Biomass Spatio-temporal Changes And Carbon Sequestration Potential Of Urban Green Space

Green space is the ecological base and natural barrier of cities.Understanding the dynamic changes as well as quantifying the biomass and carbon sequestration potential of urban green space is essential for its optimal management.Taking the urban area of Xuzhou City as an example,information derived from 2016-2021Sentinel series（Sentinel-1/2）satellite images,SRTM data,and field ground survey data were applied to achieve urban green space type mapping based on image objects.Multiple linear regression and stepwise regression biomass models for different types of urban green space were constructed and tested.Using the preferred models and integrating the remote sensing inversion results of all types of green space biomass,information on the distribution and changes of urban green space biomass in Xuzhou was obtained.The carbon storage and sequestration potential of green space were thus further explored.The main research results and conclusions are as follows:（1）The distribution and structural composition of urban green space were clarified.Using the spectral and texture features as the basis,the multi-scale segmentation of multi-source remote sensing images,classification network construction,and classifier training tests were implemented in turn to subdivide Xuzhou urban green space into broadleaf forest,coniferous forest,and shrub-grass vegetation,with an overall classification accuracy of 86.59%and Kappa coefficient of0.78.The urban green space in Xuzhou was more numerous in the north than in the south,and the total area showed a fluctuating decreasing trend over time.In the urban area,shrub-grass vegetation was the most widely distributed,and the number of broadleaf forest was greater than that of coniferous forest.（2）The spatio-temporal variation characteristics of urban green space biomass were revealed.Biomass estimation models were developed separately according to green space types,and the effectiveness of two data sources,Sentinel-1 and Sentinel-2,and their combinations in green space biomass estimation was tested and compared.Compared with the models supported by single-source data,the multi-source stepwise regression biomass models with high accuracy(R_pj²≥0.75 and RMSE_pj≤35.95ton/ha)were used for biomass inversion.The results showed that the total value of urban green space biomass continued to increase,and the biomass density first decreased and then increased.The difference in urban green space biomass density between summer and winter was about 20 ton/ha,and the seasonal variation rate of total value was about 36%.Biomass hotspot areas were concentrated in the southwest and expanded slowly.The overall level of green space biomass between the loops was increased.The gradient characteristics of biomass were relatively obvious in terms of elevation and slope.（3）The carbon storage and sequestration potential of urban green space were estimated.The carbon storage of urban green space has been growing steadily for five consecutive years,and the southeast and southwest areas were the main contributing areas.Within the fixed carbon density interval,the broadleaf forest showed the most significant growth trend in carbon storage,the coniferous forest had more complicated changes,and shrub-grass vegetation had no significant interannual changes.The carbon sequestration potential of urban green space in Xuzhou was estimated by the maximum value method and the classification and grading method to reach 1.22 and0.61 Tg C,respectively,in which the contribution of the broadleaf forest was the highest（65.70%and 75.97%）and the lowest in the coniferous forest（3.79%and5.73%）.Based on the scenario assumptions of vegetation growth and area shift in urban green space,it is predicted that the carbon sequestration potential will reach0.40 Tg C by the mid-21st century.The thesis has 46 figures,32 tables,and 195 references.