Uncertainties of landslide susceptibility prediction:influences of different study area scales and mapping unit scales

This study aims to investigate the effects of different mapping unit scales and study area scales on the uncertainty rules of landslide susceptibility prediction(LSP).To illustrate various study area scales,Ganzhou City in China,its eastern region(Ganzhou East),and Ruijin County in Ganzhou East were chosen.Different mapping unit scales are represented by grid units with spatial resolution of 30 and 60 m,as well as slope units that were extracted by multi-scale segmentation method.The 3855 landslide locations and 21 typical environmental factors in Ganzhou City are first determined to create spatial datasets with input-outputs.Then,landslide susceptibility maps(LSMs)of Ganzhou City,Ganzhou East and Ruijin County are pro-duced using a support vector machine(SVM)and random forest(RF),respectively.The LSMs of the above three regions are then extracted by mask from the LSM of Ganzhou City,along with the LSMs of Ruijin County from Ganzhou East.Additionally,LSMs of Ruijin at various mapping unit scales are generated in accordance.Accuracy and landslide suscepti-bility indexes(LSIs)distribution are used to express LSP uncertainties.The LSP uncertainties under grid units significantly decrease as study area scales decrease from Ganzhou City,Ganzhou East to Ruijin County,whereas those under slope units are less affected by study area scales.Of course,attentions should also be paid to the broader representativeness of large study areas.The LSP accuracy of slope units increases by about 6%–10%compared with those under grid units with 30 m and 60 m resolution in the same study area's scale.The significance of environmental factors exhibits an averaging trend as study area scale increases from small to large.The importance of environmental factors varies greatly with the 60 m grid unit,but it tends to be consistent to some extent in the 30 m grid unit and the slope unit.

Extrapolation reconstruction of wind pressure fields on the claddings of high-rise buildings

Recent research about reconstruction methods mainly used the interpolation reconstruction of the fluctuating wind pressure field on the surface.However,to investigate wind pressure at the edge of the building,the work presented in this paper focuses on the extrapolation reconstruction of wind pressure fields.Here,we propose an improved proper orthogonal decomposition(POD)and Kriging method with a von Karman correlation function to resolve this issue.The studies show that it works well for not only interpolation reconstruction but also extrapolation reconstruction.The proposed method does require determination of the Hurst exponent and other parameters analysed from the original data.Hence,the fluctuating wind fields have been characterized by the von Karman correlation function,as an a priori function.Compared with the cubic spline method and different variogram,preliminary results suggest less time consumption and high efficiency in extrapolation reconstruction at the edge.