This paper studies the relationship between accessibility and housing prices in Dalian by using an improved geographically weighted regression model and house prices, traffic, remote sensing images, etc. Multi-source ...This paper studies the relationship between accessibility and housing prices in Dalian by using an improved geographically weighted regression model and house prices, traffic, remote sensing images, etc. Multi-source data improves the accuracy of the spatial differentiation that reflects the impact of traffic accessibility on house prices. The results are as follows: first, the average house price is 12 436 yuan(RMB)/m^2, and reveals a declining trend from coastal areas to inland areas. The exception was Guilin Street, which demonstrates a local peak of house prices that decreases from the center of the street to its periphery. Second, the accessibility value is 33 minutes on average, excluding northern and eastern fringe areas, which was over 50 minutes. Third, the significant spatial correlation coefficient between accessibility and house prices is 0.423, and the coefficient increases in the southeastern direction. The strongest impact of accessibility on house prices is in the southeastern coast, and can be seen in the Lehua, Yingke, and Hushan communities, while the weakest impact is in the northwestern fringe, and can be seen in the Yingchengzi, Xixiaomo, and Daheishi community areas.展开更多
Drug use （DU）, particularly injecting drug use （IDU） has been the main route of transmission and spread of Human Immunodeficiency Virus （HIV）/Acquired Immune Deficiency Syndrome （AIDSJ among injecting drug use...Drug use （DU）, particularly injecting drug use （IDU） has been the main route of transmission and spread of Human Immunodeficiency Virus （HIV）/Acquired Immune Deficiency Syndrome （AIDSJ among injecting drug users （IDUs）[1]. Previous studies have proven that needles or cottons sharing during drug injection were major risk factors for HIV/AIDS transmission at the personal level[z4]. Being a social behavioral issue, HIV/AIDS related risk factors should be far beyond the personal level. Therefore, studies on HIV/AIDS related risk factors should focus not only on the individual factors, but also on the association between HIV/AIDS cases and macroscopic-factors, such as economic status, transportation, health care services, etc[1]. The impact of the macroscopic-factors on HIV/AIDS status might be either positive or negative, which are potentially reflected in promoting, delaying or detecting HIV/AIDS epidemics.展开更多
This study used spatial autoregression(SAR)model and geographically weighted regression(GWR)model to model the spatial patterns of farmland density and its temporal change in Gucheng County,Hubei Province,China in 199...This study used spatial autoregression(SAR)model and geographically weighted regression(GWR)model to model the spatial patterns of farmland density and its temporal change in Gucheng County,Hubei Province,China in 1999 and 2009,and discussed the difference between global and local spatial autocorrelations in terms of spatial heterogeneity and non-stationarity.Results showed that strong spatial positive correlations existed in the spatial distributions of farmland density,its temporal change and the driving factors,and the coefficients of spatial autocorrelations decreased as the spatial lag distance increased.SAR models revealed the global spatial relations between dependent and independent variables,while the GWR model showed the spatially varying fitting degree and local weighting coefficients of driving factors and farmland indices(i.e.,farmland density and temporal change).The GWR model has smooth process when constructing the farmland spatial model.The coefficients of GWR model can show the accurate influence degrees of different driving factors on the farmland at different geographical locations.The performance indices of GWR model showed that GWR model produced more accurate simulation results than other models at different times,and the improvement precision of GWR model was obvious.The global and local farmland models used in this study showed different characteristics in the spatial distributions of farmland indices at different scales,which may provide the theoretical basis for farmland protection from the influence of different driving factors.展开更多
Aquatic habitat assessments encompass large and small wadeable streams which vary from many meters wide to ephemeral. Differences in stream sizes within or across watersheds, however, may lead to incompatibility of da...Aquatic habitat assessments encompass large and small wadeable streams which vary from many meters wide to ephemeral. Differences in stream sizes within or across watersheds, however, may lead to incompatibility of data at varying spatial scales. Specifically, issues caused by moving between scales on large and small streams are not typically addressed by many forms of statistical analysis, making the comparison of large (>30 m wetted width) and small stream (<10 m wetted width) habitat assessments difficult. Geographically weighted regression (GWR) may provide avenues for efficiency and needed insight into stream habitat data by addressing issues caused by moving between scales. This study examined the ability of GWR to consistently model stream substrate on both large and small wadeable streams at an equivalent resolution. We performed GWR on two groups of 60 randomly selected substrate patches from large and small streams and used depth measurements to model substrate. Our large and small stream substrate models responded equally well to GWR. Results showed no statistically significant difference between GWR R<sup>2 </sup>values of large and small stream streams. Results also provided a much needed method for comparison of large and small wadeable streams. Our results have merit for aquatic resource managers, because they demonstrate ability to spatially model and compare substrate on large and small streams. Using depth to guide substrate modeling by geographically weighted regression has a variety of applications which may help manage, monitor stream health, and interpret substrate change over time.展开更多
Researchers have been trying to identify the contributory factors behind pedestrian crash occurrences through studies at both microscopic and macroscopic levels.However,built environment-related factors have primarily...Researchers have been trying to identify the contributory factors behind pedestrian crash occurrences through studies at both microscopic and macroscopic levels.However,built environment-related factors have primarily been examined in developed countries,resulting in a limited understanding of the phenomenon in the context of developing countries.Methodologically,these studies mostly used global regression models,which failed to incorporate spatial autocorrelation and spatial heterogeneity.Additionally,some of these studies applied spatial regression models randomly without following a comprehensive logical framework behind their selections.Our study aimed to develop a comprehensive spatial regression modeling framework to examine the relationships between pedestrian crash occurrences and the built environment at the macroscopic level in a megacity,Dhaka,the capital of a developing country:Bangladesh.Using secondary pedestrian crash data,the study applied one global non-spatial model,two global spatial regression models,and two local spatial regression models following a comprehensive spatial regression modeling framework.The factors which significantly contributed to pedestrian crash occurrences in Dhaka were employed person density,mixed and recreational land use density,primary road density,major intersection density,and share of non-motorized modes.Except for the last factor,all the other ones were positively related to pedestrian crash density.Among the five models used in this study,the multiscale geographically weighted regression(MGWR)performed the best as it calibrated each local relationship with a distant spatial scale parameter.The findings and recommendations presented in this study would be useful for reducing pedestrian crashes and choosing the appropriate modeling technique for crash analysis.展开更多
微波遥感是土壤水分监测的重要手段,但微波遥感土壤水分产品的空间分辨率较低,难以满足区域尺度的应用需求。使用地理加权回归模型,以1 km MODIS产品的遥感地表温度(LST)和归一化植被指数(NDVI)作为辅助数据,将空间分辨率为9 km的SMAP...微波遥感是土壤水分监测的重要手段,但微波遥感土壤水分产品的空间分辨率较低,难以满足区域尺度的应用需求。使用地理加权回归模型,以1 km MODIS产品的遥感地表温度(LST)和归一化植被指数(NDVI)作为辅助数据,将空间分辨率为9 km的SMAP被动微波土壤水分数据降尺度为1 km,利用吉林省地面实测土壤水分数据,对降尺度后的SMAP数据进行了精度验证。结果表明,该降尺度方法在吉林省适用性较好,降尺度结果与SMAP数据在空间分布上保持了较高的一致性,小幅度提高了SMAP数据的精度,显著提高了SMAP数据的空间细节和纹理特征。展开更多
文章以河谷城市甘肃省兰州市为例,在测度“三生”空间冲突强度并揭示多尺度分异机制的基础上提出冲突协调策略。结果显示:①“三生”空间格局演化与地域分异显著。生活空间的增加主要源于对生态空间和生产空间的侵占。②兰州市“三生”...文章以河谷城市甘肃省兰州市为例,在测度“三生”空间冲突强度并揭示多尺度分异机制的基础上提出冲突协调策略。结果显示:①“三生”空间格局演化与地域分异显著。生活空间的增加主要源于对生态空间和生产空间的侵占。②兰州市“三生”空间冲突时空演化与地类分异显著。时序上,“三生”空间冲突强度呈持续上升态势,整体处于基本可控级别;空间上,形成了“一心、两翼、多轴带”的空间冲突格局;就地类而言,城镇的生活空间与生产空间冲突水平较高。③兰州市“三生”空间冲突影响因素尺度效应和异质性明显。高程、坡度、地形起伏度等对“三生”空间冲突具有抑制作用;人口密度、人均G D P、夜间灯光指数等因素加剧了区域“三生”空间冲突程度。展开更多
基金Under the auspices of National Natural Science Foundation of China(No.41471140,41771178)Liaoning Province Outstanding Youth Program(No.LJQ2015058)
文摘This paper studies the relationship between accessibility and housing prices in Dalian by using an improved geographically weighted regression model and house prices, traffic, remote sensing images, etc. Multi-source data improves the accuracy of the spatial differentiation that reflects the impact of traffic accessibility on house prices. The results are as follows: first, the average house price is 12 436 yuan(RMB)/m^2, and reveals a declining trend from coastal areas to inland areas. The exception was Guilin Street, which demonstrates a local peak of house prices that decreases from the center of the street to its periphery. Second, the accessibility value is 33 minutes on average, excluding northern and eastern fringe areas, which was over 50 minutes. Third, the significant spatial correlation coefficient between accessibility and house prices is 0.423, and the coefficient increases in the southeastern direction. The strongest impact of accessibility on house prices is in the southeastern coast, and can be seen in the Lehua, Yingke, and Hushan communities, while the weakest impact is in the northwestern fringe, and can be seen in the Yingchengzi, Xixiaomo, and Daheishi community areas.
基金supported by the National Scientific Research Mega-Project under the 12th Five-Year Plan of China(2012ZX10001001)
文摘Drug use （DU）, particularly injecting drug use （IDU） has been the main route of transmission and spread of Human Immunodeficiency Virus （HIV）/Acquired Immune Deficiency Syndrome （AIDSJ among injecting drug users （IDUs）[1]. Previous studies have proven that needles or cottons sharing during drug injection were major risk factors for HIV/AIDS transmission at the personal level[z4]. Being a social behavioral issue, HIV/AIDS related risk factors should be far beyond the personal level. Therefore, studies on HIV/AIDS related risk factors should focus not only on the individual factors, but also on the association between HIV/AIDS cases and macroscopic-factors, such as economic status, transportation, health care services, etc[1]. The impact of the macroscopic-factors on HIV/AIDS status might be either positive or negative, which are potentially reflected in promoting, delaying or detecting HIV/AIDS epidemics.
基金Under the auspices of National Natural Science Foundation of China(No.40601073,41101192,41201571)Fundamental Research Funds for the Central Universities(No.2011PY112,2011QC041,2011QC091)Huazhong Agricultural University Scientific&Technological Self-innovation Foundation(No.2011SC21)
文摘This study used spatial autoregression(SAR)model and geographically weighted regression(GWR)model to model the spatial patterns of farmland density and its temporal change in Gucheng County,Hubei Province,China in 1999 and 2009,and discussed the difference between global and local spatial autocorrelations in terms of spatial heterogeneity and non-stationarity.Results showed that strong spatial positive correlations existed in the spatial distributions of farmland density,its temporal change and the driving factors,and the coefficients of spatial autocorrelations decreased as the spatial lag distance increased.SAR models revealed the global spatial relations between dependent and independent variables,while the GWR model showed the spatially varying fitting degree and local weighting coefficients of driving factors and farmland indices(i.e.,farmland density and temporal change).The GWR model has smooth process when constructing the farmland spatial model.The coefficients of GWR model can show the accurate influence degrees of different driving factors on the farmland at different geographical locations.The performance indices of GWR model showed that GWR model produced more accurate simulation results than other models at different times,and the improvement precision of GWR model was obvious.The global and local farmland models used in this study showed different characteristics in the spatial distributions of farmland indices at different scales,which may provide the theoretical basis for farmland protection from the influence of different driving factors.
文摘Aquatic habitat assessments encompass large and small wadeable streams which vary from many meters wide to ephemeral. Differences in stream sizes within or across watersheds, however, may lead to incompatibility of data at varying spatial scales. Specifically, issues caused by moving between scales on large and small streams are not typically addressed by many forms of statistical analysis, making the comparison of large (>30 m wetted width) and small stream (<10 m wetted width) habitat assessments difficult. Geographically weighted regression (GWR) may provide avenues for efficiency and needed insight into stream habitat data by addressing issues caused by moving between scales. This study examined the ability of GWR to consistently model stream substrate on both large and small wadeable streams at an equivalent resolution. We performed GWR on two groups of 60 randomly selected substrate patches from large and small streams and used depth measurements to model substrate. Our large and small stream substrate models responded equally well to GWR. Results showed no statistically significant difference between GWR R<sup>2 </sup>values of large and small stream streams. Results also provided a much needed method for comparison of large and small wadeable streams. Our results have merit for aquatic resource managers, because they demonstrate ability to spatially model and compare substrate on large and small streams. Using depth to guide substrate modeling by geographically weighted regression has a variety of applications which may help manage, monitor stream health, and interpret substrate change over time.
基金This research is funded by Bangladesh University of Engineering and Technology(BUET).
文摘Researchers have been trying to identify the contributory factors behind pedestrian crash occurrences through studies at both microscopic and macroscopic levels.However,built environment-related factors have primarily been examined in developed countries,resulting in a limited understanding of the phenomenon in the context of developing countries.Methodologically,these studies mostly used global regression models,which failed to incorporate spatial autocorrelation and spatial heterogeneity.Additionally,some of these studies applied spatial regression models randomly without following a comprehensive logical framework behind their selections.Our study aimed to develop a comprehensive spatial regression modeling framework to examine the relationships between pedestrian crash occurrences and the built environment at the macroscopic level in a megacity,Dhaka,the capital of a developing country:Bangladesh.Using secondary pedestrian crash data,the study applied one global non-spatial model,two global spatial regression models,and two local spatial regression models following a comprehensive spatial regression modeling framework.The factors which significantly contributed to pedestrian crash occurrences in Dhaka were employed person density,mixed and recreational land use density,primary road density,major intersection density,and share of non-motorized modes.Except for the last factor,all the other ones were positively related to pedestrian crash density.Among the five models used in this study,the multiscale geographically weighted regression(MGWR)performed the best as it calibrated each local relationship with a distant spatial scale parameter.The findings and recommendations presented in this study would be useful for reducing pedestrian crashes and choosing the appropriate modeling technique for crash analysis.
文摘微波遥感是土壤水分监测的重要手段,但微波遥感土壤水分产品的空间分辨率较低,难以满足区域尺度的应用需求。使用地理加权回归模型,以1 km MODIS产品的遥感地表温度(LST)和归一化植被指数(NDVI)作为辅助数据,将空间分辨率为9 km的SMAP被动微波土壤水分数据降尺度为1 km,利用吉林省地面实测土壤水分数据,对降尺度后的SMAP数据进行了精度验证。结果表明,该降尺度方法在吉林省适用性较好,降尺度结果与SMAP数据在空间分布上保持了较高的一致性,小幅度提高了SMAP数据的精度,显著提高了SMAP数据的空间细节和纹理特征。
文摘文章以河谷城市甘肃省兰州市为例,在测度“三生”空间冲突强度并揭示多尺度分异机制的基础上提出冲突协调策略。结果显示:①“三生”空间格局演化与地域分异显著。生活空间的增加主要源于对生态空间和生产空间的侵占。②兰州市“三生”空间冲突时空演化与地类分异显著。时序上,“三生”空间冲突强度呈持续上升态势,整体处于基本可控级别;空间上,形成了“一心、两翼、多轴带”的空间冲突格局;就地类而言,城镇的生活空间与生产空间冲突水平较高。③兰州市“三生”空间冲突影响因素尺度效应和异质性明显。高程、坡度、地形起伏度等对“三生”空间冲突具有抑制作用;人口密度、人均G D P、夜间灯光指数等因素加剧了区域“三生”空间冲突程度。
