Remote sensing monitoring of aboveground carbon storage of Pinus massoniana forests in a typical red soil erosion area in Southern China: Hetian, Changting County of Fujian Province

The dynamic changes of forest carbon storage have important indications for revealing the effectiveness of regional soil erosion control. Take Hetian Town, Changting County as an example. In 2017, 34 Masson pine（Pinus massoniana） forests samples were randomly set as the modeling set, and the original waveband, vegetation index and principal component factor regression analysis of the Landsat images of the same period were used to construct the best inversion model for the aboveground forest carbon storage of Masson pine forests. The best inversion model, the linear normalization method based on the principle of pseudo invariant feature（PIF）, realizes the applicability correction conversion of the model on the images of 2003 and 2010, and realizes the inversion of the carbon storage of the Masson pine forests in the study area in 2003, 2010 and 2017. Research on spatio-temporal differentiation characteristics. The results show that the best remote sensing inversion model for the aboveground forest carbon storage of Masson pine forests in the study area in 2017 is an index model constructed with the Green Normalized Vegetation Index（GNDVI） as the independent variable: C2017=0.006 e14.357 GNDVI2017,the fitting coefficient of determination of this model is 0.57, and the average relative accuracy is 82.19%; In 2003 and 2010, the remote sensing estimation models of the aboveground forest carbon storage of Masson pine forests are: C2003=0.006 e((16.4086 GNDVI2003+1.1428)),C2010=0.006 e((15.1677 GNDVI2010+1.5821)), The coefficient of determination of the two-period calibration model is above 0.85; Carbon storage in 2003, 2010 and 2017 were 8.24 t/hm2, 11.34 t/hm2 and 16.14 t/hm2, respectively, showing an overall upward trend; the aboveground forest carbon storage increases with the elevation and slope, and the aboveground forest carbon storage on the sunny slope is higher than that on the shady slope; The growth rate of carbon storage decreases with the increase of altitude and slope, and the growth rate of carbon storage on the shady slope is higher than that on the sunny slope.