It is well established that complex networks are responsible for the high-level information processing in the human brain.The topology of complex networks allows efficient dynamic interactions between spatially distin...It is well established that complex networks are responsible for the high-level information processing in the human brain.The topology of complex networks allows efficient dynamic interactions between spatially distinct brain areas,which may be studied by analyzing the topological展开更多
The aim of this work is to explore the impact of regional transit service on tour-based commuter travel behavior by using the Bayesian hierarchical multinomial logit model, accounting for the spatial heterogeneity of ...The aim of this work is to explore the impact of regional transit service on tour-based commuter travel behavior by using the Bayesian hierarchical multinomial logit model, accounting for the spatial heterogeneity of the people living in the same area.With two indicators, accessibility and connectivity measured at the zone level, the regional transit service is captured and then related to the travel mode choice behavior. The sample data are selected from Washington-Baltimore Household Travel Survey in 2007,including all the trips from home to workplace in morning hours in Baltimore city. Traditional multinomial logit model using Bayesian approach is also estimated. A comparison of the two different models shows that ignoring the spatial context can lead to a misspecification of the effects of the regional transit service on travel behavior. The results reveal that improving transit service at regional level can be effective in reducing auto use for commuters after controlling for socio-demographics and travel-related factors.This work provides insights for interpreting tour-based commuter travel behavior by using recently developed methodological approaches. The results of this work will be helpful for engineers, urban planners, and transit operators to decide the needs to improve regional transit service and spatial location efficiently.展开更多
On the basis of analyzing yearly data and spatial relationships between tourism spots, star hotels and travel agencies of Hainan Province, and comparing all the methods of measuring industrial spatial agglomeration, t...On the basis of analyzing yearly data and spatial relationships between tourism spots, star hotels and travel agencies of Hainan Province, and comparing all the methods of measuring industrial spatial agglomeration, this paper chose Hefindahl index, Location Quotient, nearest neighbor index, spatial connection index and geographic concentration index to measure Hainan tourism agglomeration. By applying these methods, total tourism agglomeration, agglomeration of tourism factors and regional agglomeration differences were studied. The results showed that the overall agglomeration increases as time flows, and the eastern part is the most agglomerated, the west takes the second, with the middle ranking the least. The large-scale agglomeration regions are Sanya and Haikou. The influencing factors of Hainan tourism spatial agglomeration were concluded as tourism resource endowment, industrial attributes, geographic conditions, governmental policies and the overall economic development level, etc. In addition, the paper proposed tourism spatial agglomeration modes of Hainan Province at various spatial scales.展开更多
The environmental factors that influence tree-grass abundances in tropical savanna and grasslands are not well understood,particularly for woodland-grassland mosaics in humid zones.We studied the effects of abiotic an...The environmental factors that influence tree-grass abundances in tropical savanna and grasslands are not well understood,particularly for woodland-grassland mosaics in humid zones.We studied the effects of abiotic and spatial variables on woody and herbaceous species distributions in a Terai ecosystem of northeastern India.We evaluated the importance of climatic and non-climatic factors that maintain variable tree-grass ratios across the landscape,and also accounted for spatial connectivity and dispersal.We measured species abundances of woody and herbaceous plant species in 134 plots with each 30 m×30 m in a 519 km^(2)protected Terai habitat,and derived several climatic and non-climatic environmental factors.We constructed variables based on different models of spatial connectivity among sites,to test their influence on species abundances.We then used redundancy analyses and variation partitioning to quantify the importance of environmental variables and spatial structure on variation in tree-grass abundances.We found that environmental variables including rainfall,fire,water stress,topography and soil nutrients had statistically significant effects on species abundance and tree-grass ratios.Spatial structure was significant,and the best spatial model was an inverse distance-weighted model with linkage extending to 23.5 km,indicating weak dispersal limitation.About 21%of the variation in species abundance was explained by the selected environmental and spatial factors.The results indicate that dynamic plant communities in which spatial-temporal variation in environmental factors may drive stochasticity in species distribution and abundance,thus dominantly influencing on the vegetation mosaic.展开更多
文摘It is well established that complex networks are responsible for the high-level information processing in the human brain.The topology of complex networks allows efficient dynamic interactions between spatially distinct brain areas,which may be studied by analyzing the topological
基金Project(71173061)supported by the National Natural Science Foundation of ChinaProject(2013U-6)supported by Key Laboratory of Eco Planning & Green Building,Ministry of Education(Tsinghua University),China
文摘The aim of this work is to explore the impact of regional transit service on tour-based commuter travel behavior by using the Bayesian hierarchical multinomial logit model, accounting for the spatial heterogeneity of the people living in the same area.With two indicators, accessibility and connectivity measured at the zone level, the regional transit service is captured and then related to the travel mode choice behavior. The sample data are selected from Washington-Baltimore Household Travel Survey in 2007,including all the trips from home to workplace in morning hours in Baltimore city. Traditional multinomial logit model using Bayesian approach is also estimated. A comparison of the two different models shows that ignoring the spatial context can lead to a misspecification of the effects of the regional transit service on travel behavior. The results reveal that improving transit service at regional level can be effective in reducing auto use for commuters after controlling for socio-demographics and travel-related factors.This work provides insights for interpreting tour-based commuter travel behavior by using recently developed methodological approaches. The results of this work will be helpful for engineers, urban planners, and transit operators to decide the needs to improve regional transit service and spatial location efficiently.
基金Sponsored by National Natural Science Foundation of China(51309134)Research Starting Funds for Imported TalentsNingxia University(BQD2012011)
文摘On the basis of analyzing yearly data and spatial relationships between tourism spots, star hotels and travel agencies of Hainan Province, and comparing all the methods of measuring industrial spatial agglomeration, this paper chose Hefindahl index, Location Quotient, nearest neighbor index, spatial connection index and geographic concentration index to measure Hainan tourism agglomeration. By applying these methods, total tourism agglomeration, agglomeration of tourism factors and regional agglomeration differences were studied. The results showed that the overall agglomeration increases as time flows, and the eastern part is the most agglomerated, the west takes the second, with the middle ranking the least. The large-scale agglomeration regions are Sanya and Haikou. The influencing factors of Hainan tourism spatial agglomeration were concluded as tourism resource endowment, industrial attributes, geographic conditions, governmental policies and the overall economic development level, etc. In addition, the paper proposed tourism spatial agglomeration modes of Hainan Province at various spatial scales.
基金We thank the UNESCO World Heritage Sites Program and the United States Fish and Wildlife Service Tiger Conservation Grant Program(F12AP00312)for financial support to carry out this work.
文摘The environmental factors that influence tree-grass abundances in tropical savanna and grasslands are not well understood,particularly for woodland-grassland mosaics in humid zones.We studied the effects of abiotic and spatial variables on woody and herbaceous species distributions in a Terai ecosystem of northeastern India.We evaluated the importance of climatic and non-climatic factors that maintain variable tree-grass ratios across the landscape,and also accounted for spatial connectivity and dispersal.We measured species abundances of woody and herbaceous plant species in 134 plots with each 30 m×30 m in a 519 km^(2)protected Terai habitat,and derived several climatic and non-climatic environmental factors.We constructed variables based on different models of spatial connectivity among sites,to test their influence on species abundances.We then used redundancy analyses and variation partitioning to quantify the importance of environmental variables and spatial structure on variation in tree-grass abundances.We found that environmental variables including rainfall,fire,water stress,topography and soil nutrients had statistically significant effects on species abundance and tree-grass ratios.Spatial structure was significant,and the best spatial model was an inverse distance-weighted model with linkage extending to 23.5 km,indicating weak dispersal limitation.About 21%of the variation in species abundance was explained by the selected environmental and spatial factors.The results indicate that dynamic plant communities in which spatial-temporal variation in environmental factors may drive stochasticity in species distribution and abundance,thus dominantly influencing on the vegetation mosaic.
