation and estimation on vegetation carbon storage and carbon density of subtropical evergreen broad-leaved forests in Jiangxi Province combined with remote sensing technology

Qiugen Zhang

doi:10.1117/12.2667251

10 February 2023 Investigation and estimation on vegetation carbon storage and carbon density of subtropical evergreen broad-leaved forests in Jiangxi Province combined with remote sensing technology

Qiugen Zhang

Author Affiliations +

Proceedings Volume 12552, International Conference on Geographic Information and Remote Sensing Technology (GIRST 2022); 1255213 (2023) https://doi.org/10.1117/12.2667251
Event: International Conference on Geographic Information and Remote Sensing Technology (GIRST 2022), 2022, Kunming, China

Abstract

The study of forest carbon storage and carbon density has become the focus of the study of forest carbon source (sink). Three typical subtropical evergreen broad-leaved forest in Jiangxi Province were taken as the research object, which included Cyclobalanopsis glauca forest, Schima superba forest, and Castanopsis eyrei forest. Combined the investigation method with remote sensing estimation, the related factors with carbon storage sample plot of Cyclobalanopsis glauca forest, Schima superba forest and Castanopsis eyrei forest had surveyed in Jiulian Mountain nature reserves, Wuyi Mountain nature reserves and Dagang Mountain nature reserves. In this paper, a remote sensing estimation model of vegetation index was established. The carbon storage and carbon density of subtropical evergreen broad-leaved forest in Jiangxi province had been estimated, and the sequential variation had been analyzed in latest 30 years. The result showed: in the subtropical evergreen broad-leaved forest vegetation layer, different organs had different carbon content; three kinds of subtropical evergreen broad-leaved forest carbon storage and density from high to low was Castanopsis eyrei forest, Schima superba forest, Cyclobalanopsis glauca forest. The vegetation biomass NDVI model was y=2.6977e^2.5523x. From 1985 to 2015, the carbon storage of vegetation had increased from 0.2401 GtC to 0.3664 GtC, the carbon density of vegetation had increased from 116.9 t/hm² to 133.65 t/hm².

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Qiugen Zhang "Investigation and estimation on vegetation carbon storage and carbon density of subtropical evergreen broad-leaved forests in Jiangxi Province combined with remote sensing technology", Proc. SPIE 12552, International Conference on Geographic Information and Remote Sensing Technology (GIRST 2022), 1255213 (10 February 2023); https://doi.org/10.1117/12.2667251

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KEYWORDS

Carbon

Vegetation

Biomass

Remote sensing

Biological research

Statistical analysis

Carbon monoxide

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