A micro-electromechanical system(MEMS)scanning mirror accelerates the raster scanning of optical-resolution photoacoustic microscopy(OR-PAM).However,the nonlinear tilt angular-voltage characteristic of a MEMS mirror i...A micro-electromechanical system(MEMS)scanning mirror accelerates the raster scanning of optical-resolution photoacoustic microscopy(OR-PAM).However,the nonlinear tilt angular-voltage characteristic of a MEMS mirror introduces distortion into the maximum back-projection image.Moreover,the size of the airy disk,ultrasonic sensor properties,and thermal effects decrease the resolution.Thus,in this study,we proposed a spatial weight matrix(SWM)with a dimensionality reduction for image reconstruction.The three-layer SWM contains the invariable information of the system,which includes a spatial dependent distortion correction and 3D deconvolution.We employed an ordinal-valued Markov random field and the Harris Stephen algorithm,as well as a modified delay-and-sum method during a time reversal.The results from the experiments and a quantitative analysis demonstrate that images can be effectively reconstructed using an SWM;this is also true for severely distorted images.The index of the mutual information between the reference images and registered images was 70.33 times higher than the initial index,on average.Moreover,the peak signal-to-noise ratio was increased by 17.08%after 3D deconvolution.This accomplishment offers a practical approach to image reconstruction and a promising method to achieve a real-time distortion correction for MEMS-based OR-PAM.展开更多
Image classification and unsupervised image segmentation can be achieved using the Gaussian mixture model.Although the Gaussian mixture model enhances the flexibility of image segmentation,it does not reflect spatial ...Image classification and unsupervised image segmentation can be achieved using the Gaussian mixture model.Although the Gaussian mixture model enhances the flexibility of image segmentation,it does not reflect spatial information and is sensitive to the segmentation parameter.In this study,we first present an efficient algorithm that incorporates spatial information into the Gaussian mixture model(GMM)without parameter estimation.The proposed model highlights the residual region with considerable information and constructs color saliency.Second,we incorporate the content-based color saliency as spatial information in the Gaussian mixture model.The segmentation is performed by clustering each pixel into an appropriate component according to the expectation maximization and maximum criteria.Finally,the random color histogram assigns a unique color to each cluster and creates an attractive color by default for segmentation.A random color histogram serves as an effective tool for data visualization and is instrumental in the creation of generative art,facilitating both analytical and aesthetic objectives.For experiments,we have used the Berkeley segmentation dataset BSDS-500 and Microsoft Research in Cambridge dataset.In the study,the proposed model showcases notable advancements in unsupervised image segmentation,with probabilistic rand index(PRI)values reaching 0.80,BDE scores as low as 12.25 and 12.02,compactness variations at 0.59 and 0.7,and variation of information(VI)reduced to 2.0 and 1.49 for the BSDS-500 and MSRC datasets,respectively,outperforming current leading-edge methods and yielding more precise segmentations.展开更多
Snow depth is a general input variable in many models of agriculture,hydrology,climate and ecology.This study makes use of observational data of snow depth and explanatory variables to compare the accuracy and effect ...Snow depth is a general input variable in many models of agriculture,hydrology,climate and ecology.This study makes use of observational data of snow depth and explanatory variables to compare the accuracy and effect of geographically weighted regression kriging(GWRK)and regression kriging(RK)in a spatial interpolation of regional snow depth.The auxiliary variables are analyzed using correlation coefficients and the variance inflation factor(VIF).Three variables,Height,topographic ruggedness index(TRI),and land surface temperature(LST),are used as explanatory variables to establish a regression model for snow depth.The estimated spatial distribution of snow depth in the Bayanbulak Basin of the Tianshan Mountains in China with a spatial resolution of 1 km is obtained.The results indicate that 1)the result of GWRK's accuracy is slightly higher than that of RK(R^2=0.55 vs.R^2=0.50,RMSE(root mean square error)=0.102 m vs.RMSE=0.077 m);2)for the subareas,GWRK and RK exhibit similar estimation results of snow depth.Areas in the Bayanbulak Basin with a snow depth greater than 0.15m are mainly distributed in an elevation range of 2632.00–3269.00 m and the snow in this area comprises 45.00–46.00% of the total amount of snow in this basin.However,the GWRK resulted in more detailed information on snow depth distribution than the RK.The final conclusion is that GWRK is better suited for estimating regional snow depth distribution.展开更多
Cell migration plays a significant role in physiological and pathological processes.Understanding the characteristics of cell movement is crucial for comprehending biological processes such as cell functionality,cell ...Cell migration plays a significant role in physiological and pathological processes.Understanding the characteristics of cell movement is crucial for comprehending biological processes such as cell functionality,cell migration,and cell–cell interactions.One of the fundamental characteristics of cell movement is the specific distribution of cell speed,containing valuable information that still requires comprehensive understanding.This article investigates the distribution of mean velocities along cell trajectories,with a focus on optimizing the efficiency of cell food search in the context of the entire colony.We confirm that the specific velocity distribution in the experiments corresponds to an optimal search efficiency when spatial weighting is considered.The simulation results indicate that the distribution of average velocity does not align with the optimal search efficiency when employing average spatial weighting.However,when considering the distribution of central spatial weighting,the specific velocity distribution in the experiment is shown to correspond to the optimal search efficiency.Our simulations reveal that for any given distribution of average velocity,a specific central spatial weighting can be identified among the possible central spatial weighting that aligns with the optimal search strategy.Additionally,our work presents a method for determining the spatial weights embedded in the velocity distribution of cell movement.Our results have provided new avenues for further investigation of significant topics,such as relationship between cell behavior and environmental conditions throughout their evolutionary history,and how cells achieve collective cooperation through cell-cell communication.展开更多
Compared with traditional gravity measurement data,gravity gradient tensor data contain more high frequency information,which can be used to understand the earth's interior structure,mineral resources distribution...Compared with traditional gravity measurement data,gravity gradient tensor data contain more high frequency information,which can be used to understand the earth's interior structure,mineral resources distribution etc. In this study,the authors present an algorithm for inverting gravity gradiometer data to recover the three-dimensional( 3-D) distributions of density. Spatial gradient weighting was used to constrain the extent of the body horizontally and vertically. A more accurate inversion result can be obtained by combining the prior information into the weighting function and applying it in inversion. This method was tested on synthetic models and the inverted results showed that the resolution was significantly improved. Moreover,the algorithm was applied to the inversion of empirical data from a salt dome located in Texas,USA,which demonstrated the validity of the proposed method.展开更多
Satellite-based precipitation products have been widely used to estimate precipitation, especially over regions with sparse rain gauge networks. However, the low spatial resolution of these products has limited their ...Satellite-based precipitation products have been widely used to estimate precipitation, especially over regions with sparse rain gauge networks. However, the low spatial resolution of these products has limited their application in localized regions and watersheds.This study investigated a spatial downscaling approach, Geographically Weighted Regression Kriging(GWRK), to downscale the Tropical Rainfall Measuring Mission(TRMM) 3 B43 Version 7 over the Lancang River Basin(LRB) for 2001–2015. Downscaling was performed based on the relationships between the TRMM precipitation and the Normalized Difference Vegetation Index(NDVI), the Land Surface Temperature(LST), and the Digital Elevation Model(DEM). Geographical ratio analysis(GRA) was used to calibrate the annual downscaled precipitation data, and the monthly fractions derived from the original TRMM data were used to disaggregate annual downscaled and calibrated precipitation to monthly precipitation at 1 km resolution. The final downscaled precipitation datasets were validated against station-based observed precipitation in 2001–2015. Results showed that: 1) The TRMM 3 B43 precipitation was highly accurate with slight overestimation at the basin scale(i.e., CC(correlation coefficient) = 0.91, Bias = 13.3%). Spatially, the accuracies of the upstream and downstream regions were higher than that of the midstream region. 2) The annual downscaled TRMM precipitation data at 1 km spatial resolution obtained by GWRK effectively captured the high spatial variability of precipitation over the LRB. 3) The annual downscaled TRMM precipitation with GRA calibration gave better accuracy compared with the original TRMM dataset. 4) The final downscaled and calibrated precipitation had significantly improved spatial resolution, and agreed well with data from the validated rain gauge stations, i.e., CC = 0.75, RMSE(root mean square error) = 182 mm, MAE(mean absolute error) = 142 mm, and Bias = 0.78%for annual precipitation and CC = 0.95, RMSE = 25 mm, MAE = 16 mm, and Bias = 0.67% for monthly precipitation.展开更多
Panel data combine cross-section data and time series data. If the cross-section is locations, there is a need to check the correlation among locations. ρ and λ are parameters in generalized spatial model to cover e...Panel data combine cross-section data and time series data. If the cross-section is locations, there is a need to check the correlation among locations. ρ and λ are parameters in generalized spatial model to cover effect of correlation between locations. Value of ρ or λ will influence the goodness of fit model, so it is important to make parameter estimation. The effect of another location is covered by making contiguity matrix until it gets spatial weighted matrix (W). There are some types of W—uniform W, binary W, kernel Gaussian W and some W from real case of economics condition or transportation condition from locations. This study is aimed to compare uniform W and kernel Gaussian W in spatial panel data model using RMSE value. The result of analysis showed that uniform weight had RMSE value less than kernel Gaussian model. Uniform W had stabil value for all the combinations.展开更多
Spatial spillover effects,either positive or negative,of transport infrastructure,highways/expressways,etc.,on regional economic growth are proposed.Using the panel data for 11 cities of Zhejiang province from 1994 to...Spatial spillover effects,either positive or negative,of transport infrastructure,highways/expressways,etc.,on regional economic growth are proposed.Using the panel data for 11 cities of Zhejiang province from 1994 to 2003,a spatial production function is applied to examine the spatial spillovers which can be generated as a positive output spillover from the transport infrastructure between neighboring cities.Some spatial weighted matrices are adopted to define different neighboring cities to measure how easily factors or economic activities can migrate between regions.The estimation results show that the output elasticity of the highway infrastructure in 11 cities are all insignificant at a 5% significance level;hence,highway infrastructure in a region cannot explain the same region's economic growth.On the other hand,the highway infrastructure of other contiguous regions has positive spillover effects on a same region's economic growth.展开更多
Using GIS spatial statistical analysis method, with ArcGIS software as an analysis tool, taking the diseased maize in Hedong District of Linyi City as the study object, the distribution characteristic of the diseased ...Using GIS spatial statistical analysis method, with ArcGIS software as an analysis tool, taking the diseased maize in Hedong District of Linyi City as the study object, the distribution characteristic of the diseased crops this time in spatial location was analyzed. The results showed that the diseased crops mainly dis- tributed along with river tributaries and downstream of main rivers. The correlation between adjacent diseased plots was little, so the infection of pests and diseases were excluded, and the major reason of incidence might be river pollution.展开更多
We use the directional slacks-based measure of efficiency and inverse distance weighting method to analyze the spatial pattern evolution of the industrial green total factor productivity of 108 cities in the Yangtze R...We use the directional slacks-based measure of efficiency and inverse distance weighting method to analyze the spatial pattern evolution of the industrial green total factor productivity of 108 cities in the Yangtze River Economic Belt in 2003–2013.Results show that both the subprime mortgage crisis and ‘the new normal' had significant negative effects on productivity growth,leading to the different spatial patterns between 2003–2008 and 2009–2013.Before 2008,green poles had gathered around some capital cities and formed a tripartite pattern,which was a typical core-periphery pattern.Due to a combination of the polarization and the diffusion effects,capital cities became the growth poles and ‘core' regions,while surrounding areas became the ‘periphery'.This was mainly caused by the innate advantage of capital cities and ‘the rise of central China' strategy.After 2008,the tripartite pattern changed to a multi-poles pattern where green poles continuously and densely spread in the midstream and downstream areas.This is due to the regional difference in the leading effect of green poles.The leading effect of green poles in midstream and downstream areas has changed from polarization to diffusion,while the polarization effect still leads in the upstream area.展开更多
Nowadays,the evaluation of coal deposits becomes crucial,due to many uncontrollable factors,which affect the energy sector.A comparative evaluation of coal deposits is essential for their hierarchical classification r...Nowadays,the evaluation of coal deposits becomes crucial,due to many uncontrollable factors,which affect the energy sector.A comparative evaluation of coal deposits is essential for their hierarchical classification regarding their sustainable exploitation,when compared to other coal deposits or competitive fuels,which may be used as alternative solutions for electricity generation.In this paper,a method for spatial analysis and evaluation of a lignite deposit is proposed,by creating four spatial key indicators via GIS analysis,which are then aggregated by applying a weighted linear combination.The analytical hierarchy process is applied to estimate the relative weights of the indicators,in order to perform a weighted cartographic overlay.Through the synthesis of the indicators,an overall,total spatial quality indicator is calculated.The weighted analysis was shown to be more effective compared to the unweighted one,because it can provide more reliable results regarding the exploitation of the examined lignite deposit.The implementation of GIS-based analytical hierarchy process in spatial analysis and evaluation of lignite deposits,in terms of sustainable exploitation,demonstrates that this method can be extensively applied for evaluating the economic potential of mineral deposits.展开更多
In this study, we developed an energy security evaluation model(ESEM) from three dimensions, energy supply-transport security, safety of energy utilization, and stability of political-socioeconomic environment, based ...In this study, we developed an energy security evaluation model(ESEM) from three dimensions, energy supply-transport security, safety of energy utilization, and stability of political-socioeconomic environment, based on the integrated application of subjective and objective weight allocation technique. Then the spatial-temporal evolution of global energy security pattern and its driving mechanism was analyzed with the method above, and the results are shown as follows:(1) since the 1990 s, the spatial patterns of global energy security have shown a deteriorating trend, with the growth of countries in at-risk type and relatively at-risk type.(2) The spatial distribution of countries with secure energy system shows a strong stability, and these countries are concentrated persistently in Western Europe and North America. The spatial evolution of countries with relatively secure energy system also presents a strong stability, which are mainly distributed in the periphery of the secure ones, namely Central and Southern Europe, South America and Eurasia, while countries with general energy system are mainly distributed in Asia, Africa and Southern Europe, and the spatial-temporal evolution of this type is the main cause for the deterioration of world energy security pattern. Countries with at-risk and relatively at-risk energy system are mainly concentrated in Africa, Asia, the Middle East and Eurasia, rendering spatial extension to the east and south.(3) In the past 20 years, the mechanism for world’s energy security pattern formation gradually transforms from the ‘unitary dimension dominated’ to the ‘binary dimension-dominated’, and the main factors influencing the global energy security pattern become more diverse.(4) In the pattern of world’s energy security, China’s performance on energy security has been the global average since the 1990 s, which shows a decreasing trend in safety of energy utilization dimension. Findings in this study can provide a reference for the government in terms of formulating strategic responses and policy options.展开更多
As an important component of China’ transportation systems, for a long time, the insufficient performance of transport in QinghaiTibet Plateau(QTP) was a bottleneck restricting the economic growth and social developm...As an important component of China’ transportation systems, for a long time, the insufficient performance of transport in QinghaiTibet Plateau(QTP) was a bottleneck restricting the economic growth and social development in this area. Nevertheless, the implementation of the western development strategy has accelerated the preliminary construction of comprehensive transport network since 2000. Due to the large area and significant geographical heterogeneity, there is a growing need to understand the relationship between transportation and economic development based on the perspective of spatial difference. By using GIS-based raster analysis and Geographically Weighted Regression(GWR) model, we investigated the spatial-temporal distribution of highway, railway and airport accessibility, respectively, and estimated the correlation and heterogeneity between transport accessibility and the level of economic development. Results revealed that:(1) Transport accessibility in the QTP improved by 53.38% in the past 15 years, which is specifically embodied in the improvement of both highway and railway.(2) Accessibility presented prominent differentiation in the space, increasing from west to east and reducing with the rise of elevation, specifically, the best accessibility area of the highway is below 4000 m above sea level, while the area with an altitude of over 4000 m has the lowest aviation time cost.(3) In general, the long weighted average time cost to critical transport facilities posed significantly negative effect on county economic growth in QTP, more positively, the adverse effect gradually weakened over time.(4) Obvious heterogeneity exists at the influence of different transport accessibility factors on the level of economic development, reflecting both in the horizontal space and altitudinal belt. Therefore, region-specific policies should be addressed for the sustainable development of transport facilities as well as economy in the west mountain areas.展开更多
Rainfall is a significant portion of hydrologic data. Rainfall records, however, are often incomplete due to several factors. In this study, the inverse distance weighting (IDW) method integrated with GIS is used to e...Rainfall is a significant portion of hydrologic data. Rainfall records, however, are often incomplete due to several factors. In this study, the inverse distance weighting (IDW) method integrated with GIS is used to estimate the rainfall distribution in Duhok Governorate. A total of 25 rain fall stations and rainfall data between 2000 and 2010 were used, where 6 rainfall stations were used for cross-validation. In addition, the relationship between interpolation accuracy and two critical parameters of IDW (Power α value, and a radius of influence) was evaluated. Also, the rainfall distribution of Duhok Governorate was classified. As an output of this study and in most cases, the optimal parameters for IDW in interpolating rainfall data must have a radius of influence up to (15 - 60 km). However, the optimal α values varied between 1 and 5. Based on the results of this study, we concluded that the IDW is an appropriate method of spatial interpolation to predict the probable rainfall data in Duhok Governorate using α = 1 and search radius = 105 km for all the 25 rainfall stations.展开更多
<div style="text-align:justify;"> Precipitation is an important part of the global hydrological cycle. The large- scale, high-precision continuous precipitation data obtained by satellite remote sensin...<div style="text-align:justify;"> Precipitation is an important part of the global hydrological cycle. The large- scale, high-precision continuous precipitation data obtained by satellite remote sensing detection technology has become an important source of spatial precipitation data. However, because the spatial resolution of remote sensing precipitation data is still low, it is difficult to meet the needs of hydrological research, which restricts their application in drought and flood analysis, hydrological simulation, etc. In response to this problem, this paper takes the Beijing-Tianjin-Hebei region as the research area, downscaling the TRMM data and the GPM data space of the continuation plan, and increasing the spatial resolution of the data to 1 km. Compared with the original data, spatial downscaling data not only greatly improves the spatial resolution, but also increases the accuracy of the data, which has better applicability. </div>展开更多
This paper presents an approach based on field data to model the spatial distribution of the site productivity index （SPI） of the diverse forest types in Jalisco, Mexico and the response in SPI to site and cli-matic...This paper presents an approach based on field data to model the spatial distribution of the site productivity index （SPI） of the diverse forest types in Jalisco, Mexico and the response in SPI to site and cli-matic conditions. A linear regression model was constructed to test the hypothesis that site and climate variables can be used to predict the SPI of the major forest types in Jalisco. SPI varied significantly with topog-raphy （elevation, aspect and slope）, soil attributes （pH, sand and silt）, climate （temperature and precipitation zones） and forest type. The most important variable in the model was forest type, which accounted for 35% of the variability in SPI. Temperature and precipitation accounted for 8 to 9% of the variability in SPI while the soil attributes accounted for less than 4% of the variability observed in SPI. No significant differences were detected between the observed and predicted SPI for the individual forest types. The linear regression model was used to develop maps of the spatial variability in predicted SPI for the individual forest types in the state. The spatial site productivity models developed in this study provides a basis for understanding the complex relationship that exists between forest productivity and site and climatic conditions in the state. Findings of this study will assist resource managers in making cost-effective decisions about the management of individual forest types in the state of Jalisco, Mexico.展开更多
基金supported by National Natural Science Foundation of China,Nos.61822505,11774101,61627827Science and Technology Planning Project of Guangdong Province,No.2015B020233016+2 种基金China Postdoctoral Science Foundation,No.2019 M652943Natural Science Foundation of Guangdong Province,No.2019A1515011399Guangzhou Science and Technology Program key projects,Nos.2019050001.
文摘A micro-electromechanical system(MEMS)scanning mirror accelerates the raster scanning of optical-resolution photoacoustic microscopy(OR-PAM).However,the nonlinear tilt angular-voltage characteristic of a MEMS mirror introduces distortion into the maximum back-projection image.Moreover,the size of the airy disk,ultrasonic sensor properties,and thermal effects decrease the resolution.Thus,in this study,we proposed a spatial weight matrix(SWM)with a dimensionality reduction for image reconstruction.The three-layer SWM contains the invariable information of the system,which includes a spatial dependent distortion correction and 3D deconvolution.We employed an ordinal-valued Markov random field and the Harris Stephen algorithm,as well as a modified delay-and-sum method during a time reversal.The results from the experiments and a quantitative analysis demonstrate that images can be effectively reconstructed using an SWM;this is also true for severely distorted images.The index of the mutual information between the reference images and registered images was 70.33 times higher than the initial index,on average.Moreover,the peak signal-to-noise ratio was increased by 17.08%after 3D deconvolution.This accomplishment offers a practical approach to image reconstruction and a promising method to achieve a real-time distortion correction for MEMS-based OR-PAM.
基金supported by the MOE(Ministry of Education of China)Project of Humanities and Social Sciences(23YJAZH169)the Hubei Provincial Department of Education Outstanding Youth Scientific Innovation Team Support Foundation(T2020017)Henan Foreign Experts Project No.HNGD2023027.
文摘Image classification and unsupervised image segmentation can be achieved using the Gaussian mixture model.Although the Gaussian mixture model enhances the flexibility of image segmentation,it does not reflect spatial information and is sensitive to the segmentation parameter.In this study,we first present an efficient algorithm that incorporates spatial information into the Gaussian mixture model(GMM)without parameter estimation.The proposed model highlights the residual region with considerable information and constructs color saliency.Second,we incorporate the content-based color saliency as spatial information in the Gaussian mixture model.The segmentation is performed by clustering each pixel into an appropriate component according to the expectation maximization and maximum criteria.Finally,the random color histogram assigns a unique color to each cluster and creates an attractive color by default for segmentation.A random color histogram serves as an effective tool for data visualization and is instrumental in the creation of generative art,facilitating both analytical and aesthetic objectives.For experiments,we have used the Berkeley segmentation dataset BSDS-500 and Microsoft Research in Cambridge dataset.In the study,the proposed model showcases notable advancements in unsupervised image segmentation,with probabilistic rand index(PRI)values reaching 0.80,BDE scores as low as 12.25 and 12.02,compactness variations at 0.59 and 0.7,and variation of information(VI)reduced to 2.0 and 1.49 for the BSDS-500 and MSRC datasets,respectively,outperforming current leading-edge methods and yielding more precise segmentations.
基金supported by Projects of International Cooperation and Exchanges NSFC (grant: 41361140361)the Special fund project of Chinese Academy of Sciences (grant: Y371164001)the key deployment project of Chinese Academy of Sciences (Grant No. KZZD-EW-12-2, KZZD-EW12-3)
文摘Snow depth is a general input variable in many models of agriculture,hydrology,climate and ecology.This study makes use of observational data of snow depth and explanatory variables to compare the accuracy and effect of geographically weighted regression kriging(GWRK)and regression kriging(RK)in a spatial interpolation of regional snow depth.The auxiliary variables are analyzed using correlation coefficients and the variance inflation factor(VIF).Three variables,Height,topographic ruggedness index(TRI),and land surface temperature(LST),are used as explanatory variables to establish a regression model for snow depth.The estimated spatial distribution of snow depth in the Bayanbulak Basin of the Tianshan Mountains in China with a spatial resolution of 1 km is obtained.The results indicate that 1)the result of GWRK's accuracy is slightly higher than that of RK(R^2=0.55 vs.R^2=0.50,RMSE(root mean square error)=0.102 m vs.RMSE=0.077 m);2)for the subareas,GWRK and RK exhibit similar estimation results of snow depth.Areas in the Bayanbulak Basin with a snow depth greater than 0.15m are mainly distributed in an elevation range of 2632.00–3269.00 m and the snow in this area comprises 45.00–46.00% of the total amount of snow in this basin.However,the GWRK resulted in more detailed information on snow depth distribution than the RK.The final conclusion is that GWRK is better suited for estimating regional snow depth distribution.
基金Project supported by the National Natural Science Foundation of China(Grant No.31971183).
文摘Cell migration plays a significant role in physiological and pathological processes.Understanding the characteristics of cell movement is crucial for comprehending biological processes such as cell functionality,cell migration,and cell–cell interactions.One of the fundamental characteristics of cell movement is the specific distribution of cell speed,containing valuable information that still requires comprehensive understanding.This article investigates the distribution of mean velocities along cell trajectories,with a focus on optimizing the efficiency of cell food search in the context of the entire colony.We confirm that the specific velocity distribution in the experiments corresponds to an optimal search efficiency when spatial weighting is considered.The simulation results indicate that the distribution of average velocity does not align with the optimal search efficiency when employing average spatial weighting.However,when considering the distribution of central spatial weighting,the specific velocity distribution in the experiment is shown to correspond to the optimal search efficiency.Our simulations reveal that for any given distribution of average velocity,a specific central spatial weighting can be identified among the possible central spatial weighting that aligns with the optimal search strategy.Additionally,our work presents a method for determining the spatial weights embedded in the velocity distribution of cell movement.Our results have provided new avenues for further investigation of significant topics,such as relationship between cell behavior and environmental conditions throughout their evolutionary history,and how cells achieve collective cooperation through cell-cell communication.
基金Supported by Project of Natural Science Fund of Jilin Province(No.20180101312JC)
文摘Compared with traditional gravity measurement data,gravity gradient tensor data contain more high frequency information,which can be used to understand the earth's interior structure,mineral resources distribution etc. In this study,the authors present an algorithm for inverting gravity gradiometer data to recover the three-dimensional( 3-D) distributions of density. Spatial gradient weighting was used to constrain the extent of the body horizontally and vertically. A more accurate inversion result can be obtained by combining the prior information into the weighting function and applying it in inversion. This method was tested on synthetic models and the inverted results showed that the resolution was significantly improved. Moreover,the algorithm was applied to the inversion of empirical data from a salt dome located in Texas,USA,which demonstrated the validity of the proposed method.
基金Under the auspices of the National Natural Science Foundation of China(No.41661099)the National Key Research and Development Program of China(No.Grant 2016YFA0601601)
文摘Satellite-based precipitation products have been widely used to estimate precipitation, especially over regions with sparse rain gauge networks. However, the low spatial resolution of these products has limited their application in localized regions and watersheds.This study investigated a spatial downscaling approach, Geographically Weighted Regression Kriging(GWRK), to downscale the Tropical Rainfall Measuring Mission(TRMM) 3 B43 Version 7 over the Lancang River Basin(LRB) for 2001–2015. Downscaling was performed based on the relationships between the TRMM precipitation and the Normalized Difference Vegetation Index(NDVI), the Land Surface Temperature(LST), and the Digital Elevation Model(DEM). Geographical ratio analysis(GRA) was used to calibrate the annual downscaled precipitation data, and the monthly fractions derived from the original TRMM data were used to disaggregate annual downscaled and calibrated precipitation to monthly precipitation at 1 km resolution. The final downscaled precipitation datasets were validated against station-based observed precipitation in 2001–2015. Results showed that: 1) The TRMM 3 B43 precipitation was highly accurate with slight overestimation at the basin scale(i.e., CC(correlation coefficient) = 0.91, Bias = 13.3%). Spatially, the accuracies of the upstream and downstream regions were higher than that of the midstream region. 2) The annual downscaled TRMM precipitation data at 1 km spatial resolution obtained by GWRK effectively captured the high spatial variability of precipitation over the LRB. 3) The annual downscaled TRMM precipitation with GRA calibration gave better accuracy compared with the original TRMM dataset. 4) The final downscaled and calibrated precipitation had significantly improved spatial resolution, and agreed well with data from the validated rain gauge stations, i.e., CC = 0.75, RMSE(root mean square error) = 182 mm, MAE(mean absolute error) = 142 mm, and Bias = 0.78%for annual precipitation and CC = 0.95, RMSE = 25 mm, MAE = 16 mm, and Bias = 0.67% for monthly precipitation.
文摘Panel data combine cross-section data and time series data. If the cross-section is locations, there is a need to check the correlation among locations. ρ and λ are parameters in generalized spatial model to cover effect of correlation between locations. Value of ρ or λ will influence the goodness of fit model, so it is important to make parameter estimation. The effect of another location is covered by making contiguity matrix until it gets spatial weighted matrix (W). There are some types of W—uniform W, binary W, kernel Gaussian W and some W from real case of economics condition or transportation condition from locations. This study is aimed to compare uniform W and kernel Gaussian W in spatial panel data model using RMSE value. The result of analysis showed that uniform weight had RMSE value less than kernel Gaussian model. Uniform W had stabil value for all the combinations.
基金The National Key Technology R&D Program of China during the 11 th Five-Year Plan Period(No.2006BAH02A06)Program for New Century Excellent Talents in China(No.NCET-05-0529)
文摘Spatial spillover effects,either positive or negative,of transport infrastructure,highways/expressways,etc.,on regional economic growth are proposed.Using the panel data for 11 cities of Zhejiang province from 1994 to 2003,a spatial production function is applied to examine the spatial spillovers which can be generated as a positive output spillover from the transport infrastructure between neighboring cities.Some spatial weighted matrices are adopted to define different neighboring cities to measure how easily factors or economic activities can migrate between regions.The estimation results show that the output elasticity of the highway infrastructure in 11 cities are all insignificant at a 5% significance level;hence,highway infrastructure in a region cannot explain the same region's economic growth.On the other hand,the highway infrastructure of other contiguous regions has positive spillover effects on a same region's economic growth.
文摘Using GIS spatial statistical analysis method, with ArcGIS software as an analysis tool, taking the diseased maize in Hedong District of Linyi City as the study object, the distribution characteristic of the diseased crops this time in spatial location was analyzed. The results showed that the diseased crops mainly dis- tributed along with river tributaries and downstream of main rivers. The correlation between adjacent diseased plots was little, so the infection of pests and diseases were excluded, and the major reason of incidence might be river pollution.
基金Under the auspices of the post-funded project of National Social Science Foundation of China(No.16FJL009)
文摘We use the directional slacks-based measure of efficiency and inverse distance weighting method to analyze the spatial pattern evolution of the industrial green total factor productivity of 108 cities in the Yangtze River Economic Belt in 2003–2013.Results show that both the subprime mortgage crisis and ‘the new normal' had significant negative effects on productivity growth,leading to the different spatial patterns between 2003–2008 and 2009–2013.Before 2008,green poles had gathered around some capital cities and formed a tripartite pattern,which was a typical core-periphery pattern.Due to a combination of the polarization and the diffusion effects,capital cities became the growth poles and ‘core' regions,while surrounding areas became the ‘periphery'.This was mainly caused by the innate advantage of capital cities and ‘the rise of central China' strategy.After 2008,the tripartite pattern changed to a multi-poles pattern where green poles continuously and densely spread in the midstream and downstream areas.This is due to the regional difference in the leading effect of green poles.The leading effect of green poles in midstream and downstream areas has changed from polarization to diffusion,while the polarization effect still leads in the upstream area.
文摘Nowadays,the evaluation of coal deposits becomes crucial,due to many uncontrollable factors,which affect the energy sector.A comparative evaluation of coal deposits is essential for their hierarchical classification regarding their sustainable exploitation,when compared to other coal deposits or competitive fuels,which may be used as alternative solutions for electricity generation.In this paper,a method for spatial analysis and evaluation of a lignite deposit is proposed,by creating four spatial key indicators via GIS analysis,which are then aggregated by applying a weighted linear combination.The analytical hierarchy process is applied to estimate the relative weights of the indicators,in order to perform a weighted cartographic overlay.Through the synthesis of the indicators,an overall,total spatial quality indicator is calculated.The weighted analysis was shown to be more effective compared to the unweighted one,because it can provide more reliable results regarding the exploitation of the examined lignite deposit.The implementation of GIS-based analytical hierarchy process in spatial analysis and evaluation of lignite deposits,in terms of sustainable exploitation,demonstrates that this method can be extensively applied for evaluating the economic potential of mineral deposits.
基金National Natural Science Foundation of China,No.41671126,No.41171147Special Funds for Scientific Research Institutes from Science&Technology Department of Fujian Province,No.2016R1032-5
文摘In this study, we developed an energy security evaluation model(ESEM) from three dimensions, energy supply-transport security, safety of energy utilization, and stability of political-socioeconomic environment, based on the integrated application of subjective and objective weight allocation technique. Then the spatial-temporal evolution of global energy security pattern and its driving mechanism was analyzed with the method above, and the results are shown as follows:(1) since the 1990 s, the spatial patterns of global energy security have shown a deteriorating trend, with the growth of countries in at-risk type and relatively at-risk type.(2) The spatial distribution of countries with secure energy system shows a strong stability, and these countries are concentrated persistently in Western Europe and North America. The spatial evolution of countries with relatively secure energy system also presents a strong stability, which are mainly distributed in the periphery of the secure ones, namely Central and Southern Europe, South America and Eurasia, while countries with general energy system are mainly distributed in Asia, Africa and Southern Europe, and the spatial-temporal evolution of this type is the main cause for the deterioration of world energy security pattern. Countries with at-risk and relatively at-risk energy system are mainly concentrated in Africa, Asia, the Middle East and Eurasia, rendering spatial extension to the east and south.(3) In the past 20 years, the mechanism for world’s energy security pattern formation gradually transforms from the ‘unitary dimension dominated’ to the ‘binary dimension-dominated’, and the main factors influencing the global energy security pattern become more diverse.(4) In the pattern of world’s energy security, China’s performance on energy security has been the global average since the 1990 s, which shows a decreasing trend in safety of energy utilization dimension. Findings in this study can provide a reference for the government in terms of formulating strategic responses and policy options.
基金jointly sponsored by Institute of Mountain Hazards and Environment,Research Center of Sichuan County Economy Developmentthe financial support from the National Natural Science Foundation of China(Grants No.41571523,41661144038,41671152)+1 种基金the National Key Technology Research and Development Program of the Ministry of Science and Technology of China(Grant No.2014BAC05B01)the Major Base Planning Projects of Sichuan Social Science(Grants No.SC18EZD050)
文摘As an important component of China’ transportation systems, for a long time, the insufficient performance of transport in QinghaiTibet Plateau(QTP) was a bottleneck restricting the economic growth and social development in this area. Nevertheless, the implementation of the western development strategy has accelerated the preliminary construction of comprehensive transport network since 2000. Due to the large area and significant geographical heterogeneity, there is a growing need to understand the relationship between transportation and economic development based on the perspective of spatial difference. By using GIS-based raster analysis and Geographically Weighted Regression(GWR) model, we investigated the spatial-temporal distribution of highway, railway and airport accessibility, respectively, and estimated the correlation and heterogeneity between transport accessibility and the level of economic development. Results revealed that:(1) Transport accessibility in the QTP improved by 53.38% in the past 15 years, which is specifically embodied in the improvement of both highway and railway.(2) Accessibility presented prominent differentiation in the space, increasing from west to east and reducing with the rise of elevation, specifically, the best accessibility area of the highway is below 4000 m above sea level, while the area with an altitude of over 4000 m has the lowest aviation time cost.(3) In general, the long weighted average time cost to critical transport facilities posed significantly negative effect on county economic growth in QTP, more positively, the adverse effect gradually weakened over time.(4) Obvious heterogeneity exists at the influence of different transport accessibility factors on the level of economic development, reflecting both in the horizontal space and altitudinal belt. Therefore, region-specific policies should be addressed for the sustainable development of transport facilities as well as economy in the west mountain areas.
文摘Rainfall is a significant portion of hydrologic data. Rainfall records, however, are often incomplete due to several factors. In this study, the inverse distance weighting (IDW) method integrated with GIS is used to estimate the rainfall distribution in Duhok Governorate. A total of 25 rain fall stations and rainfall data between 2000 and 2010 were used, where 6 rainfall stations were used for cross-validation. In addition, the relationship between interpolation accuracy and two critical parameters of IDW (Power α value, and a radius of influence) was evaluated. Also, the rainfall distribution of Duhok Governorate was classified. As an output of this study and in most cases, the optimal parameters for IDW in interpolating rainfall data must have a radius of influence up to (15 - 60 km). However, the optimal α values varied between 1 and 5. Based on the results of this study, we concluded that the IDW is an appropriate method of spatial interpolation to predict the probable rainfall data in Duhok Governorate using α = 1 and search radius = 105 km for all the 25 rainfall stations.
文摘<div style="text-align:justify;"> Precipitation is an important part of the global hydrological cycle. The large- scale, high-precision continuous precipitation data obtained by satellite remote sensing detection technology has become an important source of spatial precipitation data. However, because the spatial resolution of remote sensing precipitation data is still low, it is difficult to meet the needs of hydrological research, which restricts their application in drought and flood analysis, hydrological simulation, etc. In response to this problem, this paper takes the Beijing-Tianjin-Hebei region as the research area, downscaling the TRMM data and the GPM data space of the continuation plan, and increasing the spatial resolution of the data to 1 km. Compared with the original data, spatial downscaling data not only greatly improves the spatial resolution, but also increases the accuracy of the data, which has better applicability. </div>
文摘This paper presents an approach based on field data to model the spatial distribution of the site productivity index （SPI） of the diverse forest types in Jalisco, Mexico and the response in SPI to site and cli-matic conditions. A linear regression model was constructed to test the hypothesis that site and climate variables can be used to predict the SPI of the major forest types in Jalisco. SPI varied significantly with topog-raphy （elevation, aspect and slope）, soil attributes （pH, sand and silt）, climate （temperature and precipitation zones） and forest type. The most important variable in the model was forest type, which accounted for 35% of the variability in SPI. Temperature and precipitation accounted for 8 to 9% of the variability in SPI while the soil attributes accounted for less than 4% of the variability observed in SPI. No significant differences were detected between the observed and predicted SPI for the individual forest types. The linear regression model was used to develop maps of the spatial variability in predicted SPI for the individual forest types in the state. The spatial site productivity models developed in this study provides a basis for understanding the complex relationship that exists between forest productivity and site and climatic conditions in the state. Findings of this study will assist resource managers in making cost-effective decisions about the management of individual forest types in the state of Jalisco, Mexico.
