一种基于数据融合的林火火线动态蔓延预测方法的研究

准确预测林火蔓延对于有效防治野火危害具有重要意义。传统林火蔓延速度场经验模型需要可燃物特性、坡度、温度及湿度等众多实测参数,由于参数均具有不同的时空分布,限制了模型的实际应用。因此提出速度场实时测量及水平集法模拟林火蔓延两种技术相结合的方法,通过测定火蔓延锋面的位置获取当前时刻锋面处的速度场分布并对此速度场在未燃烧区域进行延拓,结合水平集法预测林火蔓延,并使用数值模拟及实验数据验证了该方法能够有效预测短期内林火蔓延趋势,得出基于速度场的数据融合方法可满足实际林火蔓延建模的需求。     

The impact of job security,satisfaction and stress on performance assessment and optimization of generation companies

In this study, performances of Iranian thermal power plants have been assessed with respect to human factors such as job stress, satisfaction and security through data envelopment analysis (DEA). In the first step performance of power plants (DMUs) have been evaluated considering traditional production factors including installed capacity, internal consumption and fuel consumption as inputs and gross production as output (model 1). In the next step, model 1 is expanded to include three above mentioned human factors (model 2). Power plants have been ranked based on their relative efficiency scores in both models. Pearson and Spearman correlation coefficients between relative efficiency scores and rankings of power plants in two models have been calculated. The results show that efficiency scores and rankings of power plants in two models are quite different indicating that mentioned human factors have direct impact on overall performance of generation companies and that if we were to use just traditional factors it would not reflect the optimum efficiency of the DMUs. Finally, job security has been found as the most effective human factor in Iranian power plants. This is the first study that presents an integrated approach for assessment of electric power plants considering job stress, security and satisfaction. And it is shown that these human factors play important role in overall performance of generation companies.     

如何提高环境监测数据的质量

环境监测数据的质量是否具有代表性、准确性、精密性、可比性和完整性,将直接影响到环境监测为环境管理服务的质量、环境执法的公正性和严肃性以及政府环境决策的科学性,关系到科学发展观和国民经济可持续发展战略的正确实施,本文通过＂五性＂来谈一下如何提高监测数据的质量,也就是通过提高环境监测数据的代表性、准确性、精密性、可比性、完整性来提高数据质量,以期对同行有所启发。     

Data quality evaluation and calibration of on-road remote sensing systems based on exhaust plumes

In recent years, with rapid increases in the number of vehicles in China, the contribution of vehicle exhaust emissions to air pollution has become increasingly prominent. To achieve the precise control of emissions, on-road remote sensing (RS) technology has been developed and applied for law enforcement and supervision. However, data quality is still an existing issue affecting the development and application of RS. In this study, the RS data from a cross-road RS system used at a single site (from 2012 to 2015) were collected, the data screening process was reviewed, the issues with data quality were summarized, a new method of data screening and calibration was proposed, and the effectiveness of the improved data quality control methods was finally evaluated. The results showed that this method reduces the skewness and kurtosis of the data distribution by up to nearly 67%, which restores the actual characteristics of exhaust diffusion and is conducive to the identification of actual clean and high-emission vehicles. The annual variability of emission factors of nitric oxide decreases by 60% – on average – eliminating the annual drift of fleet emissions and improving data reliability.     

Effectiveness of the policy of circular economy in China: A DEA-based analysis for the period of 11th five-year-plan

As a policy instrument for sustainable development, nationwide circular economy (CE) mode has been implemented for 7 years by the Chinese government, to overcome the dilemma among economic depression, energy shortage and environmental pollution. Unfortunately, few literatures contribute to checking the efficiency of regional CE and exploring the potential reasons in China, which will be practically helpful in guiding China's future development and providing reference for other developing countries that will adopt CE mode. Therefore, this paper puts forward the method of super-efficiency DEA window analysis to dynamically evaluate CE efficiency of 30 regions in China covering the period of 2005–2010. In line with the features of CE, the specific efficiency of three sub-systems, namely resource saving and pollutant reducing (RSPR) sub-system, waste reusing and resource recycling (WRRR) sub-system and pollution controlling and waste disposing (PCWD) sub-system, was assessed and compared regarding time series trend and spatial distribution, based on which, the comprehensive CE efficiency was totally ranked. The results show that, on the one hand, during the period of 2005–2010, Chinese CE efficiency slightly increased, implying a significant policy effect of CE; on the other hand, the efficiency of different sub-systems varies, with RSPR sub-system the lowest, and WRRR and PCWD sub-systems relatively higher. In terms of regional distribution, the efficiency of RSPR sub-system in the east area dominates during the whole period. However, for the other two sub-systems, from 2005 to 2007, the efficiency scores of the east fluctuate, then after 2007, the east area became more efficient than the central and the west areas. Throughout the study period, the RSPR sub-system in the central area stably maintains low efficiency, and so does the WRRR sub-system in the west area. The difference in regional efficiency of three sub-systems reflects the difficulty of carrying out CE policy in China comprehensively, which means that, promoting the adaptability of regional policy for local government and enhancing the coordination among various policies for China's central government are the key concerns for realizing sustainable development.     

Challenges to quantitative applications of Landsat observations for the urban thermal environment

Since the launch of its first satellite in 1972, the Landsat program has operated continuously for more than forty years. A large data archive collected by the Landsat program sig-nificantly benefits both the academic community and society. Thermal imagery from Landsat sensors, provided with relatively high spatial resolution, is suitable for monitoring urban thermal environment. Growing use of Landsat data in monitoring urban thermal environment is demonstrated by increasing publications on this subject, especially over the last decade. Urban thermal environment is usually delineated by land surface temperature (LST). However, the quantitative and accurate estimation of LST from Landsat data is still a challenge, especially for urban areas. This paper will discuss the main challenges for urban LST retrieval, including urban surface emissivity, atmospheric correction, radiometric calibration, and validation. In addition, we will discuss general challenges confronting the continuity of quantitative applications of Landsat observations. These challenges arise mainly from the scan line corrector failure of the Landsat 7 ETM + and channel differences among sensors. Based on these investigations, the concerns are to: (1) show general users the limitation and possible uncertainty of the retrieved urban LST from the single thermal channel of Landsat sensors; (2) emphasize efforts which should be done for the quantitative applications of Landsat data; and (3) understand the potential challenges for the continuity of Landsat observation (i.e., thermal infrared) for global change monitoring, while several climate data record programs being in progress.     

基于水足迹强度的江苏省水资源利用效率分析

水足迹强度是可以量化水资源利用效率的指标,文章在计算江苏省水足迹的基础上,选取6项水足迹强度指标,分部门比较各地市水资源利用效率的差异,并基于ESDA研究水足迹强度的空间自相关性,构建空间集聚图。研究表明:2002~2014年江苏省各市水足迹总体呈现上升趋势,水资源压力增大;总体上苏南和苏北地区的农业水足迹强度都偏高,农业水资源利用效率低;苏南地区工业产值高但耗水量大,因此工业水足迹强度也偏高;苏北地区的灰水足迹强度偏高,水资源压力较大;江苏省水足迹强度具有不断增强的全局自相关性,地市出现集聚现象,不同地市的集聚分布也日益明显;大部分苏北地区属于高高集聚并且向外扩张,低低集聚主要分布在苏南地区。研究结果为政府部门分析地市间水资源利用效率差异,制定高效的水资源利用政策等提供依据。     

A method for simplifying the analysis of traffic accidents injury severity on two-lane highways using Bayesian networks

Introduction

This study describes a method for reducing the number of variables frequently considered in modeling the severity of traffic accidents. The method's efficiency is assessed by constructing Bayesian networks (BN).

Method

It is based on a two stage selection process. Several variable selection algorithms, commonly used in data mining, are applied in order to select subsets of variables. BNs are built using the selected subsets and their performance is compared with the original BN (with all the variables) using five indicators. The BNs that improve the indicators’ values are further analyzed for identifying the most significant variables (accident type, age, atmospheric factors, gender, lighting, number of injured, and occupant involved). A new BN is built using these variables, where the results of the indicators indicate, in most of the cases, a statistically significant improvement with respect to the original BN.

Conclusions

It is possible to reduce the number of variables used to model traffic accidents injury severity through BNs without reducing the performance of the model.

Impact on Industry

The study provides the safety analysts a methodology that could be used to minimize the number of variables used in order to determine efficiently the injury severity of traffic accidents without reducing the performance of the model.     

基于数据分析的地铁智能温控系统方案设计

针对目前地铁站及地铁车辆内部的环境温度控制,提出一种通过数据分析随环境变化情况进行自动调节的智能温度控制系统方案。智能温度控制系统采用闭环控制,核心温控采用PID控制。阐述系统的设计原理、架构、关键技术、实际应用中的工作模式,说明环境因素采集预算子系统、温度实时监测子系统、温度预警和温度调整子系统的系统功能。     

遥感指数在湖泊叶绿素a反演研究中的应用

借鉴陆地植被指数的算法,利用MODIS数据的波段组合对太湖叶绿素8浓度进行反演。探讨了差值植被指数DVI、比值植被指数RVI、归一化植被指数NDVI这三种遥感指数形式的反演效果及各自特点。MODIS数据蓝光波段和红外波段的组合是反演太湖叶绿素浓度的最佳波段组合,DVI适合于反演叶绿素浓度高的情况,RVI的反演结果两极分化明显而普适性较差,NDVI适合于反演浓度较低的情况。