Study On Sample Area Scale Effect Of Urban Vegetation LAI Retrieval Based On Landsattm And SPOT6 Images

Urban green space is the core part of maintaining stability of urban ecosystem,it has the function of maintaining regional carbon balance,adjusting the microclimate,air purification,water conservation and so on.Leaf area index is the key parameter of setting up all kinds of ecosystem function index model.In the study of urban green space,ecological function plays an important role.With the continuous development of remote sensing technology,remote sensing inversion method has become an important way to gain Leaf area index distribution data in a large area.We choose the area within the third ring road in Wuhan as the research area,and set 13 samples of 100m*100m,then divide each sample into 100 small plots with 10m*10m.Field data of 1300 small plots are determinate during 6-10 in 2015.LAI of different plot size were reversed using the statistical models based on SPOT6 and TM images.LAI inversion scale effect of sample size shows by determinant coefficients and prediction accuracy of LAI inversion models.The results are as follows:(1)Under each sample area scale,the determinant coefficient and prediction accuracy of SPOT6 image are higher than those of TM image.It confirms that the scale effect of spatial resolution for remote sensing,which is consistent with the former’s research.(2)Under SPOT6 image,with the increasing of plot size(10mx10m,20mx20m,30m’30m,40mx40m,50mx50m,60mx60m),the determinant coefficients(R2)and the prediction accuracy of optimal LAI inversion models increase,meanwhile the S x decrease.The value of R2(0.856)and the prediction accuracy(89.34%)reach the maximum and the Sx(0.074)reach the minimum in the 60mx60m sample scale.Scale effect of LAI inversion because of different sample size.(3)Under TM image,with the increasing of plot size(10m×10m,20m×20m,30m×30m,40m×40m,50m×50m,60m×60m),the determinant coefficients(R2)and the prediction accuracy of optimal LAI inversion models increase,meanwhile the S x decrease.The value of R2(0.787)and the prediction accuracy(87.74%)reach the maximum and the S x(0.127)reach the minimum in the 60mx60m sample scale.Scale effect of LAI inversion because of different sample size.(4)Scale effect because of difference sample area of LAI inversion was not caused by different VI selection,Using SAVI model inversion under different sample area scale,Both the SPOT6 and TM images,Scale effect even existed.