Spatial And Temporal Dynamics Of Forest Carbon Density In Yueyang City

As one of the world’s largest terrestrial ecosystems,forests significantly influence carbon cycling processes.With the impact of climate change and human activities,the spatial and temporal variation of forest carbon density has become a hot issue for research in recent years.This paper uses forest science,remote sensing technology,and geographic information science as a guide to study the high forest in Yueyang City,Hunan Province.The inversion model of forest carbon density for different dominant tree species and species groups in Yueyang City was constructed to accurately estimate the forest carbon density in Yueyang City from 2013 to 2022 and to investigate the spatial and temporal changes in forest carbon density in Yueyang City.The main research components and findings are as follows:(1)The remote sensing classification method of dominant tree species and tree species groups in Yueyang City was analyzed and preferred.Based on Landsat-8 imagery data,Support Vector Machine(SVM)and Random Forest(RF)classifiers were used to classify the dominant tree species and tree species groups in Yueyang City.The results show that the overall validation accuracies of the SVM and RF classifiers are 66.74%and 87.30%,respectively;the Kappa coefficients are 0.6006 and 0.7747,respectively,and the automatic classification effect of the RF classifier is better than that of the SVM classifier.(2)An inverse model of forest carbon density in Yueyang City was constructed.To address the problem of large differences in parameter values of forest carbon density models for different tree species in the remote sensing inversion of forest carbon density,the average forest carbon density of small groups was calculated using the IPCC woody biomass method as the dependent variable,and remote sensing factors such as spectral information and texture features of the forest were extracted using Landsat 8 OLI data and combined with topographic factors as the independent variables to construct forest carbon density inversion models for different dominant tree species and tree species groups using MLR,SVM and RF.The results show that the R2 of the RF model was significantly higher than that of the MLR and SVM models,the,RMSE and MAE were significantly lower than those of the MLR and SVM models,with higher inversion accuracy,and the values of the spatial distribution of forest carbon density ranged from 3.06 to 62.80 t·hm-2.Compared with the spatial distribution values of forest carbon density without dominant tree species classification(4.64-31.96 t·hm-2),the inverse model constructed in this study eliminated the problems of severe overfitting and underestimation of peak value when forest carbon density estimation was performed under unclassified conditions.(3)The spatial and temporal dynamics of forest carbon density in Yueyang City were studied.The forest carbon density of Yueyang City from 2013 to 2022 was estimated using the forest carbon density inversion model constructed in this paper.Then the forest carbon density was classified into five classes:stable,slightly increasing,significantly increasing,slightly decreasing,and significantly decreasing,based on the change in forest carbon density before and after the two periods.The estimated results were analyzed in terms of spatial and temporal changes.The results show that,on the time scale,the forest carbon density of Yueyang City in the ten years from 2013 to 2022 has a higher proportion of "slight decrease" and "significant decrease" in 2013-2018 compared with 2018-2022.However,the area of "basically stable" carbon density accounted for 63.10%,and the overall carbon density remained stable;the forest carbon density of Yueyang City showed an increasing trend from 2018 to 2022,and the growing trend was pronounced in 2022,with the average forest carbon density reaching 18.81 t·hm-2.On a spatial scale,the average forest carbon density in the northeast,northwest,and southwest regions showed a decreasing trend from 2013 to 2018,while Yueyang County,Pingjiang County,and Yunxi District in the central and southern areas showed an increasing trend.The average forest carbon density in the central region showed a decreasing trend from 2018 to 2022,while all other areas showed a growing trend.