remote sensing of woody vegetation in savannas has been inhibited by its complex stand structure and abundant vegetation species.An understanding of the distribution and spatial variation in savanna vegetation is crit...remote sensing of woody vegetation in savannas has been inhibited by its complex stand structure and abundant vegetation species.An understanding of the distribution and spatial variation in savanna vegetation is critical for making timely assessments of the ecosystem conditions.This study investigated the possibility of improving the prediction of woody vegetation in tropical savannas using an approach that integrates spatial statistics and remote sensing.展开更多
Analysis of influence of spatial trend on calculated genetic correlation coeffi-cient was carried out on winter wheat variety trial of a random block design. The result indicated that significant spatial structure ex...Analysis of influence of spatial trend on calculated genetic correlation coeffi-cient was carried out on winter wheat variety trial of a random block design. The result indicated that significant spatial structure existed in thousand kernel weight and kernels per head of winter wheat. Simulated data based on field data demonstrate that strong spatial trend is one of the important causes for genetic correlation coefficient (absolute value) being greater than 1. We suggested that analysis of spatial structure of field data by geostatistical technology be conducted before calculating genetic correlation coefficient.展开更多
Aim of the study is to evaluate the environmental impact of geothermic activities by the use of in site spectral analyses of different environmental com- ponents.These activities can cause the heavy metal （Hg,Sb,S,B,...Aim of the study is to evaluate the environmental impact of geothermic activities by the use of in site spectral analyses of different environmental com- ponents.These activities can cause the heavy metal （Hg,Sb,S,B,As,H<sub>2</sub>S）drifting from power plants to around areas.Different analytical techniques展开更多
Electrical conductivity(EC)is considered as the most important indicator for assessment of groundwater quality.Determination of suitable interpolation method for derivation of groundwater quality variables map such as...Electrical conductivity(EC)is considered as the most important indicator for assessment of groundwater quality.Determination of suitable interpolation method for derivation of groundwater quality variables map such as EC is dependent on region conditions and existence of enough data.For determining groundwater EC,341 groundwater samples were randomly collected from the central regions of Guilan province,paddy soils,in northern Iran.Interpolation methods including inverse distance weighting(IDW),global polynomial interpolation(GPI),local polynomial interpolation(LPI),radial basis function(RBF),ordinary kriging(OK)and empirical Bayesian Kriging(EBK)were used to generate spatial distribution of groundwater EC.The results indicate that EBK is a superior method with the least RMSE,MAE and the highest R 2.The generated maps can be used to identify the regions in the studied area where groundwater could be allowed to be extracted and utilized by farmers to reduce adverse effect of the scarcity of surface water.展开更多
文摘remote sensing of woody vegetation in savannas has been inhibited by its complex stand structure and abundant vegetation species.An understanding of the distribution and spatial variation in savanna vegetation is critical for making timely assessments of the ecosystem conditions.This study investigated the possibility of improving the prediction of woody vegetation in tropical savannas using an approach that integrates spatial statistics and remote sensing.
文摘Analysis of influence of spatial trend on calculated genetic correlation coeffi-cient was carried out on winter wheat variety trial of a random block design. The result indicated that significant spatial structure existed in thousand kernel weight and kernels per head of winter wheat. Simulated data based on field data demonstrate that strong spatial trend is one of the important causes for genetic correlation coefficient (absolute value) being greater than 1. We suggested that analysis of spatial structure of field data by geostatistical technology be conducted before calculating genetic correlation coefficient.
文摘Aim of the study is to evaluate the environmental impact of geothermic activities by the use of in site spectral analyses of different environmental com- ponents.These activities can cause the heavy metal （Hg,Sb,S,B,As,H<sub>2</sub>S）drifting from power plants to around areas.Different analytical techniques
文摘Electrical conductivity(EC)is considered as the most important indicator for assessment of groundwater quality.Determination of suitable interpolation method for derivation of groundwater quality variables map such as EC is dependent on region conditions and existence of enough data.For determining groundwater EC,341 groundwater samples were randomly collected from the central regions of Guilan province,paddy soils,in northern Iran.Interpolation methods including inverse distance weighting(IDW),global polynomial interpolation(GPI),local polynomial interpolation(LPI),radial basis function(RBF),ordinary kriging(OK)and empirical Bayesian Kriging(EBK)were used to generate spatial distribution of groundwater EC.The results indicate that EBK is a superior method with the least RMSE,MAE and the highest R 2.The generated maps can be used to identify the regions in the studied area where groundwater could be allowed to be extracted and utilized by farmers to reduce adverse effect of the scarcity of surface water.
