A high-performance cellular automata model for urban simulation based on vectorization and parallel computing technology

Cellular automata (CA) models can simulate complex urban systems through simple rules and have become important tools for studying the spatio-temporal evolution of urban land use. However, the multiple and large-volume data layers, massive geospatial processing and complicated algorithms for automatic calibration in the urban CA models require a high level of computational capability. Unfortunately, the limited performance of sequential computation on a single computing unit (i.e. a central processing unit (CPU) or a graphics processing unit (GPU)) and the high cost of parallel design and programming make it difficult to establish a high-performance urban CA model. As a result of its powerful computational ability and scalability, the vectorization paradigm is becoming increasingly important and has received wide attention with regard to this kind of computational problem. This paper presents a high-performance CA model using vectorization and parallel computing technology for the computation-intensive and data-intensive geospatial processing in urban simulation. To transfer the original algorithm to a vectorized algorithm, we define the neighborhood set of the cell space and improve the operation paradigm of neighborhood computation, transition probability calculation, and cell state transition. The experiments undertaken in this study demonstrate that the vectorized algorithm can greatly reduce the computation time, especially in the environment of a vector programming language, and it is possible to parallelize the algorithm as the data volume increases. The execution time for the simulation of 5-m resolution and 3 × 3 neighborhood decreased from 38,220.43 s to 803.36 s with the vectorized algorithm and was further shortened to 476.54 s by dividing the domain into four computing units. The experiments also indicated that the computational efficiency of the vectorized algorithm is closely related to the neighborhood size and configuration, as well as the shape of the research domain. We can conclude that the combination of vectorization and parallel computing technology can provide scalable solutions to significantly improve the applicability of urban CA.     

When does economic development promote mitigation and why?

Is economic development compatible with mitigation? On the one hand, development should promote effective climate policy by enhancing states’ capacities for mitigation. On the other hand, economic growth creates more demand for production, thereby inhibiting emissions reduction. These arguments are often reconciled in the environmental Kuznets curve (EKC) thesis. According to this approach, development initially increases emissions in poor economies, but begins to lower emissions after a country has attained a certain level of development.

The aim of this article is to determine empirically whether the EKC hypothesis seems plausible in light of emissions trends over the birth and implementation of the Kyoto Protocol. Drawing on data from the World Bank World Development Indicators and World Resources Institute Climate Data Explorer, it conducts a large-N investigation of the emissions behaviour of 120 countries from 1990 to 2012. While several quantitative studies have found that economic factors influence emissions activity, this article goes beyond existing research by employing a more sophisticated – multilevel – research design to determine whether economic development: (a) continues to be a significant driver once country-level clustering is accounted for and (b) has different effects on different countries. The results of this article indicate that, even after we account for country-level clustering and hold constant the other main putative drivers of emissions activity, economic development tends to inhibit emissions reduction. They also provide strong evidence that emissions trends resemble the EKC, with development significantly constraining emissions reduction in the South and promoting it in the North.

POLICY RELEVANCE

This article contributes to the understanding of the (changing) role of economic development in shaping emissions activity. It demonstrates the need for a contextualized, country-specific approach for evaluating the effectiveness of economic development in promoting emissions reduction and uncovers new evidence in support of the EKC hypothesis.     

Global impact of a climate treaty if the Human Development Index replaces GDP as a welfare proxy

This study explores the implications of shifting the narrative of climate policy evaluation from one of costs/benefits or economic growth to a message of improving social welfare. Focusing on the costs of mitigation and the associated impacts on gross domestic product (GDP) may translate into a widespread concern that a climate agreement will be very costly. This article considers the well-known Human Development Index (HDI) as an alternative criterion for judging the welfare effects of climate policy. We estimate what the maximum possible annual average increase in HDI welfare per tons of CO₂ would be within the carbon budget associated with limiting warming to 2°C over the period 2015–2050. Emission pathways are determined by a policy that allows the HDI of poor countries and their emissions to increase under a business-as-usual development path, while countries with a high HDI value (>0.8) have to restrain their emissions to ensure that the global temperature rise does not exceed 2°C. For comparison, the well-known multi-regional RICE model is used to assess GDP growth under the same climate change policy goals.

Policy relevance

This is the first study that shifts the narrative of climate policy evaluation from one of GDP growth to a message of improving social welfare, as captured by the HDI. This could make it easier for political leaders and climate negotiators to publicly commit themselves to ambitious carbon emission reduction goals, such as limiting global warming to 2°C, as in the (non-binding) agreement made at COP 21 in Paris in 2015. We find that if impacts are framed in terms of growth in HDI per t CO₂ emission per capita instead of in GDP, the HDI of poor countries and their emissions are allowed to increase under a business-as-usual development path, whereas countries with a high HDI (>0.8) must control emissions so that global temperature rise remains within 2°C. Importantly, a climate agreement is more attractive for rich countries under the HDI than the GDP frame. This is good news, as these countries have to make the major contribution to emissions reductions.     

基于逐时资料的黄山雾凇特征及气象条件分析

利用2004—2016年黄山气象站逐日、逐时地面气象观测资料分析了雾凇的时间分布特征及气象条件。结果表明:(1)黄山年平均雾凇日61.6d,年份之间差异明显;雾凇初日主要在11月,终日主要在3—4月;连续雾凇日数多在3～4d,占40%,各年均出现了连续雾凇日数≥10d的情况。(2)雾凇出现在10月至次年4月,其中12月至次年3月雾凇日数占89.8%;月平均雾凇日数与月平均气温呈显著负相关。雾凇还存在一定的日变化,08:00—09:00最多,18:00最少。(3)逐日资料统计表明,适宜雾凇出现的气象条件是雾日且日平均气温在-8～2℃之间、平均相对湿度≥80%、平均风速2～9m/s。(4)逐时资料统计表明,雾凇的形成主要受气温影响,雾凇形成前需7h以上的累计低温(≤0℃),适宜雾凇形成的气象条件是有雾且气温在-6～1℃之间,湿度≥95%,风速2～11m/s,较好地反映了雾凇形成的临界气象条件。     

那曲市历年冰雹日数变化特征及冰雹、雷暴环境条件分析

利用那曲市7个国家气象观测站建站至2015年的冰雹日数资料,分析了那曲市冰雹日数时空分布特征及气候突变情况,并分析了2012—2016年色尼区单站冰雹日、雷雨日个例,揭示了色尼区冰雹、雷暴发生前的环境条件。结果表明:那曲市年平均冰雹日数呈减少趋势,减少趋势最明显的是申扎县,每10 a减少4. 9天,减少趋势最弱的为色尼区和班戈县,每10 a减少1. 9天,减少趋势均通过了0. 01的显著性检验;不同区域各代表站均显示减少趋势且出现突变现象;那曲市冰雹天气具有明显的季节特征,大多集中在6—9月;降雹时间多集中在14—20时,占全天的78%。对那曲市色尼区冰雹日和雷雨(无降雹)日个例分析表明,高原较强对流发生在0℃层高度低(多在1.5 km高度以下)、CAPE值小(多在500 J·kg~(-1)以下)、风垂直切变弱的环境下,与平原地区大冰雹环境差异显著,因而高原冰雹绝大部分为直径5 mm以下的小冰雹,严格意义上应称为霰;雷雨天气低层较雹日的更暖湿,其温度露点差略小于雹日的,露点比雹日的高,因而雹日抬升凝结高度高于雷雨日的。     

京津冀地区人口与经济协调发展关系研究

京津冀地区是中国重要的人口集聚区和经济增长极,在京津冀协同发展的背景下研究京津冀地区人口与经济的协调发展关系,对于促进区域内经济的可持续发展具有重要意义。本文基于京津冀地区2000-2010年各区(县)和2000-2014年各城市的人口、GDP数据,运用人口—经济增长弹性、地理集中度、不一致指数、重心分析等方法探究京津冀地区人口与经济的协调发展关系,结果表明：①在总量规模上,京津冀地区整体人口增长与经济增长的协调度较高,但各城市人口增长与经济增长的协调度存在较大差异。②在空间分布上,从地理集中度来看,京津冀地区人口、经济地理集中度均呈现北部低、中南部高的分布特征,其中北京、天津经济地理集中度高于人口地理集中度,河北多数城市人口地理集中度高于经济地理集中度;从重心来看,京津冀地区整体的人口与经济重心都向东北方向移动,且经济重心的移动幅度大于人口重心,2个重心偏离距离不断加大,此外各城市的人口重心与经济重心也出现不同程度的分离。最后,提出了促进京津冀地区人口与经济协调发展的政策建议。     

The geometry of space-time prisms with uncertain anchors

Space-time prisms envelop all spatio-temporal locations that moving objects may have visited between two of their known spatio-temporal locations, given a bound on their travel speed. In this context, the known locations are often the result of observations or measurements, and they are called ‘anchor points’. The classic space-time prism, in isotropic two-dimensional space, as well as in transportation networks, assumes that the measurements of these anchor points are exact. Whereas, in many applications, we can assume that time can be measured fairly precisely, this assumption is unrealistic for the spatial components of measured locations (we think of Global Positioning System (GPS) errors, for instance). In this paper, we extend the classical prism from anchor points to circular ‘anchor regions’ that capture the uncertainty or error on their measurement. We define the notion of a space-time prism with uncertain anchor points, called uncertain prism, for short. We study the geometry of uncertain prisms in an arbitrary metric space to make this concept as widely applicable as possible. We also focus on the rims of uncertain space-time prisms, which demarcate the area that a moving object can have visited between two anchor regions (given some local speed limitations).     

For your eyes only? Evaluating a coordinated and multiple views tool with a map,a parallel coordinated plot and a table using an eye-tracking approach

Geographic visualization tools with coordinated and multiple views (CMV) typically provide sets of visualization methods. Such configuration gives users the possibility of investigating data in various visual contexts; however, it can be confusing due to the multiplicity of visual components and interactive functions. We addressed this challenge and conducted an empirical study on how a CMV tool, consisting of a map, a parallel coordinate plot (PCP), and a table, is used to acquire information. We combined a task-based approach with eye-tracking and usability metrics since these methods provide comprehensive insights into users’ behaviour. Our empirical study revealed that the freedom to choose visualization components is appreciated by users. The individuals worked with all the available visualization methods and they often used more than one visualization method when executing tasks. Different views were used in different ways by various individuals, but in a similarly effective way. Even PCP, which is claimed to be problematic, was found to be a handy way of exploring data when accompanied by interactive functions.     

哈大高铁对东北城市旅游经济联系的空间影响

基于GIS平台,构建可达性模型分析哈大高铁开通后东北各城市旅游交通网络可达性变化特征,然后通过修正引力模型,从时空压缩效应、高铁旅游带的形成、旅游通勤圈空间分异、加剧旅游极化效应等方面分析哈大高铁对东北各城市间旅游经济联系的影响。结果显示：高铁带来的时空压缩效应大大强化了东北城市的旅游交通可达性和旅游经济联系,整个通勤圈时空压缩2 h左右,提升幅度均呈现距离高铁增加而衰减现象,且省际城市间的变化大于省内城市间的变化,东三省的变化大于内蒙东部区域的变化。沿线城市在高铁开通后将获得更大的旅游发展动能,并加快哈大高铁旅游带的形成。沿线城市“一日游”和“两日游”受益明显,偏远城市则在“七日游”方面受益较多;东北旅游应以高铁为契机,精心开发沿线旅游精品线路,加快旅游一体化合作,打造东北旅游新形象。高铁使旅游市场空间分布上出现“极化效应”,提升旅游产业供求效率的同时,拉大了城市间旅游差距,不利于旅游产业协调性发展。今后应以高铁为核心完善快速交通干线布局,将更多旅游城市和旅游景点纳入高铁通勤圈。     

当代中国的全球观念与全球战略

简要叙述了“一带一路”战略对于中国崛起的重大意义,分析了当今全球地缘政治的基本格局、重要区域（国家）的地缘政治倾向及与中国发展经贸和产能合作可能的前景,指出了“一带一路”战略实施中可能将遇到的问题,并就加强“一带一路”研究及资料收集、整理、管理工作提了建议。