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Spatial Distribution Characteristics of Biomass and Carbon Storage in Forest Vegetation in Chongqing Based on RS and GIS


Affiliations
1 Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu, Sichuan, 610041, China
2 Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
 

Research on the spatial distribution characteristics of carbon storage in forest vegetation not only facilitates the study of carbon sink and ecological compensation of the forest ecosystem, but also provides basic data for recovering and reconstructing the forest ecosystem and increasing the carbon sink. In this study, remote sensing images of Landsat TM (August) in 2011 and a large amount of actual surveyed data of the sample plots were used as the main and supplementary data sources, respectively. Chongqing was selected as the study site to quantitatively estimate the biomass, carbon storage, and carbon density of forest vegetation based on the biomass-remote sensing (RS) geoscientific data regression model with the aid of RS and GIS techniques. With the spatial analysis function of ArcGIS, factors affecting the geographic distribution of biomass were investigated from a macroscopic perspective, and the geographical distribution pattern characteristics of biomass in the study area were quantitatively discussed. Results showed that the total aboveground biomass of Chongqing is 2.83×108 t, and that of the forest ecosystem is 1.39×108 t. Biomass was mainly distributed in northeast and southeast Chongqing, and the overall distribution pattern was high in the east and low in the west. Forest vegetation and biomass were mainly distributed in mid-high altitudes with steep slopes. Despite the results of this biomass and carbon storage study using RS in Chongqing, further research based on the carbon cycle is needed.

Keywords

Biomass, Forest vegetation, Carbon storage, Vegetation index.
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  • Spatial Distribution Characteristics of Biomass and Carbon Storage in Forest Vegetation in Chongqing Based on RS and GIS

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Authors

Qiannan Liu
Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu, Sichuan, 610041, China
Zhiyun Ouyang
Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
Ainong Li
Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu, Sichuan, 610041, China
Weihua Xu
Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China

Abstract


Research on the spatial distribution characteristics of carbon storage in forest vegetation not only facilitates the study of carbon sink and ecological compensation of the forest ecosystem, but also provides basic data for recovering and reconstructing the forest ecosystem and increasing the carbon sink. In this study, remote sensing images of Landsat TM (August) in 2011 and a large amount of actual surveyed data of the sample plots were used as the main and supplementary data sources, respectively. Chongqing was selected as the study site to quantitatively estimate the biomass, carbon storage, and carbon density of forest vegetation based on the biomass-remote sensing (RS) geoscientific data regression model with the aid of RS and GIS techniques. With the spatial analysis function of ArcGIS, factors affecting the geographic distribution of biomass were investigated from a macroscopic perspective, and the geographical distribution pattern characteristics of biomass in the study area were quantitatively discussed. Results showed that the total aboveground biomass of Chongqing is 2.83×108 t, and that of the forest ecosystem is 1.39×108 t. Biomass was mainly distributed in northeast and southeast Chongqing, and the overall distribution pattern was high in the east and low in the west. Forest vegetation and biomass were mainly distributed in mid-high altitudes with steep slopes. Despite the results of this biomass and carbon storage study using RS in Chongqing, further research based on the carbon cycle is needed.

Keywords


Biomass, Forest vegetation, Carbon storage, Vegetation index.

References