The objectives of this study are to assess land s ui tability and to predict the spatial and temporal changes in land use types (LUTs ) by using GIS-based land use management decision support system. A GIS databas e w...The objectives of this study are to assess land s ui tability and to predict the spatial and temporal changes in land use types (LUTs ) by using GIS-based land use management decision support system. A GIS databas e with data on climate, topography, soil characteristic, irrigation condition, f ertilizer application, and special socioeconomic activities has been developed a nd used for the evaluation of land productivity for different crops by integrati ng with a crop growth model-the erosion productivity impact calculator (EPIC). International food policy simulation model (IFPSIM) is also embedded into GIS fo r the predictions of how crop demands and crop market prices will change under a lternative policy scenarios. An inference engine (IE) including land use choice model is developed to illustrate land use choice behavior based on logit models , which allows to analyze how diversified factors ranging from climate changes, crop price changes to land management changes can affect the distribution of agr icultural land use. A test for integrated simulation is taken in each 0.1° by 0.1° grid cell to predict the change of agricultural land use types at globa l level. Global land use changes are simulated from 1992 to 2050.展开更多
The article intends to find a method to quantify traffic congestion＇s impacts on travelers to help transportation planners and policy decision makers well understand congestion situations. Three new congestion indica...The article intends to find a method to quantify traffic congestion＇s impacts on travelers to help transportation planners and policy decision makers well understand congestion situations. Three new congestion indicators, including transportation environment satisfaction （TES）, travel time satisfaction （TTS）, and traffic congestion frequency and feeling （TCFF）, are defined to estimate urban traffic congestion based on travelers＇ feelings. Data of travelers＇ attitude about congestion and trip information were collected from a survey in Shanghai, China. Based on the survey data, we estimated the value of the three indi- cators. Then, the principal components analysis was used to derive a small number of linear combinations of a set of variables to estimate the whole congestion status. A linear regression model was used to find out the significant variables which impact respondents＇ feelings. Two ordered logit models were used to select significant variables of TES and TTS. Attitudinal factor variables were also used in these models. The results show that attitudinal factor variables and cluster category variables are as important as sociodemographic variables in the models. Using the three congestion indicators, the government can collect travelers＇ feeling about traffic congestion and estimate the transportation policy that might be applied to cope with traffic congestion.展开更多
Every year,a substantial number of children sustain injuries and fatalities in motor vehicle crashes in Wyoming.Understanding the factors contributing to child injury is crucial for the development of appropriate miti...Every year,a substantial number of children sustain injuries and fatalities in motor vehicle crashes in Wyoming.Understanding the factors contributing to child injury is crucial for the development of appropriate mitigation measures that aid in alleviating the severity of such injuries.In this study,a hierarchical Bayesian binary logit regression model was developed to investigate the factors that contribute to children’s injuries resulting from crashes while accounting for possible intra-class correlation effects(those of unobserved factors common to children involved in the same crash).A strong correlation among crashes justified the use of the hierarchical Bayesian logit model.As per the modeling results,the children’s ages,safety restraint types,vehicle types,drivers’ages,alcohol/drug involvement,drivers’seat belt use habits,drivers’actions,manners of collision and environmental conditions contributed to child injury risk.The child’s age was found to be inversely related to the risk of injury.Similarly,among safety restraint types,rear-facing car seats and forward-facing car seats were found to reduce injury likelihoods in crashes.When it comes to the drivers’characteristics,the probability of incurring injuries among the child population increased in the presence of young,unbuckled and impaired drivers.Furthermore,improper driving actions,such as running off the road,raised the risk of incurring injuries to children.The findings of this study may be beneficial to authorities regarding developing and implementing road safety programs aimed at ameliorating child injury concerns.展开更多
Identification of accident black spots has gained tremendous popularity among road agencies and safety specialists for evaluating and subsequently enhancing road traffic safety.However,there is still limited understan...Identification of accident black spots has gained tremendous popularity among road agencies and safety specialists for evaluating and subsequently enhancing road traffic safety.However,there is still limited understanding of the internal relationship between black spots and microscopic vehicle kinetic parameters.To address this gap,this paper describes a project that was undertaken using the real-time tire force data(kinetic response)obtained from road experiments on Wenli Expressway.First,factor analysis was applied to extracted three independent indicators(power-braking,handling stability,and ride comfort)from seven original kinetic indicators with multiple collinearities.Afterward,the main indicators were given vehicle kinetic meaning by analyzing the characteristics of original indicators associated with them.A compelling correlation was established among kinetic parameters,vehicle running qualities,and accident risk.Additionally,an integrated evaluation framework was established to identify accident black spots based on applying ordered logit models and PLS-entropy-TOPSIS approaches.The recognition results exhibited that the overall recognition accuracy obtained by the latter was found to be comparable to that achieved using the previous one.The compound evaluation model proposed in this paper has been proven to present many advantages for black spot identification.It is evidently clear from the findings that the vehicle kinetic parameters have significant correlations with road accident risk.This paper could provide some insightful knowledge for identifying and preventing the black spots from ameliorating traffic safety.展开更多
文摘The objectives of this study are to assess land s ui tability and to predict the spatial and temporal changes in land use types (LUTs ) by using GIS-based land use management decision support system. A GIS databas e with data on climate, topography, soil characteristic, irrigation condition, f ertilizer application, and special socioeconomic activities has been developed a nd used for the evaluation of land productivity for different crops by integrati ng with a crop growth model-the erosion productivity impact calculator (EPIC). International food policy simulation model (IFPSIM) is also embedded into GIS fo r the predictions of how crop demands and crop market prices will change under a lternative policy scenarios. An inference engine (IE) including land use choice model is developed to illustrate land use choice behavior based on logit models , which allows to analyze how diversified factors ranging from climate changes, crop price changes to land management changes can affect the distribution of agr icultural land use. A test for integrated simulation is taken in each 0.1° by 0.1° grid cell to predict the change of agricultural land use types at globa l level. Global land use changes are simulated from 1992 to 2050.
基金supported by the Key Natural Science Foundation of China:Urban Transportation Planning Theory and Methods under the Information Environment, Grant No. 50738004/E0807
文摘The article intends to find a method to quantify traffic congestion＇s impacts on travelers to help transportation planners and policy decision makers well understand congestion situations. Three new congestion indicators, including transportation environment satisfaction （TES）, travel time satisfaction （TTS）, and traffic congestion frequency and feeling （TCFF）, are defined to estimate urban traffic congestion based on travelers＇ feelings. Data of travelers＇ attitude about congestion and trip information were collected from a survey in Shanghai, China. Based on the survey data, we estimated the value of the three indi- cators. Then, the principal components analysis was used to derive a small number of linear combinations of a set of variables to estimate the whole congestion status. A linear regression model was used to find out the significant variables which impact respondents＇ feelings. Two ordered logit models were used to select significant variables of TES and TTS. Attitudinal factor variables were also used in these models. The results show that attitudinal factor variables and cluster category variables are as important as sociodemographic variables in the models. Using the three congestion indicators, the government can collect travelers＇ feeling about traffic congestion and estimate the transportation policy that might be applied to cope with traffic congestion.
基金funded by the Wyoming Department of Transportation(WyDOT)supported by the Mountain Plains Consortium(Grant Number 69A3551747108(FAST Act))。
文摘Every year,a substantial number of children sustain injuries and fatalities in motor vehicle crashes in Wyoming.Understanding the factors contributing to child injury is crucial for the development of appropriate mitigation measures that aid in alleviating the severity of such injuries.In this study,a hierarchical Bayesian binary logit regression model was developed to investigate the factors that contribute to children’s injuries resulting from crashes while accounting for possible intra-class correlation effects(those of unobserved factors common to children involved in the same crash).A strong correlation among crashes justified the use of the hierarchical Bayesian logit model.As per the modeling results,the children’s ages,safety restraint types,vehicle types,drivers’ages,alcohol/drug involvement,drivers’seat belt use habits,drivers’actions,manners of collision and environmental conditions contributed to child injury risk.The child’s age was found to be inversely related to the risk of injury.Similarly,among safety restraint types,rear-facing car seats and forward-facing car seats were found to reduce injury likelihoods in crashes.When it comes to the drivers’characteristics,the probability of incurring injuries among the child population increased in the presence of young,unbuckled and impaired drivers.Furthermore,improper driving actions,such as running off the road,raised the risk of incurring injuries to children.The findings of this study may be beneficial to authorities regarding developing and implementing road safety programs aimed at ameliorating child injury concerns.
基金National Natural Science Foundation of China(Nos.51778141,52072069,71871078)Jiangsu Creative PhD Student-sponsored Project(No.KYCX20_00138)the Transportation Department of Henan Province(No.2018G7)。
文摘Identification of accident black spots has gained tremendous popularity among road agencies and safety specialists for evaluating and subsequently enhancing road traffic safety.However,there is still limited understanding of the internal relationship between black spots and microscopic vehicle kinetic parameters.To address this gap,this paper describes a project that was undertaken using the real-time tire force data(kinetic response)obtained from road experiments on Wenli Expressway.First,factor analysis was applied to extracted three independent indicators(power-braking,handling stability,and ride comfort)from seven original kinetic indicators with multiple collinearities.Afterward,the main indicators were given vehicle kinetic meaning by analyzing the characteristics of original indicators associated with them.A compelling correlation was established among kinetic parameters,vehicle running qualities,and accident risk.Additionally,an integrated evaluation framework was established to identify accident black spots based on applying ordered logit models and PLS-entropy-TOPSIS approaches.The recognition results exhibited that the overall recognition accuracy obtained by the latter was found to be comparable to that achieved using the previous one.The compound evaluation model proposed in this paper has been proven to present many advantages for black spot identification.It is evidently clear from the findings that the vehicle kinetic parameters have significant correlations with road accident risk.This paper could provide some insightful knowledge for identifying and preventing the black spots from ameliorating traffic safety.
文摘游憩承载力是衡量国家森林公园利用限度的一个重要指标.然而,游憩承载力的内涵和度量方法在学术界尚未形成一个统一的认知.已有的研究多以社会承载力和工程方法测算单位时间内景区允许进入游客的数量.这种做法虽然在管理上具有一定的可操作性,但却不能准确反映承载力概念的科学内涵.文章从旅游效用最大化视角出发,构建基于景区环境属性水平的游憩承载力理论框架,并估计各种属性的承载力阈值.研究过程运用选择实验法进行问卷设计和条件logit模型进行参数估计.模型结果表明,植被覆盖率承载力阈值为78%,垃圾数量承载力阈值为3件/20 m,游客密度承载力阈值为14人/200 m^2,水的能见度承载力阈值为1.45 m.
