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。     

Development and case study of a science-based software platform to support policy making on air quality

This article describes the development and implementations of a novel software platform that supports real-time, science-based policy making on air quality through a user-friendly interface. The software, RSM-VAT, uses a response surface modeling (RSM) methodology and serves as a visualization and analysis tool (VAT) for three-dimensional air quality data obtained by atmospheric models. The software features a number of powerful and intuitive data visualization functions for illustrating the complex nonlinear relationship between emission reductions and air quality benefits. The case study of contiguous U.S. demonstrates that the enhanced RSM-VAT is capable of reproducing the air quality model results with Normalized Mean Bias < 2% and assisting in air quality policy making in near real time.     

基于GPRS网络的环境自动监控数据传输系统的设计

分析了江苏省环境自动监控系统数据传输的现状，提出了一种基于GPKS网络的环境自动监控数据传输系统，并进行了详细的设计。     

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。     

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.     

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.     

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。     

中国木材产业发展的阶段识别及时空分异特征

论文基于产业生命周期理论及探索性空间数据分析方法,运用1954—2014年各省木材产量数据对中国木材产业的发展阶段以及时空格局变化规律展开了分析。研究表明：1） Gompertz模型显示木材产业处于产业生命周期的成长阶段;2）探索性空间数据分析显示木材产业具有明显的地域转移趋势和显著的区域聚集特征,尤其在2000年以后,南方集体林区逐渐形成了木材生产“热点”;3）根据重心模型显示的移动轨迹,可以将木材产业发展分为三个时期,即经济驱动时期、经济驱动与生态驱动相持时期、生态驱动时期,木材产业的时空格局演变是这两种驱动力量相对均衡的结果。根据研究结论,提出了重视森林资源培育、适时放开采伐限额、由行政监督向购买社会服务转变等促进木材产业发展的建议。     

水环境DSS系统中数据集市的开发应用

水环境综合整治是一种投资巨大、影响深远的系统工程,需要进行科学决策.近来年水环境决策支持技术发展很快,而作为其中两大支柱之一,水环境数据库的开发日益受到重视.数据仓库、数据集市等技术是对数据库技术的重要发展.为此在水环境数据库之上开发水环境数据集市进行了探讨.将已有的水环境数据库,按照水环境综合整治的主题,采取星型模型进行重新组织,即生成水环境数据集市.介绍了ECTL工具的开发,即将数据库转换为数据集市的抽取(Extract)、清洗(Cleanse)、转换(Transform)、装载(Load)工具;然后介绍了OLAP(OnLine Analytical Processing)工具的开发,即为实现对数据集市的应用而开发相应的联机分析处理工具,相应的联机分析功能包括查询、分类、可视化等.通过应用实例展示了水环境数据集市提供决策支持信息的能力.