手机定位人口数据在应急救援中的应用

随着智能手机的普及,基于手机定位的人口数据在突发性灾害应急救援领域发挥着日益重要的作用。以近几年地震灾区为主要研究对象,选择灾区中有代表性的旅游景区、县城及乡镇,获取这些区域手机定位的人口数据,同时采用传统方法估算区域内人口数量,并进行差异性对比。研究结果表明:差异性最大的是旅游景区、其次是县城和乡镇;在人口年度变化上,旅游景区的人口在7、8月份达到高峰,乡镇人口高值区出现在2月份,县城人口年度差异无明显规律。     

土压平衡矩形顶管施工引起的地表沉降规律研究

为了分析与掌握矩形顶管施工引起的地表沉降变形规律，提出基于MIDAS-GTS有限元软件的分析方法，首先，通过工程实例验证MIDAS-GTS有限元软件在分析顶管施工引起地表沉降变形的有效性；其次，通过影响因素的敏感性分析确定不同影响因素作用下的地表沉降变形特性，这些影响因素主要包括开挖面支护压力、侧摩阻力、地层结构特性等；最后，通过地表沉降变形特性分析得出矩形顶管的适用范围。研究结果表明:基于MIDAS-GTS有限元软件的地表沉降规律分析方法和结果，可为矩形顶管施工过程提供相关参考和借鉴。     

大数据解析技术在大气环境监测中的应用研究

针对近年来新兴的大数据及挖掘、分析技术,对大数据解析技术在环境科学研究中的应用进行了分析和探析。以城市局部地区大气细颗粒污染物PM2.5浓度计算为例,筛选了PM2.5浓度历史数据、气象条件、交通状况、人群活动情况、网格道路状况等数据为影响特征量,分析了用神经网络法进行大数据解析和推演的原理和数学过程,是用数学、计算机、统计等方法研究解决多元、非线性复杂环境问题的一种新的探索。     

Safe speed limits for a safe system: The relationship between speed limit and fatal crash rate for different crash types

Objective: The objective of this article is to provide empirical evidence for safe speed limits that will meet the objectives of the Safe System by examining the relationship between speed limit and injury severity for different crash types, using police-reported crash data.

Method: Police-reported crashes from 2 Australian jurisdictions were used to calculate a fatal crash rate by speed limit and crash type. Example safe speed limits were defined using threshold risk levels.

Results: A positive exponential relationship between speed limit and fatality rate was found. For an example fatality rate threshold of 1 in 100 crashes it was found that safe speed limits are 40 km/h for pedestrian crashes; 50 km/h for head-on crashes; 60 km/h for hit fixed object crashes; 80 km/h for right angle, right turn, and left road/rollover crashes; and 110 km/h or more for rear-end crashes.

Conclusions: The positive exponential relationship between speed limit and fatal crash rate is consistent with prior research into speed and crash risk. The results indicate that speed zones of 100 km/h or more only meet the objectives of the Safe System, with regard to fatal crashes, where all crash types except rear-end crashes are exceedingly rare, such as on a high standard restricted access highway with a safe roadside design.     

Spatial and Seasonal Response of Municipal Water Use to Weather across the Contiguous U.S.

Weather variability has the potential to influence municipal water use, particularly in dry regions such as the western United States (U.S.). Outdoor water use can account for more than half of annual household water use and may be particularly responsive to weather, but little is known about how the expected magnitude of these responses varies across the U.S. This nationwide study identified the response of municipal water use to monthly weather (i.e., temperature, precipitation, evapotranspiration [ET]) using monthly water deliveries for 229 cities in the contiguous U.S. Using city‐specific multiple regression and region‐specific models with city fixed effects, we investigated what portion of the variability in municipal water use was explained by weather across cities, and also estimated responses to weather across seasons and climate regions. Our findings indicated municipal water use was generally well‐explained by weather, with median adjusted R² ranging from 63% to 95% across climate regions. Weather was more predictive of water use in dry climates compared to wet, and temperature had more explanatory power than precipitation or ET. In response to a 1°C increase in monthly maximum temperature, municipal water use was shown to increase by 3.2% and 3.9% in dry cities in winter and summer, respectively, with smaller changes in wet cities. Quantifying these responses allows urban water managers to plan for weather‐driven variability in water use.     

Using culturomics and social media data to characterize wildlife consumption

Wildlife provides food, medicine, clothing, and other necessities for humans, but overexploitation can disrupt the sustainability of wildlife resources and severely threaten global biodiversity. Understanding the characteristics of consumer behavior is helpful for wildlife managers and policy makers, but the traditional survey methods are laborious and time-consuming. In contrast, culturomics may more efficiently identify the features of wildlife consumption. As a case study of the culturomics approach, we examined tiger bone wine consumption in China based on social media and Baidu search engine data. Tiger bone wine is one of the most purchased tiger products; its consumption is closely related to tiger poaching, which greatly threatens wild tiger survival. We searched a popular social media website for the term “tiger bone wine” and focused on posts that were originally created from 1 January 2012 to 31 December 2018. We filtered and classified posts related to the purchase, sale, or consumption of tiger bone wine and extracted information on providers, consumption motivations, year of production, and place of origin of the tiger bone wines based on the texts and photos of these posts. We found 756 posts related to tiger bone wine consumption, 113 of which mentioned providers of tiger bone wine, including friends (53%), elder relatives (37%), peer relatives (7%), and others (3%). Out of the 756 posts, 266 indicated the motivations of tiger bone wine consumption. Tiger bone wines were consumed as a tonic (34%), medicine (23%), game product (30%), and a symbol of wealth (28%). Some posts indicated ≥2 consumption motivations. These findings were consistent with the search queries from Baidu index. Such information could help develop targeted strategies for tiger conservation. The culturomics approach illustrated by our study is a rapid and cost-efficient way to characterize wildlife consumption.     

国家生态环境监测“十四五”展望

"十四五"时期,生态文明改革持续深入,生态环境治理将向精准治污、科学治污、依法治污转变,这对加快推进生态环境监测体系与监测能力现代化提出了迫切要求。因此,本文从网络建设、体制机制、服务效能等方面,对生态环境监测所取得的进展与成效进行了系统分析,并对国家生态环境监测面临的机遇与挑战进行了深入剖析。在此基础上,针对支撑评价排名、服务精准治污、有序衔接新职能、建设大数据平台、强化数据应用、深化综合评价、理顺体制机制、推动产学研用、提升基础能力等方面,提出了"十四五"期间国家生态环境监测发展的相关建议。     

A critical overview of driver recording tools

Introduction: Technological advancements during recent decades have led to the development of a wide array of tools and methods in order to record driving behavior and measure various aspects of driving performance. The aim of the present study is to present and comparatively assess the various driver recording tools that researchers have at their disposal. Method: In order to achieve this aim, a multitude of published studies from the international literature have been examined based on the driver recording methodologies that have been implemented. An examination of more traditional survey methods (questionnaires, police reports, and direct observer methods) is initially conducted, followed by investigating issues pertinent to the use of driving simulators. Afterwards, an extensive section is provided for naturalistic driving data tools, including the utilization of on-board diagnostics (OBD) and in-vehicle data recorders (IVDRs). Lastly, in-depth incident analysis and the exploitation of smartphone data are discussed. Results: A critical synthesis of the results is conducted, providing the advantages and disadvantages of utilizing each tool and including additional knowledge regarding ease of experimental implementation, data handling issues, impacts on subsequent analyses, as well as the respective cost parameters. Conclusions: New technologies provide undeniably powerful tools that allow for seamless data handling, storage, and analysis, such as smartphones and in-vehicle data recorders. However, this sometimes comes at considerable costs (which may or may not pay off at a later stage), while legacy driver recording methods still have their own niches to fill in research. Practical Applications: The present research supports researchers when designing driver behavior monitoring studies. The present work enables better scheduling and pacing of research activities, but can also provide insights for the distribution of research funds.     

Use of Predictive Weather Uncertainties in an Irrigation Scheduling Tool Part II: An Application of Metrics and Adjoints

We apply predictive weather metrics and land model sensitivities to improve the Colorado State University Water Irrigation Scheduler for Efficient Application (WISE). WISE is an irrigation decision aid that integrates environmental and user information for optimizing water use. Rainfall forecasts and verification performance metrics are used to estimate predictive rainfall probabilities that are used as input data within the irrigation decision aid. These input data errors are also used within a land model sensitivity study to diagnose important prognostic water movement behaviors for irrigation tool development purposes simultaneously performing the analysis in space and time. Thus, important questions such as “how long can a crop water application be delayed while maintaining crop yield production?” are addressed by evaluating crop growth stage interactions as a function of soil depth (i.e., space), rainfall events (i.e., time), and their probabilistic uncertainties. Editor’s note : This paper is part of the featured series on Optimizing Ogallala Aquifer Water Use to Sustain Food Systems. See the February 2019 issue for the introduction and background to the series.     

大数据环境下企业安全绩效管理的基础性问题*

为明晰大数据对安全绩效管理的影响，把握信息时代下企业安全绩效管理的研究方向，基于大数据时代下安全绩效管理内容，阐述数据驱动下安全绩效管理的应用优势，探讨数据驱动下安全绩效管理的研究变革，剖析大数据环境下企业安全绩效管理的数据流向，构建数据驱动下安全绩效管理的框架模型，并提出数据驱动下企业安全绩效管理应用对策。结果表明:基于大数据的安全绩效管理有助于提升企业安全管理水平，也为安全生产系统优化提供理论依据。