Identifying risk factors for road traffic injuries can be considered one of the main priorities of transportation agencies. More than 12,000 fatal work zone crashes were reported between 2000 and 2013. Despite recent ...Identifying risk factors for road traffic injuries can be considered one of the main priorities of transportation agencies. More than 12,000 fatal work zone crashes were reported between 2000 and 2013. Despite recent efforts to improve work zone safety, the frequency and severity of work zone crashes are still a big concern for transportation agencies. Although many studies have been conducted on different work zone safety-related issues, there is a lack of studies that investigate the effect of adverse weather conditions on work zone crash severity. This paper utilizes probit–classification tree, a relatively recent and promising combination of machine learning technique and conventional parametric model, to identify factors affecting work zone crash severity in adverse weather conditions using 8 years of work zone weatherrelated crashes (2006–2013) in Washington State. The key strength of this technique lies in its capability to alleviate the shortcomings of both parametric and nonparametric models. The results showed that both presence of traffic control device and lighting conditions are significant interacting variables in the developed complementary crash severity model for work zone weather-related crashes. Therefore, transportation agencies and contractors need to invest more in lighting equipment and better traffic control strategies at work zones, specifically during adverse weather conditions.展开更多
Through typical sampling,the species,diameters at breast height (DBH) and growth status of street trees in Donghu Hi-tech Development Zone in Wuhan City were investigated;the characteristics and existing problems were...Through typical sampling,the species,diameters at breast height (DBH) and growth status of street trees in Donghu Hi-tech Development Zone in Wuhan City were investigated;the characteristics and existing problems were analyzed.Constructive suggestions were put forward to enrich urban street tree species and outstand the characteristics of local species,so as to provide references to the street tree planning in Donghu Hi-tech Development Zone in Wuhan City.展开更多
Impervious surface(IS) is often recognized as the indicator of urban environmental changes. Numerous research efforts have been devoted to studying its spatio-temporal dynamics and ecological effects, especially for t...Impervious surface(IS) is often recognized as the indicator of urban environmental changes. Numerous research efforts have been devoted to studying its spatio-temporal dynamics and ecological effects, especially for the IS in Beijing metropolitan region. However, most previous studies primarily considered the Beijing metropolitan region as a whole without considering the differences and heterogeneity among the function zones. In this study, the subpixel impervious surface results in Beijing within a time series(1991, 2001, 2005, 2011 and 2015) were extracted by means of the classification and regression tree(CART) model combined with change detection models. Then based on the method of standard deviation ellipse, Lorenz curve, contribution index(CI) and landscape metrics, the spatio-temporal dynamics and variations of IS(1991, 2001, 2011 and 2015) in different function zones and districts were analyzed. It is found that the total area of impervious surface in Beijing increased dramatically during the study period, increasing about 144.18%. The deflection angle of major axis of standard deviation ellipse decreased from 47.15° to 38.82°, indicating the major development axis in Beijing gradually moved from northeast-southwest to north-south. Moreover, the heterogeneity of impervious surface’s distribution among 16 districts weakened gradually, but the CI values and landscape metrics in four function zones differed greatly. The urban function extended zone(UFEZ), the main source of the growth of IS in Beijing, had the highest CI values. Its lowest CI value was 1.79 that is still much higher than the highest CI value in other function zones. The core function zone(CFZ), the traditional aggregation zone of impervious surface, had the highest contagion index(CONTAG) values, but it contributed less than UFEZ due to its small area. The CI value of the new urban developed zone(NUDZ) increased rapidly, and it increased from negative to positive and multiplied, becoming animportant contributor to the rise of urban impervious surface. However, the ecological conservation zone(ECZ) had a constant negative contribution all the time, and its CI value decreased gradually. Moreover, the landscape metrics and centroids of impervious surface in different density classes differed greatly. The high-density impervious surface had a more compact configuration and a greater impact on the eco-environment.展开更多
This study was designed to use LiDAR data to research tree heights in montane forest blocks of Kenya. It uses a completely randomised block design to asses if differences exist in forest heights: 1) among montane fore...This study was designed to use LiDAR data to research tree heights in montane forest blocks of Kenya. It uses a completely randomised block design to asses if differences exist in forest heights: 1) among montane forest blocks, 2) among Agro ecological zones (AEZ) within each forest block and 3) between similar AEZ in different forest blocks. Forest height data from the Geoscience Laser Altimeter System (GLAS) on the Ice Cloud and Land Elevation Satellite (ICE-SAT) for the period 2003-2009 was used for 2146 circular plots, of 0.2 - 0.25 ha in size. Results indicate that, tree height is largely influenced by Agro ecological conditions and the wetter zones have taller trees in the upper, middle and lower highlands. In the upper highland zones of limited human activity, tree heights did not vary among forest blocks. Variations in height among forest blocks and within forest blocks were exaggerated in regions of active human intervention.展开更多
[ Objective] The research aimed to study climatic zoning of tea tree cultivation in Hanzhong. [Method] Based on climate data at 11 meteorological observatories of Hanzhong during 1971 -2010, selecting annual average e...[ Objective] The research aimed to study climatic zoning of tea tree cultivation in Hanzhong. [Method] Based on climate data at 11 meteorological observatories of Hanzhong during 1971 -2010, selecting annual average extreme minimum temperature, annual average temperature, accumulative temperature ≥10 ℃ and annual rainfall as climatic zoning factors, regression model between zoning factors and geographic information was established, and comprehensive climatic zoning indicator of tea tree cultivation in Hanzhong was determined. [ Result] Tea tree cultivation in Hanzhong was divided into suitable, more suitable and unsuitable planting zones by using critical value of climatic zoning. [ Conclusion] The research could provide scientific basis for reasonable planning layout and sustainable development of tea tree in the whole city.展开更多
针对传统滑坡易发性预测方法主要依赖统一的降雨量阈值,忽视不同区域因地形、土壤和植被等环境因素差异导致的降雨响应问题,该文提出了一种提高预测准确性和实时性的解决方案。采用K-Means聚类方法,根据地形、土壤和植被等环境因素,将...针对传统滑坡易发性预测方法主要依赖统一的降雨量阈值,忽视不同区域因地形、土壤和植被等环境因素差异导致的降雨响应问题,该文提出了一种提高预测准确性和实时性的解决方案。采用K-Means聚类方法,根据地形、土壤和植被等环境因素,将研究区域划分为若干具有相似特征的子区域,为每个子区域拟合基于实时数据的降雨量阈值,提升阈值的局部适应性和针对性。将分区的实时降雨量阈值与自适应神经树模型(adaptive neural tree,ANT)集成,使ANT模型适应各分区的特定环境条件,并根据累计降雨量与滑坡发生率的关系自动调整预测阈值。以中缅油气管道贵州段为例,将整体阈值和基于K-Means聚类得到的分区实时降雨量阈值分别应用于ANT模型。结果显示,采用聚类分区实时降雨量阈值的ANT模型在精确度、召回率、F1分数和受试者工作特征曲线下面积(receiver operating characteristic area under curve,ROC AUC)值等关键性能指标上均优于仅使用整体阈值的模型。研究表明,基于K-Means聚类的实时降雨量阈值分区方法与ANT模型的集成,能够显著提高滑坡易发性预测的准确率,实现滑坡风险的实时评估。展开更多
基金sponsored by the Federal Highway Administration(FHWA)in cooperation with the American Association of State Highway and Transportation Officials(AASHTO)
文摘Identifying risk factors for road traffic injuries can be considered one of the main priorities of transportation agencies. More than 12,000 fatal work zone crashes were reported between 2000 and 2013. Despite recent efforts to improve work zone safety, the frequency and severity of work zone crashes are still a big concern for transportation agencies. Although many studies have been conducted on different work zone safety-related issues, there is a lack of studies that investigate the effect of adverse weather conditions on work zone crash severity. This paper utilizes probit–classification tree, a relatively recent and promising combination of machine learning technique and conventional parametric model, to identify factors affecting work zone crash severity in adverse weather conditions using 8 years of work zone weatherrelated crashes (2006–2013) in Washington State. The key strength of this technique lies in its capability to alleviate the shortcomings of both parametric and nonparametric models. The results showed that both presence of traffic control device and lighting conditions are significant interacting variables in the developed complementary crash severity model for work zone weather-related crashes. Therefore, transportation agencies and contractors need to invest more in lighting equipment and better traffic control strategies at work zones, specifically during adverse weather conditions.
文摘Through typical sampling,the species,diameters at breast height (DBH) and growth status of street trees in Donghu Hi-tech Development Zone in Wuhan City were investigated;the characteristics and existing problems were analyzed.Constructive suggestions were put forward to enrich urban street tree species and outstand the characteristics of local species,so as to provide references to the street tree planning in Donghu Hi-tech Development Zone in Wuhan City.
基金National Basic Research Program of China,No.2015CB953603National Natural Science Foundation of China,No.41671339State Key Laboratory of Earth Surface Processes and Resource Ecology,No.2017-FX-01(1)
文摘Impervious surface(IS) is often recognized as the indicator of urban environmental changes. Numerous research efforts have been devoted to studying its spatio-temporal dynamics and ecological effects, especially for the IS in Beijing metropolitan region. However, most previous studies primarily considered the Beijing metropolitan region as a whole without considering the differences and heterogeneity among the function zones. In this study, the subpixel impervious surface results in Beijing within a time series(1991, 2001, 2005, 2011 and 2015) were extracted by means of the classification and regression tree(CART) model combined with change detection models. Then based on the method of standard deviation ellipse, Lorenz curve, contribution index(CI) and landscape metrics, the spatio-temporal dynamics and variations of IS(1991, 2001, 2011 and 2015) in different function zones and districts were analyzed. It is found that the total area of impervious surface in Beijing increased dramatically during the study period, increasing about 144.18%. The deflection angle of major axis of standard deviation ellipse decreased from 47.15° to 38.82°, indicating the major development axis in Beijing gradually moved from northeast-southwest to north-south. Moreover, the heterogeneity of impervious surface’s distribution among 16 districts weakened gradually, but the CI values and landscape metrics in four function zones differed greatly. The urban function extended zone(UFEZ), the main source of the growth of IS in Beijing, had the highest CI values. Its lowest CI value was 1.79 that is still much higher than the highest CI value in other function zones. The core function zone(CFZ), the traditional aggregation zone of impervious surface, had the highest contagion index(CONTAG) values, but it contributed less than UFEZ due to its small area. The CI value of the new urban developed zone(NUDZ) increased rapidly, and it increased from negative to positive and multiplied, becoming animportant contributor to the rise of urban impervious surface. However, the ecological conservation zone(ECZ) had a constant negative contribution all the time, and its CI value decreased gradually. Moreover, the landscape metrics and centroids of impervious surface in different density classes differed greatly. The high-density impervious surface had a more compact configuration and a greater impact on the eco-environment.
文摘This study was designed to use LiDAR data to research tree heights in montane forest blocks of Kenya. It uses a completely randomised block design to asses if differences exist in forest heights: 1) among montane forest blocks, 2) among Agro ecological zones (AEZ) within each forest block and 3) between similar AEZ in different forest blocks. Forest height data from the Geoscience Laser Altimeter System (GLAS) on the Ice Cloud and Land Elevation Satellite (ICE-SAT) for the period 2003-2009 was used for 2146 circular plots, of 0.2 - 0.25 ha in size. Results indicate that, tree height is largely influenced by Agro ecological conditions and the wetter zones have taller trees in the upper, middle and lower highlands. In the upper highland zones of limited human activity, tree heights did not vary among forest blocks. Variations in height among forest blocks and within forest blocks were exaggerated in regions of active human intervention.
文摘[ Objective] The research aimed to study climatic zoning of tea tree cultivation in Hanzhong. [Method] Based on climate data at 11 meteorological observatories of Hanzhong during 1971 -2010, selecting annual average extreme minimum temperature, annual average temperature, accumulative temperature ≥10 ℃ and annual rainfall as climatic zoning factors, regression model between zoning factors and geographic information was established, and comprehensive climatic zoning indicator of tea tree cultivation in Hanzhong was determined. [ Result] Tea tree cultivation in Hanzhong was divided into suitable, more suitable and unsuitable planting zones by using critical value of climatic zoning. [ Conclusion] The research could provide scientific basis for reasonable planning layout and sustainable development of tea tree in the whole city.
文摘针对传统滑坡易发性预测方法主要依赖统一的降雨量阈值,忽视不同区域因地形、土壤和植被等环境因素差异导致的降雨响应问题,该文提出了一种提高预测准确性和实时性的解决方案。采用K-Means聚类方法,根据地形、土壤和植被等环境因素,将研究区域划分为若干具有相似特征的子区域,为每个子区域拟合基于实时数据的降雨量阈值,提升阈值的局部适应性和针对性。将分区的实时降雨量阈值与自适应神经树模型(adaptive neural tree,ANT)集成,使ANT模型适应各分区的特定环境条件,并根据累计降雨量与滑坡发生率的关系自动调整预测阈值。以中缅油气管道贵州段为例,将整体阈值和基于K-Means聚类得到的分区实时降雨量阈值分别应用于ANT模型。结果显示,采用聚类分区实时降雨量阈值的ANT模型在精确度、召回率、F1分数和受试者工作特征曲线下面积(receiver operating characteristic area under curve,ROC AUC)值等关键性能指标上均优于仅使用整体阈值的模型。研究表明,基于K-Means聚类的实时降雨量阈值分区方法与ANT模型的集成,能够显著提高滑坡易发性预测的准确率,实现滑坡风险的实时评估。
