Dynamic monitoring of forest carbon stocks based on the InVEST model.

Abstract

Forest carbon storage is almost estimated by the ground survey data, there is a difficulty of huge statistical work and modeling complexity. To calculate forest carbon stocks in a quick and accurate way, which has been the current research focus in forestry both inside and outside of China. A new method is proposed by combining a little input parameters of the InVEST model with a large monitoring scale of remote sensing data. First, InVEST model was used to estimate regional carbon stocks according to forest type carbon data and according to raster data. Then this data was compared to the multistage carbon data from remote sensing data to achieve a dynamic monitoring of forest carbon stocks. This paper estimated and mapped carbon stock of the Qingyuan (a county) in 2009, according to the administrative division map can estimate the carbon storage of the scale of town and village. After estimated carbon reserves of Kengxi (a village) in 2009 and 2014, carbon difference method was adopted to dynamic monitoring of carbon sink. Results showed that the carbon sink estimated with the new method for Qiyuan(a county), Zhejiang, China was 3.274 3×107 Mg in 2009. Also, the carbon stock for Kengxi (a village) increased 1.780 3×104 Mg from 2009 to 2014. Compared to forest average carbon density, adding forest species average carbon storage and carbon sinks to forest carbon stock monitoring improved estimation precision of forest carbon stocks. This dynamic multi-dimensional method for monitoring forest carbon sinks being simple, convenient, user-friendly, and advantageous because it used less data input and visual output in the model, could be used in the county, township (town) and village forest carbon monitoring. [Ch, 5 fig. 4 tab. 32 ref.]