Investigation Of Urban Street Tree Characteristics And Associated Function Evaluation Based On Street View Big Data Measurement

With the popularity of street view on urban road networks,street view big data can provide more and more information.It is urgent to use this information data to effectively evaluate urban ecosystems.Urban greening provides many high-quality ecosystem services for cities,and whether the use of streetscape information can be used to evaluate these ecological services and associated functions has not yet been determined.It is the general objective of our study to evaluate the characteristics of urban road forests based on streetscape information and,based on this,to evaluate the associated functions such as bird-preferred road forest environments,whether the control of air quality by road forests and the emission of harmful gases by plants themselves can also be evaluated using street view.For this purpose we conducted the following studies:firstly to determine the feasibility of measuring trees in the streetscape survey by comparison with field surveys within Harbin city;secondly,to conduct a latitudinal pattern large-scale（18.39°-45.37°）census of road forests to determine the latitudinal distribution pattern of urban street trees and the influencing factors;and to evaluate the effectiveness of urban bird observation using street images,using Qingdao city as an example;finally,the evaluation of the impact of urban greening on air quality control was carried out in the national capital cities（27）,and the emission of the BVOCs isoprene in Zhengzhou City was quantified on the basis of the above data.The preliminary conclusions are as follows:1.Establishment of a method for measuring trees using street view images.Use of scale-independent,fixed-sized street objects as recalibrating meters in tandem with imagery software has enabled street-view images to be used effectively in the remote measurement of diameter at breast height（DBH）,tree height,underbranch height,and canopy projection size.Comparison of four independent meters determined that stem limewhite-related meters（used for tree disease and bark-freeze injury control;usually 1.3 in height throughout China）had greater precision than road curb height,lane width,and traffic line width meters.The limewhite meter‘s precision was slightly lower than those of the meters in combination（i.e.,when at least three of the abovementioned meters were used for the same tree measurement）,but no statistically significant differences were detected between the limewhite and combined meters（p>0.05）.In contrast,the road curb height,traffic line width,and lane width meters all had significantly lower precision.The highest levels of precision were 92%,87%,and 80%for DBH,height（tree height and underbranch height）,and tree canopy size measurements,respectively.Empirical recalibration of the image-based measurements has not improved data precision with reference to field surveys（p>0.05）.Moreover,similar results were obtained regardless of individual users,and repeatability for DBH measurements（r²>0.92）,and maximum differences among individual users were 0.6–1.9 cm for DBH（averaged at 22 cm）and 8–50 cm for underbranch height（mean value at 8 m）.Labor costs and time needed for this approach were one-thirtieth to one-tenth those required for field surveys.Therefore,the use of street view imagery represents a more efficient way to assess forest ecological services.2.Latitudinal variation of street tree characteristics.As latitude increased,diameter breast height（DBH）,canopy projection size（CPS）decreased in a linear,along with an increase in the density of forests（>100 trees/100m street）.All trees‘sizes followed a log-normal distribution pattern.As latitude increased,the peak position（μ）of DBH and CPS decreased,under-canopy height（UCH）skewness shifted to the right,and CPS kurtosis became steeper.Tree health status showed strong latitude dependency（r²>0.4,p<0.05）,about 0.42%,1.50%,1.53%,and0.08%increases per 1°latitude increase in percentage diebacks abnormal leaf,unhealthy tree,and dead tree,respectively.National top abundant trees were Poplar,camphor,willow,plane tree,banyan（5.5%-14.6%）,and the arbor-shrub-herb layer forests took 52.3%of total plots.Latitude was positively related to the abundance of Poplar,willows,elm,and pine but negatively related to the unrecognized tree groups（p<0.05）.Latitude independence was in tree height and vertical forest structures.Combining health,tree size,and structure as indicators for the ecological service provision showed a linear decrease with latitude.RDA ordination found geoclimatic conditions（49%-61.5%）and social developments（21.4%-52.7%）were almost equally responsible for the variations in tree size,health,and species composition.At the same time,road width was the most crucial（coefficient>2.0%,p<0.01）.Our findings indicated that urban tree variation was geo-climatic dependent but sharply shaped by social development.3.Evaluating the feasibility of urban birds.Different rater repeatability was 79.1%in nest evaluations and 46.9%in bird occurrence.A re-check of the different-rating photos can increase them to 92%and 70%,respectively.Seven-rater statistics showed that>5%sampling ratio could produce a non-significant different in bird and nest percentage of the whole data.The middle-viewing layer survey alone could produce 93%precision of the nest checks by saving 2/3 of the time used;in birds,selecting middle and upper-view photos could find 97%of bird occurrences.In the spatial distribution,the nest‘s hotspot areas from this method were much greater than the community science bird-watching sites.While the BSV time machine made it possible to re-check nests in the same sites but challenging the re-check of bird occurrences.Nests and birds can be observed more problem in the leafless season,on wide,traffic-dense coastal streets with complex vertical structures of trees,and in the gaps of tall buildings dominated by road forests.Our results proved that BSV photos could be used to virtually evaluate bird occurrence and nests from their numbers,spatial distribution,and temporal dynamics.4.Relationship between greenery and air quality and O₃ pollution.The national averages for the sky,ground and middle-level（shrub and short trees）view greenness were 5.4%,5.5%,and 15.4%,respectively,and the sky:ground:middle ratio was 2:2:6.Street-view/bird-view greenness ratio averaged at 1.1.Large inter-city variations were observed in all the greenness parameters,and the weak associations between all street-view parameters and bird-eye greenspace percentage（21%-73%）indicate their representatives of different aspects of green infrastructures.All air quality parameters were higher in winter than in summer,except O₃.Over 90%of air quality variation could be explained by socioeconomics and geoclimates.For different air quality components,greenness had showed most significant associations with NO₂,O₃ and CO,and street-view/bird-view ratio was the most powerful indicator of all greenness parameters.Pooled-data analysis at national level showed that street-view greenness was responsible for 2.3%of the air quality variations in the summer and 3.6%in the winter;however,when separated into different regions（North-South China;East-West China）,the explaining power increased up to 16.2%.Increased NO₂ was accompanied with decreased O₃,indicating NO titration effect.The higher O₃ aligned with the higher street-view greenness,showing the greenness-related precursor risk for O₃ pollution.For this reason,we quantified the precursors of O₃ pollution,isoprene,in Zhengzhou city as an example.Among them,the city is dominated by growing trees,52%of which are in the diameter at breast height range of10-20 cm;66%of trees are less than 10 m tall.The trees were mainly composed of plane（34.06%）,poplar（20.45%）and locust tree（15.62%）.Zhengzhou City emitted 5.022 tons of isoprene alone in 2016,of which 83.9%was accounted for by one tree species alone,the plane tree.The largest area of isoprene emissions in Zhengzhou is concentrated in Songshan Road（2.76 tons/year）,where the tall and lush plane trees are planted.RDA analysis was conducted on the size of the trees and the proportion of tree species and some socioeconomic factors,and the most important factors affecting isoprene emissions from trees were the diameter at breast height of the trees and the proportion of plane trees.In summary,evaluating urban street trees and their associated functions through the application of streetscape big data is different from the perspective of real measurements and remote sensing.Studies at the sample point,urban,regional and national levels provide data support for accurate assessment of urban forest management and its ecological services.The studies of latitudinal change patterns of street trees,street-level needs of urban birds,and air pollution control and emissions can provide theoretical support for the multiple needs of urban forests and are important for improving the net ecosystem service capacity of cities.