Most evaluation of the consistency of multisensor images have focused on Normalized Difference Vegetation Index(NDVI) products for natural landscapes, often neglecting less vegetated urban landscapes. This gap has bee...Most evaluation of the consistency of multisensor images have focused on Normalized Difference Vegetation Index(NDVI) products for natural landscapes, often neglecting less vegetated urban landscapes. This gap has been filled through quantifying and evaluating spatial heterogeneity of urban and natural landscapes from QuickBird, Satellite pour l'observation de la Terre(SPOT), Advanced Spaceborne Thermal Emission and Reflection Radiometer(ASTER) and Landsat Thematic Mapper(TM) images with variogram analysis. Instead of a logarithmic relationship with pixel size observed in the corresponding aggregated images, the spatial variability decayed and the spatial structures decomposed more slowly and complexly with spatial resolution for real multisensor images. As the spatial resolution increased, the proportion of spatial variability of the smaller spatial structure decreased quickly and only a larger spatial structure was observed at very coarse scales. Compared with visible band, greater spatial variability was observed in near infrared band for both densely and less densely vegetated landscapes. The influence of image size on spatial heterogeneity was highly dependent on whether the empirical semivariogram reached its sill within the original image size. When the empirical semivariogram did not reach its sill at the original observation scale, spatial variability and mean characteristic length scale would increase with image size; otherwise they might decrease. This study could provide new insights into the knowledge of spatial heterogeneity in real multisensor images with consideration of their nominal spatial resolution, image size and spectral bands.展开更多
This study is based on meteorological observation data collected at 38 weather stations on the Tibetan Plateau over several decades. Daily reference crop evapotranspiration （ETo） was calculated with the FAO-56 stand...This study is based on meteorological observation data collected at 38 weather stations on the Tibetan Plateau over several decades. Daily reference crop evapotranspiration （ETo） was calculated with the FAO-56 standard Penman-Monteith formula. A test of normality was performed with Statistica 6.0 software, isotropic and anisotropic semi-variogram analysis was conducted with the GS＋ （geostatistics for the environmental sciences） system for Windows 7.0, and the characteristics of spatial variation of daily ETo were obtained. The following results can be obtained Daily ETo for different periods on the Tibetan Plateau are distributed normally; Except for daily ETo in the E-W （east-west） direction in the summer, which showed a slight negative correlation with distance change, the Moran＇s indexes of daily ETo for different periods in all directions on the Tibetan Plateau within a 100-km distance were positive, demonstrating a positive correlation with distance change; Variograms of daily ETo in June, the dry season, the wet season, as well as annual average daily ETo fit well with the Gaussian model; A variogram of daily ETo in December fit well with the exponential model; Variograms of daily ETo for the four seasons fit well with the linear With sill model.展开更多
A structural analysis of K of an aquifer system in the study area is presented, and the main direction and degree of the variability of K are found by using the unstationary regionalized variable theory of geostatisti...A structural analysis of K of an aquifer system in the study area is presented, and the main direction and degree of the variability of K are found by using the unstationary regionalized variable theory of geostatistics. Optimal estimation of K has been made by universal kriging method (U K M ). Both spatial variability distribution map and division map of K are given.展开更多
Microbial indices and their spatial patterns are strongly affected by environmental factors. Spatial variability of soil properties is one of the most important causes of variability in soil microbial indices. This re...Microbial indices and their spatial patterns are strongly affected by environmental factors. Spatial variability of soil properties is one of the most important causes of variability in soil microbial indices. This research was conducted in the Caspian forest to assess spatial variabilities and frequency distributions of microbial properties.Ninety soil samples were taken using a grid sampling design 40 9 40 m. Microbial indices, organic carbon,nitrogen and pH were determined. Soil variable distributions showed that microbial indices had abnormal distributions. Logarithmic transformation produced normal distribution. Spatial continuity using geostatistical(variogram) was studied and maps obtained by point kriging.The variograms revealed the presence of spatial autocorrelation. The results indicate that spatial dependence of soil microbial indices was affected by non-intrinsic factors and forest management procedures. The maps show that soil microbial indices and soil properties have spatial variability. The spatial pattern of microbial indices was correlated to organic carbon and nitrogen.展开更多
Geostatistics provides a coherent framework for spatial prediction and uncertainty assessment, whereby spatial dependence, as quantified by variograms, is utilized for best linear unbiased estimation of a regionalized...Geostatistics provides a coherent framework for spatial prediction and uncertainty assessment, whereby spatial dependence, as quantified by variograms, is utilized for best linear unbiased estimation of a regionalized variable at unsampled locations. Geostatistics for prediction of continuous regionalized variables is reviewed, with key methods underlying the derivation of major variants of uni-variate Kriging described in an easy-to-follow manner. This paper will contribute to demystification and, hence, popularization of geostatistics in geoinformatics communities.展开更多
The research of the spatial heterogeneity of PM2.5 concentration in an area, is of great significance for understanding its regional spatial distribution structure, exploring the transmission relationship between regi...The research of the spatial heterogeneity of PM2.5 concentration in an area, is of great significance for understanding its regional spatial distribution structure, exploring the transmission relationship between regions, in order to formulate joint prevention and control measures within the entire area. Based on the daily monitoring data of PM2.5 concentration in the Central Plains Economic Region in 2019, this paper utilizes cluster analysis to divide the regional PM2.5 concentration into 5 classes, builds their spatial semi-variogram model, and then utilizes interpolation analysis method to study the regional overall distribution characteristics and transmission law. The results show that the PM2.5 concentration in the Central Plains Economic Region has a medium or higher spatial autocorrelation. The critical value of the overall PM2.5 concentration in the area is 150 μg/m3, as the overall PM2.5 concentration less than the value, the PM2.5 in a region mainly comes from local emissions, as the overall PM2.5 concentration higher than the value, the influence of spatial structure on the distribution of PM2.5 concentration is gradually obvious. PM2.5 has a certain degree of spatial transmission, which mainly includes two routes as Puyang-Xingtai and Puyang-Zhengzhou, and the transmission intensity of the former is greater than the latter.展开更多
基金Under the auspices of National Natural Science Foundation of China(No.41071267,41001254)Natural Science Foundation of Fujian Province(No.2012I0005,2012J01167)
文摘Most evaluation of the consistency of multisensor images have focused on Normalized Difference Vegetation Index(NDVI) products for natural landscapes, often neglecting less vegetated urban landscapes. This gap has been filled through quantifying and evaluating spatial heterogeneity of urban and natural landscapes from QuickBird, Satellite pour l'observation de la Terre(SPOT), Advanced Spaceborne Thermal Emission and Reflection Radiometer(ASTER) and Landsat Thematic Mapper(TM) images with variogram analysis. Instead of a logarithmic relationship with pixel size observed in the corresponding aggregated images, the spatial variability decayed and the spatial structures decomposed more slowly and complexly with spatial resolution for real multisensor images. As the spatial resolution increased, the proportion of spatial variability of the smaller spatial structure decreased quickly and only a larger spatial structure was observed at very coarse scales. Compared with visible band, greater spatial variability was observed in near infrared band for both densely and less densely vegetated landscapes. The influence of image size on spatial heterogeneity was highly dependent on whether the empirical semivariogram reached its sill within the original image size. When the empirical semivariogram did not reach its sill at the original observation scale, spatial variability and mean characteristic length scale would increase with image size; otherwise they might decrease. This study could provide new insights into the knowledge of spatial heterogeneity in real multisensor images with consideration of their nominal spatial resolution, image size and spectral bands.
基金supported by the Natural Science Foundation for Youths of Tibet Autonomous Region of China (Grant No. XZ-20080383)
文摘This study is based on meteorological observation data collected at 38 weather stations on the Tibetan Plateau over several decades. Daily reference crop evapotranspiration （ETo） was calculated with the FAO-56 standard Penman-Monteith formula. A test of normality was performed with Statistica 6.0 software, isotropic and anisotropic semi-variogram analysis was conducted with the GS＋ （geostatistics for the environmental sciences） system for Windows 7.0, and the characteristics of spatial variation of daily ETo were obtained. The following results can be obtained Daily ETo for different periods on the Tibetan Plateau are distributed normally; Except for daily ETo in the E-W （east-west） direction in the summer, which showed a slight negative correlation with distance change, the Moran＇s indexes of daily ETo for different periods in all directions on the Tibetan Plateau within a 100-km distance were positive, demonstrating a positive correlation with distance change; Variograms of daily ETo in June, the dry season, the wet season, as well as annual average daily ETo fit well with the Gaussian model; A variogram of daily ETo in December fit well with the exponential model; Variograms of daily ETo for the four seasons fit well with the linear With sill model.
文摘A structural analysis of K of an aquifer system in the study area is presented, and the main direction and degree of the variability of K are found by using the unstationary regionalized variable theory of geostatistics. Optimal estimation of K has been made by universal kriging method (U K M ). Both spatial variability distribution map and division map of K are given.
基金the Iran National Science Foundation (INFS) which provided financial support through various steps of our research
文摘Microbial indices and their spatial patterns are strongly affected by environmental factors. Spatial variability of soil properties is one of the most important causes of variability in soil microbial indices. This research was conducted in the Caspian forest to assess spatial variabilities and frequency distributions of microbial properties.Ninety soil samples were taken using a grid sampling design 40 9 40 m. Microbial indices, organic carbon,nitrogen and pH were determined. Soil variable distributions showed that microbial indices had abnormal distributions. Logarithmic transformation produced normal distribution. Spatial continuity using geostatistical(variogram) was studied and maps obtained by point kriging.The variograms revealed the presence of spatial autocorrelation. The results indicate that spatial dependence of soil microbial indices was affected by non-intrinsic factors and forest management procedures. The maps show that soil microbial indices and soil properties have spatial variability. The spatial pattern of microbial indices was correlated to organic carbon and nitrogen.
基金the National 973 Program of China (No. 2007CB714402-5).
文摘Geostatistics provides a coherent framework for spatial prediction and uncertainty assessment, whereby spatial dependence, as quantified by variograms, is utilized for best linear unbiased estimation of a regionalized variable at unsampled locations. Geostatistics for prediction of continuous regionalized variables is reviewed, with key methods underlying the derivation of major variants of uni-variate Kriging described in an easy-to-follow manner. This paper will contribute to demystification and, hence, popularization of geostatistics in geoinformatics communities.
文摘The research of the spatial heterogeneity of PM2.5 concentration in an area, is of great significance for understanding its regional spatial distribution structure, exploring the transmission relationship between regions, in order to formulate joint prevention and control measures within the entire area. Based on the daily monitoring data of PM2.5 concentration in the Central Plains Economic Region in 2019, this paper utilizes cluster analysis to divide the regional PM2.5 concentration into 5 classes, builds their spatial semi-variogram model, and then utilizes interpolation analysis method to study the regional overall distribution characteristics and transmission law. The results show that the PM2.5 concentration in the Central Plains Economic Region has a medium or higher spatial autocorrelation. The critical value of the overall PM2.5 concentration in the area is 150 μg/m3, as the overall PM2.5 concentration less than the value, the PM2.5 in a region mainly comes from local emissions, as the overall PM2.5 concentration higher than the value, the influence of spatial structure on the distribution of PM2.5 concentration is gradually obvious. PM2.5 has a certain degree of spatial transmission, which mainly includes two routes as Puyang-Xingtai and Puyang-Zhengzhou, and the transmission intensity of the former is greater than the latter.
