To obtain accurate spatial distribution maps of soil organic carbon(SOC)and total nitrogen(TN)in the Hetian Town in Fujian Province,China,soil samples from three depths(0–20,20–40,and 40–60 cm)at 59 sampling sites ...To obtain accurate spatial distribution maps of soil organic carbon(SOC)and total nitrogen(TN)in the Hetian Town in Fujian Province,China,soil samples from three depths(0–20,20–40,and 40–60 cm)at 59 sampling sites were sampled by using traditional analysis and geostatistical approach.The SOC and TN ranged from 2.26 to 47.54 g kg-1,and from 0.28 to 2.71 g kg-1,respectively.The coefficient of variation for SOC and TN was moderate at 49.02–55.87%for all depths.According to the nuggetto-sill ratio values,a moderate spatial dependence of SOC content and a strong spatial dependence of TN content were found in different soil depths,demonstrating that SOC content was affected by both extrinsic and intrinsic factors while TN content was mainly influenced by intrinsic factors.Indices of cross-validation,such as mean error,mean standardized error,were close to zero,indicating that ordinary kriging interpolation is a reliable method to predict the spatial distribution of SOC and TN in different soil depths.Interpolation using ordinary kriging indicated the spatial pattern of SOC and TN were characterized by higher in the periphery and lower in the middle.To improve the accuracy of spatial interpolation for soil properties,it is necessary and important to incorporate a probabilistic and machine learning methods in the future study.展开更多
This study investigates the spatial variability of soil organic matter(SOM),soil organic carbon(SOC)and pH in the upper 20-cm layer and 20-40 cm layer in Moso bamboo(Phyllostachys pubescens Pradelle)forests using a ge...This study investigates the spatial variability of soil organic matter(SOM),soil organic carbon(SOC)and pH in the upper 20-cm layer and 20-40 cm layer in Moso bamboo(Phyllostachys pubescens Pradelle)forests using a geostatistics model.Interpolation maps of SOM,SOC,and pH were developed using ordinary kriging(OK)and inverse distance weighted(IDW)methods.The pH,SOC,and SOM of the two soil layers ranged from 4.6 to 4.7,from 1.5 to 2.7 g kg^(-1)and from 20.3 to 22.4 g kg^(-1),respectively.The coefficient of variation for SOM and SOC was 29.9-43.3%while a weak variability was found for pH.Gaussian and exponential models performed well in describing the spatial variability of SOC contents with R^(2)varying from 0.95 to 0.90.The nugget/sill values of pH are less than 25%,which indicates a strong spatial correlation,while the nugget/sill values of SOC and SOM fall under moderate spatial correlation.Interpolation using ordinary kriging and inverse distance weighted methods revealed that the spatial distribution of SOM,SOC,and pH was inconsistent due to external and internal factors across the plots.Regarding the cross-validation results,the ordinary kriging method performed better than inverse distance weighted method for selected soil properties.This study suggests that the spatial variability of soil chemical properties revealed by geostatistics modeling will help decision-makers improve the management of soil properties.展开更多
Voxel-based canopy profiling is commonly used to determine small-scale leaf area.Layer thickness and voxel size impact accuracy when using this method.Here,we determined the optimal combination of layer thickness and ...Voxel-based canopy profiling is commonly used to determine small-scale leaf area.Layer thickness and voxel size impact accuracy when using this method.Here,we determined the optimal combination of layer thickness and voxel size to estimate leaf area density accurately.Terrestrial LiDAR Stonex X300 was used to generate point cloud data for Masson pines(Pinus massoniana).The canopy layer was stratified into 0.10-1.00-m-thick layers,while voxel size was 0.01-0.10 m.The leaf area density of individual trees was estimated using leaf area indices for the upper,middle,and lower canopy and the overall canopy.The true leaf area index,obtained by layered harvesting,was used to verify the inversion results.Leaf area density was inverted by nine combinations of layer thickness and voxel size.The average relative accuracy and mean estimated accuracy of these combined inversion results exceeded 80%.When layer thickness was 1.00 m and voxel size 0.05 m,inversion was closest to the true value.The average relative accuracy was 92.58%,mean estimated accuracy 98.00%,and root mean square error 0.17.The combination of leaf area density and index was accurately retrieved.In conclusion,nondestructive voxel-based canopy profiling proved suitable for inverting the leaf area density of Masson pine in Hetian Town,Fujian Province.展开更多
A simplified two-dimensional model of two-layer porous burner based on pore level is developed.The heat transfer of solid phase in porous burner is seen as the synergistic effects of conduction through connecting brid...A simplified two-dimensional model of two-layer porous burner based on pore level is developed.The heat transfer of solid phase in porous burner is seen as the synergistic effects of conduction through connecting bridges and surface radiation between the solid particles in the model.A numerical simulation study on the characteristics of flow,combustion and heat transfer in the two-layer porous burner is carried out using the pore level model,and the effects of the control parameters such as the inlet velocity and solid thermal conductivity on thermal non-equilibrium are investigated.The results show that the flame structure is highly two-dimensional based on pore level.Obvious thermal non-equilibrium in the burner for the two phases and solid phase are observed,the largest temperature difference between the gas and solid phases is observed in combustion zone,while the temperature difference inside the solid particles is largest near the flame front.The results also reveal that thermal non-equilibrium of porous burner is much affected by the inlet velocity and solid thermal conductivity.展开更多
文摘To obtain accurate spatial distribution maps of soil organic carbon(SOC)and total nitrogen(TN)in the Hetian Town in Fujian Province,China,soil samples from three depths(0–20,20–40,and 40–60 cm)at 59 sampling sites were sampled by using traditional analysis and geostatistical approach.The SOC and TN ranged from 2.26 to 47.54 g kg-1,and from 0.28 to 2.71 g kg-1,respectively.The coefficient of variation for SOC and TN was moderate at 49.02–55.87%for all depths.According to the nuggetto-sill ratio values,a moderate spatial dependence of SOC content and a strong spatial dependence of TN content were found in different soil depths,demonstrating that SOC content was affected by both extrinsic and intrinsic factors while TN content was mainly influenced by intrinsic factors.Indices of cross-validation,such as mean error,mean standardized error,were close to zero,indicating that ordinary kriging interpolation is a reliable method to predict the spatial distribution of SOC and TN in different soil depths.Interpolation using ordinary kriging indicated the spatial pattern of SOC and TN were characterized by higher in the periphery and lower in the middle.To improve the accuracy of spatial interpolation for soil properties,it is necessary and important to incorporate a probabilistic and machine learning methods in the future study.
基金The work was supported by the National Key Research and Development Program of China:High Efficiency Cultivation and Monitoring Technology for Timber Bamboo(Grant No.:2018YFD0600103).
文摘This study investigates the spatial variability of soil organic matter(SOM),soil organic carbon(SOC)and pH in the upper 20-cm layer and 20-40 cm layer in Moso bamboo(Phyllostachys pubescens Pradelle)forests using a geostatistics model.Interpolation maps of SOM,SOC,and pH were developed using ordinary kriging(OK)and inverse distance weighted(IDW)methods.The pH,SOC,and SOM of the two soil layers ranged from 4.6 to 4.7,from 1.5 to 2.7 g kg^(-1)and from 20.3 to 22.4 g kg^(-1),respectively.The coefficient of variation for SOM and SOC was 29.9-43.3%while a weak variability was found for pH.Gaussian and exponential models performed well in describing the spatial variability of SOC contents with R^(2)varying from 0.95 to 0.90.The nugget/sill values of pH are less than 25%,which indicates a strong spatial correlation,while the nugget/sill values of SOC and SOM fall under moderate spatial correlation.Interpolation using ordinary kriging and inverse distance weighted methods revealed that the spatial distribution of SOM,SOC,and pH was inconsistent due to external and internal factors across the plots.Regarding the cross-validation results,the ordinary kriging method performed better than inverse distance weighted method for selected soil properties.This study suggests that the spatial variability of soil chemical properties revealed by geostatistics modeling will help decision-makers improve the management of soil properties.
基金This research was funded by Fujian University Industry-University Cooperation Project(grant number 2019N5012)Remote Sensing Quantitative Simulation of Rainfall Erosion Reduction Function of Forest Vertical Structure(grant number 31770760).
文摘Voxel-based canopy profiling is commonly used to determine small-scale leaf area.Layer thickness and voxel size impact accuracy when using this method.Here,we determined the optimal combination of layer thickness and voxel size to estimate leaf area density accurately.Terrestrial LiDAR Stonex X300 was used to generate point cloud data for Masson pines(Pinus massoniana).The canopy layer was stratified into 0.10-1.00-m-thick layers,while voxel size was 0.01-0.10 m.The leaf area density of individual trees was estimated using leaf area indices for the upper,middle,and lower canopy and the overall canopy.The true leaf area index,obtained by layered harvesting,was used to verify the inversion results.Leaf area density was inverted by nine combinations of layer thickness and voxel size.The average relative accuracy and mean estimated accuracy of these combined inversion results exceeded 80%.When layer thickness was 1.00 m and voxel size 0.05 m,inversion was closest to the true value.The average relative accuracy was 92.58%,mean estimated accuracy 98.00%,and root mean square error 0.17.The combination of leaf area density and index was accurately retrieved.In conclusion,nondestructive voxel-based canopy profiling proved suitable for inverting the leaf area density of Masson pine in Hetian Town,Fujian Province.
基金National Natural Science Foundation of China(No.51876107)。
文摘A simplified two-dimensional model of two-layer porous burner based on pore level is developed.The heat transfer of solid phase in porous burner is seen as the synergistic effects of conduction through connecting bridges and surface radiation between the solid particles in the model.A numerical simulation study on the characteristics of flow,combustion and heat transfer in the two-layer porous burner is carried out using the pore level model,and the effects of the control parameters such as the inlet velocity and solid thermal conductivity on thermal non-equilibrium are investigated.The results show that the flame structure is highly two-dimensional based on pore level.Obvious thermal non-equilibrium in the burner for the two phases and solid phase are observed,the largest temperature difference between the gas and solid phases is observed in combustion zone,while the temperature difference inside the solid particles is largest near the flame front.The results also reveal that thermal non-equilibrium of porous burner is much affected by the inlet velocity and solid thermal conductivity.
