Assessing Forest Distribution And Carbon Storage Changes In Jiangning District,Nanjing(2017-2020)

Forests are the largest carbon pool in terrestrial ecosystems.Timely acquisition of forest spatial distribution and carbon storage changes plays an important guiding role in planning and utilizing forest resources.In order to actively respond to the"double carbon"policy and quantify the carbon sink potential of forests,this study took Jiangning District,Nanjing City,Jiangsu Province as the research area.Firstly,the Gao Fen-1(GF-1)remote sensing satellite imagery covering Jiangning district was preprocessed and subsequently fused by using the Brovey,Gram-Schmidt(GS),Nearest Neighbor Diffusion(NND)and Wavelet transform methods,followed by a comprehensive(qualitative and quantitative)evaluation of the fusion effects of different fusion methods to determine the best fusion method.Then,the random forest(RF),support vector machine(SVM)and deep learning methods(the ordinary Mask-RCNN model and modified Mask-RCNN model combined with Swin Transformer)were applied to classify and extract different vegetation types in the study based on remote sensing spectral features,texture information,terrain feature and vegetation index,etc.And the classification results were validated by using 1000 random points to identify the optimal classification model and the best classification results of the forest distribution over the study area in 2020.On this basis,the change detection analysis was implemented to obtain the forest distribution changes in Jiangning District during the period 2017-2020.Combined with the data of forest resources planning inventory conducted in 2017 and related literatures,three carbon pools including the living standing wood,litter and debris and forest soil were identified according to the actual situation of Jiangning’s forest.Referring to the specific parameters of different tree species,the biomass conversion factor method was used to calculate the forest live standing wood carbon storage,on this basis,the litter and debris carbon storage and soil carbon storage were derived from the ratios compiled from diverse literatures.Based on the results of forest distribution changes from 2017to 2020,the carbon storage calculation in 2020 was divided into three parts,including the persisting forest area,forest gain area and forest loss area.And the calculation for persisting forest was conducted by using the optimal allometric carbon density growth equations,which were fitted in terms of coniferous forest type and broad-leaved forest type based on the regression-corrected inventory data of forest stands in a manner of space for time.And for the carbon storage calculation of forest gain area,the allometric equations were used in accordance with young forest group by specifying an average growth age of 2 years.And for the carbon storage calculation of forest loss area,the biomass conversion factor method was used in accordance with detailed parameter.Finally,the changes of forest ecosystem carbon storage in Jiangning District of Nanjing during the three years were derived,followed by a recommendation of the targeted development suggestions to provide reference for future development of forest carbon sequestration.The results showed that:(1)The standard deviation,correlation coefficient,average gradient and information entropy of the GS-fused GF-1 image were the largest among the four fusion algorithms,and the fused image had clear boundaries with rich color textures.Thus,the fusion effect of the GS fusion algorithm was the best;(2)The overall accuracy and kappa coefficient of forest extractions derived from SVM,RF,Mask-RCNN and Swin Transformer-integrated Mask-RCNN models were at 85.8%,0.787,87.8%,0.817,90.1%,0.851,93.9%and 0.908,respectively.The improved Swin Transformer-integrated Mask-RCNN model was the best one to extract the distribution of forest types in Jiangning District in 2020,which could provide a technical reference for forest type identification and monitoring.From 2017 to 2020,the forest gain area in Jiangning District was 637.164 hm~2,and the forest loss area was 289.654 hm~2,which resulted from change detection analysis of bi-temporal forest distribution maps;(3)In 2017,the carbon storage of forest ecosystems in Jiangning District of Nanjing calculated from the biomass conversion factor method coupled with empirical ratio coefficients method totaled 2,768,300 tons,including 1,264,900 tons of living standing wood carbon pool,1,458,400 tons of understory soil carbon pool,and 45,000 tons of litter and debris carbon pool;(4)The fitting results of Logistic,Richards and Gompertz carbon density growth models(carbon density against stand age by coniferous and broad-leaved forests in Jiangning District)were compared,among which the Logistic model had the best fitting effect and reliable cross-validation results,with the fitting R~2of coniferous forest and broad-leaved forest at 0.84344 and 0.88378,respectively.In 2020,the carbon storage of forest living standing wood in Jiangning District was about 1.4494 million tons,and the carbon storage of forest ecosystem totaled 3.1722 million tons,and the carbon storage increased by 14.59%compared to that of 2017.Based on the findings of the study,the targeted suggestions on forest management in Jiangning District are proposed from the following four aspects:improving forest carbon sequestration capacity,consolidating the application of forest carbon sequestration auditing results,strengthening the construction of forestry carbon storage measurement and monitoring system,and promoting the coordinated development of forest and grass ecosystems and urban forest carbon sequestration,to provide references for forest resource protection and development,attribution of forest dynamic changes,management and spatial allocation of forest resources.