[Objective] The objective of this project was to evaluate and compare spa- tial estimation accuracy by ordinary kriging and regression kriging with MODIS data, predicting SOM contents using limited available data in S...[Objective] The objective of this project was to evaluate and compare spa- tial estimation accuracy by ordinary kriging and regression kriging with MODIS data, predicting SOM contents using limited available data in Shimen County, Hunan Province, China. [Method] Terrain parameters (derived from DEM) and Normalized differential vegetation index (NDVI), Land surface temperature (LST) (derived from MODIS data) were used as auxiliary data to predict the SOM spatial distribution. The mean error (ME) and mean square error (RMSE) were adopted to validate the SOM prediction accuracy. The descriptive statistics and data transformation were conducted by using computer technology. [Result] Regression kriging with terrain and remotely sensed data was superior to ordinary kriging in the case of limited available samples; even the linear relationship between environmental variables and SOM content was moderate. The accuracy assessment showed that the regression kriging method combining with environmental factors obtained a lower mean predication error and root mean square prediction error. The relative improvement was 6.03% compared with ordinary kriging. [Conclusion] Remotely sensed data such as MODIS im- age have the potential as useful auxiliary variables for improving the precision and reliability of SOM prediction in the hilly regions.展开更多
Based on the transverse Ising model and using decoupling approximation to the Fermi-type Green's function, we study the phase transition properties of the epitaxial ferroeleetric film with one substrate. A general re...Based on the transverse Ising model and using decoupling approximation to the Fermi-type Green's function, we study the phase transition properties of the epitaxial ferroeleetric film with one substrate. A general recursive equation of the ferroelectric thin film with two n-layer materials is obtained, which enables us to study the phase transition properties for any number layers for epitaxial ferroelectric thin film. With the help of this equation, we analyze the effect of the exchange interaction and the transverse field in the phase diagram, the influence to the polarizations and Curie temperature numerically. The results show that epitaxial ferroelectric film are able to induce a strong increase or decrease of Curie temperature to different exchange interactions and transverse fields within the epitaxial film layers. The theoretical results are in reasonable accordance with experimental data of different ferroelectric thin film.展开更多
Let λf(n) be the n-th normalized Fourier coefficient of a holomorphic Hecke eigenform f(z) ∈Sk(Γ).We establish that, for any ε > 0,1/Xintegral from n=1 to x|sum λ~2f^((n^2)) from n≤x to - c_2x|2dx ?ε X154/1...Let λf(n) be the n-th normalized Fourier coefficient of a holomorphic Hecke eigenform f(z) ∈Sk(Γ).We establish that, for any ε > 0,1/Xintegral from n=1 to x|sum λ~2f^((n^2)) from n≤x to - c_2x|2dx ?ε X154/101+ε,which improves previous results.展开更多
This paper considers the semiparametric regression model Yi = xiβ+g(ti)+ Vi (1 ≤ i≤ n), where (xi, ti) are known design points, fl is an unknown slope parameter, g(.) is an unknown function, the correlate...This paper considers the semiparametric regression model Yi = xiβ+g(ti)+ Vi (1 ≤ i≤ n), where (xi, ti) are known design points, fl is an unknown slope parameter, g(.) is an unknown function, the correlated errors Vi = ∑^∞j=-∞cjei-j with ∑^∞j=-∞|cj| 〈 ∞, and ei are negatively associated random variables. Under appropriate conditions, the authors study the asymptotic normality for wavelet estimators ofβ and g(·). A simulation study is undertaken to investigate finite sample behavior of the estimators.展开更多
Overabundance of phosphorus (P) in soils and water is of great concern and has received much attention in Florida, USA. Therefore, it is essential to analyze and predict the distribution of P in soils across large are...Overabundance of phosphorus (P) in soils and water is of great concern and has received much attention in Florida, USA. Therefore, it is essential to analyze and predict the distribution of P in soils across large areas. This study was undertaken to model the variation of soil total phosphorus (TP) in Florida. A total of 448 soil samples were collected from different soil types. Soil samples were analyzed by chemical reference method and scanned in the visible/near-infrared (VNIR) region of 350-2 500 nm. Partial least squares regression (PLSR) calibration model was developed between chemical reference values and VNIR values. The coefficient of determination (R2) and the root mean squares error (RMSE) of calibration and validation sets, and the residual prediction deviation (RPD) were used to evaluate the models. The R2in calibration and validation for log-transformed TP (log TP) were 0.69 and 0.65, respectively, indicating that VNIR calibration obtained in this study accounted for at least 65% of the variance in log TP using only VNIR spectra, and the high RPD of 2.82 obtained suggested that the spectral model derived in this study was suitable and robust to predict TP in a wide range of soil types, being representative of Florida soil conditions.展开更多
Among spatial interpolation techniques,geostatistics is generally preferred because it takes into account the spatial correlation between neighbouring observations in order to predict attribute values at unsampled loc...Among spatial interpolation techniques,geostatistics is generally preferred because it takes into account the spatial correlation between neighbouring observations in order to predict attribute values at unsampled locations.A doline of approximately 15 000 m 2 at 1 900 m above sea level (North Italy) was selected as the study area to estimate a digital elevation model (DEM) using geostatistics,to provide a realistic distribution of the errors and to demonstrate whether using widely available secondary data provided more accurate estimates of soil pH than those obtained by univariate kriging.Elevation was measured at 467 randomly distributed points that were converted into a regular DEM using ordinary kriging.Further,110 pits were located using spatial simulated annealing (SSA) method.The interpolation techniques were multi-linear regression analysis (MLR),ordinary kriging (OK),regression kriging (RK),kriging with external drift (KED) and multi-collocated ordinary cokriging (CKmc).A cross-validation test was used to assess the prediction performances of the different algorithms and then evaluate which methods performed best.RK and KED yielded better results than the more complex CKmc and OK.The choice of the most appropriate interpolation method accounting for redundant auxiliary information was strongly conditioned by site specific situations.展开更多
The main objectives of this study were to introduce an integrated method for effectively identifying soil heavy metal pollution sources and apportioning their contributions, and apply it to a case study. The method co...The main objectives of this study were to introduce an integrated method for effectively identifying soil heavy metal pollution sources and apportioning their contributions, and apply it to a case study. The method combines the principal component analysis/absolute principal component scores (PCA/APCS) receptor model and geostatistics. The case study was conducted in an area of 31 km2 in the urban-rural transition zone of Wuhan, a metropolis of central China. 124 topsoil samples were collected for measuring the concentrations of eight heavy metal elements (Mn, Cu, Zn, Pb, Cd, Cr, Ni and Co). PCA results revealed that three major factors were responsible for soil heavy metal pollution, which were initially identified as "steel production", "agronomic input" and "coal consumption". The APCS technique, combined with multiple linear regression analysis, was then applied for source apportionment. Steel production appeared to be the main source for Ni, Co, Cd, Zn and Mn, agronomic input for Cu, and coal consumption for Pb and Cr. Geostatistical interpolation using ordinary kriging was finally used to map the spatial distributions of the contributions of pollution sources and further confirm the result interpretations. The introduced method appears to be an effective tool in soil pollution source apportionment and identification, and might provide valuable reference information for pollution control and environmental management.展开更多
基金Supported by National Natural Science Foundation of China(41071204)Hunan Provincial Innovation Foundation for Postgraduate(CX2011B310)~~
文摘[Objective] The objective of this project was to evaluate and compare spa- tial estimation accuracy by ordinary kriging and regression kriging with MODIS data, predicting SOM contents using limited available data in Shimen County, Hunan Province, China. [Method] Terrain parameters (derived from DEM) and Normalized differential vegetation index (NDVI), Land surface temperature (LST) (derived from MODIS data) were used as auxiliary data to predict the SOM spatial distribution. The mean error (ME) and mean square error (RMSE) were adopted to validate the SOM prediction accuracy. The descriptive statistics and data transformation were conducted by using computer technology. [Result] Regression kriging with terrain and remotely sensed data was superior to ordinary kriging in the case of limited available samples; even the linear relationship between environmental variables and SOM content was moderate. The accuracy assessment showed that the regression kriging method combining with environmental factors obtained a lower mean predication error and root mean square prediction error. The relative improvement was 6.03% compared with ordinary kriging. [Conclusion] Remotely sensed data such as MODIS im- age have the potential as useful auxiliary variables for improving the precision and reliability of SOM prediction in the hilly regions.
基金Supported partly by SRF for ROCS,SEM under Grant No.20071108
文摘Based on the transverse Ising model and using decoupling approximation to the Fermi-type Green's function, we study the phase transition properties of the epitaxial ferroeleetric film with one substrate. A general recursive equation of the ferroelectric thin film with two n-layer materials is obtained, which enables us to study the phase transition properties for any number layers for epitaxial ferroelectric thin film. With the help of this equation, we analyze the effect of the exchange interaction and the transverse field in the phase diagram, the influence to the polarizations and Curie temperature numerically. The results show that epitaxial ferroelectric film are able to induce a strong increase or decrease of Curie temperature to different exchange interactions and transverse fields within the epitaxial film layers. The theoretical results are in reasonable accordance with experimental data of different ferroelectric thin film.
基金supported by National Natural Science Foundation of China(Grant No.11101249)
文摘Let λf(n) be the n-th normalized Fourier coefficient of a holomorphic Hecke eigenform f(z) ∈Sk(Γ).We establish that, for any ε > 0,1/Xintegral from n=1 to x|sum λ~2f^((n^2)) from n≤x to - c_2x|2dx ?ε X154/101+ε,which improves previous results.
基金supported by the National Natural Science Foundation of China under Grant No.10871146
文摘This paper considers the semiparametric regression model Yi = xiβ+g(ti)+ Vi (1 ≤ i≤ n), where (xi, ti) are known design points, fl is an unknown slope parameter, g(.) is an unknown function, the correlated errors Vi = ∑^∞j=-∞cjei-j with ∑^∞j=-∞|cj| 〈 ∞, and ei are negatively associated random variables. Under appropriate conditions, the authors study the asymptotic normality for wavelet estimators ofβ and g(·). A simulation study is undertaken to investigate finite sample behavior of the estimators.
基金Supported by the National Natural Science Foundation of China (No. 41071159)the Cooperative Ecosystem Studies UnitNational Resources Conservation Service (NRCS), USA
文摘Overabundance of phosphorus (P) in soils and water is of great concern and has received much attention in Florida, USA. Therefore, it is essential to analyze and predict the distribution of P in soils across large areas. This study was undertaken to model the variation of soil total phosphorus (TP) in Florida. A total of 448 soil samples were collected from different soil types. Soil samples were analyzed by chemical reference method and scanned in the visible/near-infrared (VNIR) region of 350-2 500 nm. Partial least squares regression (PLSR) calibration model was developed between chemical reference values and VNIR values. The coefficient of determination (R2) and the root mean squares error (RMSE) of calibration and validation sets, and the residual prediction deviation (RPD) were used to evaluate the models. The R2in calibration and validation for log-transformed TP (log TP) were 0.69 and 0.65, respectively, indicating that VNIR calibration obtained in this study accounted for at least 65% of the variance in log TP using only VNIR spectra, and the high RPD of 2.82 obtained suggested that the spectral model derived in this study was suitable and robust to predict TP in a wide range of soil types, being representative of Florida soil conditions.
文摘Among spatial interpolation techniques,geostatistics is generally preferred because it takes into account the spatial correlation between neighbouring observations in order to predict attribute values at unsampled locations.A doline of approximately 15 000 m 2 at 1 900 m above sea level (North Italy) was selected as the study area to estimate a digital elevation model (DEM) using geostatistics,to provide a realistic distribution of the errors and to demonstrate whether using widely available secondary data provided more accurate estimates of soil pH than those obtained by univariate kriging.Elevation was measured at 467 randomly distributed points that were converted into a regular DEM using ordinary kriging.Further,110 pits were located using spatial simulated annealing (SSA) method.The interpolation techniques were multi-linear regression analysis (MLR),ordinary kriging (OK),regression kriging (RK),kriging with external drift (KED) and multi-collocated ordinary cokriging (CKmc).A cross-validation test was used to assess the prediction performances of the different algorithms and then evaluate which methods performed best.RK and KED yielded better results than the more complex CKmc and OK.The choice of the most appropriate interpolation method accounting for redundant auxiliary information was strongly conditioned by site specific situations.
基金Supported by the National Natural Science Foundation of China (No. 40971269)
文摘The main objectives of this study were to introduce an integrated method for effectively identifying soil heavy metal pollution sources and apportioning their contributions, and apply it to a case study. The method combines the principal component analysis/absolute principal component scores (PCA/APCS) receptor model and geostatistics. The case study was conducted in an area of 31 km2 in the urban-rural transition zone of Wuhan, a metropolis of central China. 124 topsoil samples were collected for measuring the concentrations of eight heavy metal elements (Mn, Cu, Zn, Pb, Cd, Cr, Ni and Co). PCA results revealed that three major factors were responsible for soil heavy metal pollution, which were initially identified as "steel production", "agronomic input" and "coal consumption". The APCS technique, combined with multiple linear regression analysis, was then applied for source apportionment. Steel production appeared to be the main source for Ni, Co, Cd, Zn and Mn, agronomic input for Cu, and coal consumption for Pb and Cr. Geostatistical interpolation using ordinary kriging was finally used to map the spatial distributions of the contributions of pollution sources and further confirm the result interpretations. The introduced method appears to be an effective tool in soil pollution source apportionment and identification, and might provide valuable reference information for pollution control and environmental management.