Freeze‒thaw induced landslides(FTILs)in grasslands on the Tibetan Plateau are a geological disaster leading to soil erosion.These landslides reduce biodiversity and intensify landscape fragmentation,which in turn are ...Freeze‒thaw induced landslides(FTILs)in grasslands on the Tibetan Plateau are a geological disaster leading to soil erosion.These landslides reduce biodiversity and intensify landscape fragmentation,which in turn are strengthen by the persistent climate change and increased anthropogenic activities.However,conventional techniques for mapping FTILs on a regional scale are impractical due to their labor-intensive,costly,and time-consuming nature.This study focuses on improving FTILs detection by implementing image fusion-based Google Earth Engine(GEE)and a random forest algorithm.Integration of multiple data sources,including texture features,index features,spectral features,slope,and vertical‒vertical polarization data,allow automatic detection of the spatial distribution characteristics of FTILs in Zhidoi county,which is located within the Qinghai‒Tibet Engineering Corridor(QTEC).We employed statistical techniques to elucidate the mechanisms influencing FTILs occurrence.The enhanced method identifies two schemes that achieve high accuracy using a smaller training sample(scheme A:94.1%;scheme D:94.5%)compared to other methods(scheme B:50.0%;scheme C:95.8%).This methodology is effective in generating accurate results using only~10%of the training sample size necessitated by other methods.The spatial distribution patterns of FTILs generated for 2021 are similar to those obtained using various other training sample sources,with a primary concentration observed along the central region traversed by the QTEC.The results highlight the slope as the most crucial feature in the fusion images,accounting for 93%of FTILs occurring on gentle slopes ranging from 0°to 14°.This study provides a theoretical framework and technological reference for the identification,monitoring,prevention and control of FTILs in grasslands.Such developments hold the potential to benefit the management of grassland ecosystem,reduce economic losses,and promote grassland sustainability.展开更多
Thermoelectric(TE)performance of polycrystalline stannous selenide(SnSe)has been remarkably promoted by the strategies of energy band,defect engineering,etc.However,due to the intrinsic insufficiencies of phonon scatt...Thermoelectric(TE)performance of polycrystalline stannous selenide(SnSe)has been remarkably promoted by the strategies of energy band,defect engineering,etc.However,due to the intrinsic insufficiencies of phonon scattering and carrier concentration,it is hard to simultaneously realize the regulations of electrical and thermal transport properties by one simple approach.Herein,we develop Cu and Ce co-doping strategy that can not only greatly reduce lattice thermal conductivity but also improve the electrical transport properties.In this strategy,the incorporated Cu and Ce atoms could induce high-density SnSe_(2) nanoprecipitation arrays on the surface of SnSe microplate,and produce dopant atom point defects and dislocations in its interior,which form multi-scale phonon scattering synergy,thereby presenting an ultralow thermal conductivity of 0.275 W·m^(−1)·K^(−1) at 786 K.Meanwhile,density functional theory(DFT)calculations,carrier concentration,and mobility testing reveal that more extra hole carriers and lower conducting carrier scattering generate after Cu and Ce co-doping,thereby improving the electrical conductivity.The co-doped Sn_(0.98)Cu_(0.01)Ce_(0.01)Se bulk exhibits an excellent ZT value up to~1.2 at 786 K and a high average ZT value of 0.67 from 300 to 786 K.This work provides a simple and convenient strategy of enhancing the TE performance of polycrystalline SnSe.展开更多
基金the Innovation Capability Support Program of Shaanxi Province(2023-JC-JQ-25)High-end Foreign Experts Recruitment Plan of China(G2021172006L and G2023172014L).
文摘Freeze‒thaw induced landslides(FTILs)in grasslands on the Tibetan Plateau are a geological disaster leading to soil erosion.These landslides reduce biodiversity and intensify landscape fragmentation,which in turn are strengthen by the persistent climate change and increased anthropogenic activities.However,conventional techniques for mapping FTILs on a regional scale are impractical due to their labor-intensive,costly,and time-consuming nature.This study focuses on improving FTILs detection by implementing image fusion-based Google Earth Engine(GEE)and a random forest algorithm.Integration of multiple data sources,including texture features,index features,spectral features,slope,and vertical‒vertical polarization data,allow automatic detection of the spatial distribution characteristics of FTILs in Zhidoi county,which is located within the Qinghai‒Tibet Engineering Corridor(QTEC).We employed statistical techniques to elucidate the mechanisms influencing FTILs occurrence.The enhanced method identifies two schemes that achieve high accuracy using a smaller training sample(scheme A:94.1%;scheme D:94.5%)compared to other methods(scheme B:50.0%;scheme C:95.8%).This methodology is effective in generating accurate results using only~10%of the training sample size necessitated by other methods.The spatial distribution patterns of FTILs generated for 2021 are similar to those obtained using various other training sample sources,with a primary concentration observed along the central region traversed by the QTEC.The results highlight the slope as the most crucial feature in the fusion images,accounting for 93%of FTILs occurring on gentle slopes ranging from 0°to 14°.This study provides a theoretical framework and technological reference for the identification,monitoring,prevention and control of FTILs in grasslands.Such developments hold the potential to benefit the management of grassland ecosystem,reduce economic losses,and promote grassland sustainability.
基金support of the National Natural Science Foundation of China(Grant Nos.51702193 and 51502165)the Natural Science Basic Research Program of Shaanxi(Grant No.2022JM-202)+3 种基金the Shaanxi Provincial Education Department Serves Local Scientific Research Plan(Grant No.20JC008)the General Project in Industrial Area of Shaanxi Province(Grant No.2020GY281)the Natural Science Foundation of Shaanxi Provincial Department of Education(Grant No.20JK0525)the Scientific Research Fund of Shaanxi University of Science&Technology(Grant Nos.BJ16-20 and BJ16-21).
文摘Thermoelectric(TE)performance of polycrystalline stannous selenide(SnSe)has been remarkably promoted by the strategies of energy band,defect engineering,etc.However,due to the intrinsic insufficiencies of phonon scattering and carrier concentration,it is hard to simultaneously realize the regulations of electrical and thermal transport properties by one simple approach.Herein,we develop Cu and Ce co-doping strategy that can not only greatly reduce lattice thermal conductivity but also improve the electrical transport properties.In this strategy,the incorporated Cu and Ce atoms could induce high-density SnSe_(2) nanoprecipitation arrays on the surface of SnSe microplate,and produce dopant atom point defects and dislocations in its interior,which form multi-scale phonon scattering synergy,thereby presenting an ultralow thermal conductivity of 0.275 W·m^(−1)·K^(−1) at 786 K.Meanwhile,density functional theory(DFT)calculations,carrier concentration,and mobility testing reveal that more extra hole carriers and lower conducting carrier scattering generate after Cu and Ce co-doping,thereby improving the electrical conductivity.The co-doped Sn_(0.98)Cu_(0.01)Ce_(0.01)Se bulk exhibits an excellent ZT value up to~1.2 at 786 K and a high average ZT value of 0.67 from 300 to 786 K.This work provides a simple and convenient strategy of enhancing the TE performance of polycrystalline SnSe.
