Mapping spatiotemporal patterns of events using social media: a case study of influenza trends

Tracking spatial and temporal trends of events (e.g. disease outbreaks and natural disasters) is important for situation awareness and timely response. Social media, with increasing popularity, provide an effective way to collect event-related data from massive populations and thus a significant opportunity to dynamically monitor events as they emerge and evolve. While existing research has demonstrated the value of social media as sensors in event detection, estimating potential time spans and influenced areas of an event from social media remains challenging. Challenges include the unstable volumes of available data, the spatial heterogeneity of event activities and social media data, and the data sparsity. This paper describes a systematic approach to detecting potential spatiotemporal patterns of events by resolving these challenges through several interrelated strategies: using kernel density estimation for smoothed social media intensity surfaces; utilizing event-unrelated social media posts to help map relative event prevalence; and normalizing event indicators based on historical fluctuation. This approach generates event indicator maps and significance maps explaining spatiotemporal variations of event prevalence to identify space-time regions with potentially abnormal event activities. The approach has been applied to detect influenza activity patterns in the conterminous US using Twitter data. A set of experiments demonstrated that our approach produces high-resolution influenza activity maps that could be explained by available ground truth data.     

Automatic change detection in lane-level road networks using GPS trajectories

Lane-level road network updating is crucial for urban traffic applications that use geographic information systems contributing to, for example, intelligent driving, route planning and traffic control. Researchers have developed various algorithms to update road networks using sensor data, such as high-definition images or GPS data; however, approaches that involve change detection for road networks at lane level using GPS data are less common. This paper presents a novel method for automatic change detection of lane-level road networks based on GPS trajectories of vehicles. The proposed method includes two steps: map matching at lane level and lane-level change recognition. To integrate the most up-to-date GPS data with a lane-level road network, this research uses a fuzzy logic road network matching method. The proposed map-matching method starts with a confirmation of candidate lane-level road segments that use error ellipses derived from the GPS data, and then computes the membership degree between GPS data and candidate lane-level segments. The GPS trajectory data is classified into successful or unsuccessful matches using a set of defuzzification rules. Any topological and geometrical changes to road networks are detected by analysing the two kinds of matching results and comparing their relationships with the original road network. Change detection results for road networks in Wuhan, China using collected GPS trajectories show that these methods can be successfully applied to detect lane-level road changes including added lanes, closed lanes and lane-changing and turning rules, while achieving a robust detection precision of above 80%.     

青海省柴达木地区钾肥生产企业粉尘、噪声主要职业病危害的调查分析

青海是我国资源较为丰富的省份,钾盐资源的开发及钾肥生产在国内占有重要地位。随着青海高原地区盐湖钾肥产业的迅速发展,相关部门对该行业职业卫生、职业病防治工作日渐重视。通过大量的现场数据收集、整理,对青海高原地区盐湖钾肥行业作业人员面临的职业病危害因素、健康安全等相关问题进行了总结和分析,提出了有针对性的防范措施。     

Understanding spatial structures and organizational patterns of city networks in China: A highway passenger flow perspective

The use of multi-perspective and multi-scalar city networks has gradually developed into a range of critical approaches to understand spatial interactions and linkages. In particular, road linkages represent key characteristics of spatial dependence and distance decay, and are of great significance in depicting spatial relationships at the regional scale. Therefore, based on highway passenger flow data between prefecture-level administrative units, this paper attempted to identify the functional structures and regional impacts of city networks in China, and to further explore the spatial organization patterns of the existing functional regions, aiming to deepen our understanding of city network structures and to provide new cognitive perspectives for ongoing research. The research results lead to four key conclusions. First, city networks that are based on highway flows exhibit strong spatial dependence and hierarchical characteristics, to a large extent spatially coupled with the distributions of major megaregions in China. These phenomena are a reflection of spatial relationships at regional scales as well as core-periphery structure. Second, 19 communities that belong to an important type of spatial configuration are identified through community detection algorithm, and we suggest they are correspondingly urban economic regions within urban China. Their spatial metaphors include the administrative region economy, spatial spillover effects of megaregions, and core-periphery structure. Third, each community possesses a specific city network system and exhibits strong spatial dependence and various spatial organization patterns. Regional patterns have emerged as the result of multi-level, dynamic, and networked characteristics. Fourth, adopting a morphology-based perspective, the regional city network systems can be basically divided into monocentric, dual-nuclei, polycentric, and low-level equilibration spatial structures, while most are developing monocentrically.     

Assessment of efficiency and potentiality of agricultural resources in Central Asia

This paper quantitatively analyzes the utilization efficiency of agricultural resources in Central Asia by calculating the consumption coefficient of the main resources, including arable land, water and fertilizers. The results of these investigations reveal the following: (1) The average consumption coefficients of cultivated land resources in Central Asia are much higher than the world average value of up to 7.74 m²/kg, which is 3.6 times that of China, suggesting that the cultivated land resource consumption coefficient of cultivated land resource utilization efficiency is low in the Central Asian region. (2) Up to 80% of available water Central Asia is about 9.43 m³/kg, or nearly 9.3 times the average value elsewhere in Asia, indicating that agricultural water use efficiency in this region is very low and water resources are wasted. (3) The fertilizer consumption coefficient in Central Asia is 0.035 kg/kg, which is close to the world average, but the utilization efficiency of fertilizer is relatively high. Therefore, in the future development of agriculture, Central Asia should pay more attention to the management of agricultural water resources in order to improve the utilization efficiency of these resources as well as that of arable land.     

Exploring the potential of circular economy to mitigate pressures on biodiversity

The effects of circular economy on biodiversity are poorly understood. This study provides observations on approaches for assessing circular economy and illustrates, with a Finnish case study, the potential of circular economy to mitigate pressures on biodiversity. The case study focuses on the construction and real estate sectors, as well as the forest industry. The findings imply that circular economy actions that reduce the extraction of virgin raw materials and relieve land use pressures are effective. Improving material efficiency, increasing the cascading use of wood, and optimizing the use and reuse of materials and products, as well as extending the lifetime of buildings and optimizing space use, have good potential for mitigating pressures on biodiversity in Finland. However, as forest utilization has a major impact on Finnish biodiversity, certain actions that possibly increase the use of forest resources (e.g., replacing fossil-based, concrete, or steel materials with wood-based solutions) may impair biodiversity if biodiversity-enhancing forest management practices are not utilized. Assessing the biodiversity impacts of circular economy is challenging, and the need for further research and the development of indicators and assessment methods is clear.     

Analysis on Precipitation Efficiency of the “21.7” Henan Extremely Heavy Rainfall Event

A record-breaking heavy rainfall event that occurred in Zhengzhou, Henan province during 19–21 July 2021 is simulated using the Weather Research and Forecasting Model, and the large-scale precipitation efficiency(LSPE) and cloud-microphysical precipitation efficiency(CMPE) of the rainfall are analyzed based on the model results. Then, the key physical factors that influenced LSPE and CMPE, and the possible mechanisms for the extreme rainfall over Zhengzhou are explored. Results show that water v...     

长江经济带城乡一体化对能源效率的空间效应分析

城乡一体化作为新的经济增长动能,是建设高效的能源经济体系、平衡经济社会发展与生态环境保护的关键性途径。因此城乡一体化对能源效率的效应分析成为促进经济社会可持续发展的重要课题。本文以长江经济带各省市为研究对象,采用DEA测度了考虑非期望产出的能源效率值,并分析其时空上的分异特征,通过构建经济、社会和基础设施3个维度的综合指标体系评价城乡一体化水平,以此为基础运用Moran's I指数确定了能源效率、城乡一体化水平及其他影响因素的空间相关性,最后运用混合地理加权回归估计城乡一体化及3个控制变量的回归参数值并作空间效应分析。得出结论:① 从空间相关性分析来看,长江经济带的城乡一体化发展水平对能源效率具有正向作用,同时经济发展水平和产业结构也对能源效率有正向影响,而技术进步则在一定条件下与能源效率呈负相关关系;② 从回归系数的估计值来看,城乡一体化对能源效率的影响程度要小于技术进步和产业结构,而经济发展水平对能源效率的影响程度最小;③ 城乡一体化水平对能源效率的正向影响程度随着能源效率的上升呈现出先上升后下降的趋势,并且其影响在空间分布上自东向西呈现出递增的特征;④ 长江经济带的能源效率呈现显著的空间相关性和空间异质性。基于此,对长江经济带推进城乡一体化进程中的能源效率提升具有重要意义。     

相关观测值双因子抗差估计的改进算法

由于一个观测值的粗差将影响多个观测值的残差估值,对双因子抗差估计的迭代计算方法作如下改进：当最大标准化残差的检验结果为粗差或者明显是可疑粗差时,只对粗差观测值构建双因子等价权,其他观测值的权不变。除上述两种情况外,可同时对所有观测值构建双因子等价权进行抗差估计,并基于改进的双因子等价权构建方法简化计算步骤。利用GPS控制网的观测数据进行模拟计算分析表明,该改进算法在含有明显粗差时可提高参数估值的精度;在粗差不明显或个数较少时,可在保持参数估计精度的基础上提高计算效率。     

一种估计粗差大小的新方法——先验方差待定参数法

提出一种利用先验方差信息进行测量数据处理中粗差估计的新方法——先验方差待定参数法。该方法无需进行最小二乘和假设检验,计算简便。从基本原理出发,给出其数学模型,然后通过3个算例,与QUAD法等其他常用的粗差估计方法进行对比,证明该方法的可靠性和实用性。