2005年登陆我国热带气旋特征分析

热带气旋是影响我国沿海的主要灾害性天气系统之一, 它产生的狂风、暴雨、巨浪和风暴潮, 给沿岸地区人民生命和国家财产安全带来严重威胁。而严重的台风灾害, 往往是台风登陆引起的。为进一步研究登陆热带气旋的活动规律, 总结了2005年登陆我国热带气旋的特点, 结果表明:2005年登陆我国热带气旋具有登陆季节短、登陆地点分布异常、台风比例异常偏高、灾害损失极为严重的特点。同时, 还讨论了2005年登陆我国热带气旋异常的气候原因, 并指出未来几年登陆热带气旋和台风的年频数处在上升趋势中。     

气象因子对半冬性小麦灌浆速度的影响效应研究

选用黄淮海冬麦区4个半冬性小麦品种郯麦98、山农18、徐麦33、皖麦52为试验材料,通过分期播种试验,利用方差分析、相关分析、逐步回归和通径分析等方法,分析半冬性小麦籽粒灌浆速度变化趋势和气象因子对灌浆速度的影响。结果表明,正常播期冬小麦灌浆速度波动性最小、千粒重最大,迟播10 d冬小麦灌浆速度波动性最大、千粒重最小;华北区品种郯麦98灌浆速度表现最稳定、千粒重最高,而黄淮区品种皖麦52灌浆速度最大;半冬性小麦灌浆持续期为35～39 d;南北气候差异是影响各品种冬小麦灌浆速度不同的原因之一。半冬性小麦各播期灌浆速度的变化趋势一致,灌浆速度变化与相关显著气象因子的变化规律相符合;灌浆速度峰值期一般出现在开花后15～25 d,迟播冬小麦最大灌浆速度出现时间较对照处理提前,不利于提高粒重;气温条件对冬小麦灌浆速度影响显著,其中最高气温要素是影响不同播期品种灌浆速度的共有关键因子。通径分析表明,最高气温对灌浆速度的作用由自身的直接效应决定,而日照时数与最低气温对灌浆速度的作用与间接效应一致;最高气温平均值对灌浆速度的影响最重要,日照时数和最低气温平均值对灌浆速度的影响较弱;最高和最低气温平均值、日照时数均为灌浆速度的限制因子,其中最高气温平均值对灌浆速度变化的决策作用最大。     

夏半年川西高原600 hPa低涡活动特征

600 hPa天气系统能够分析川西高原低涡变化的主要特征,并能识别低涡的发展移动和川西高原强降水落区的关系。利用1979—2020年逐3 h的ERA5再分析资料(0.25°×0.25°)和2011—2020年逐小时降水资料,对夏半年川西高原600 hPa低涡活动特征、低涡与降水的关系及致雨低涡动力和热力特征进行统计分析,结果表明：(1)42年间低涡年均80个,持续时间1 d以内占总数的95.7%;在川西高原本地生成、移入和移出低涡年均61.5个、18个和5.3个;低涡源地和消散地分别在甘孜州白玉县和理塘县为中心的区域。(2)生命史大于12 h的低涡占比36.4%,都会带来降水,其中超83.7%会造成中雨以上降水;低涡伴随的日降水强度最大值中心位置随月份先由川西高原东部与南部地区北移到中部,之后逐渐移回到东部与南部地区,相对应7—8月多低涡从北部南移到中部摆动消亡,其余月份多低涡从中部生成影响到东部和南部地区或在南部生成并停滞或摆动。(3)强烈垂直上升运动和正涡度区的耦合发展以及深厚不稳定层结的形成和加强是致雨低涡发生发展并产生强降水的动力特征和热力层结条件。     

基于图像处理的自动野外救援系统设计

针对野外救援的不及时性,结合人工智能等技术的应用,提出了一种新的自动野外救援系统.人类在野外和海上活动中受困后,除了依靠自身能力和装备进行求生之外,外部的有效及时救援是提高生存几率的关键.自动野外救援系统,由自动报警装置、手动报警装置实现报警,触发整个系统的运行.自动救援装置可以通过定位模块实现定位,通过执行器移动到随身装置附近实现救援,随身装置还可以发出信标导引信号;自动救援装置还可以通过传感器检测信标,通过相位检测技术等计算待救者的坐标并规划路径,实现更精准的定位与救援.     

贸易保护、出口溢出效应与中国出口市场拓展

在国际贸易摩擦不断升级的背景下,厘清贸易保护对中国区域经济发展的影响是中国当前面临的重要议题。既有演化经济地理学框架主要从供给视角出发,认为出口产品路径演化过程呈现依赖技术知识溢出的特征,忽略了需求视角的影响。基于中国海关库2002—2016年的数据,以中国出口产品进入新市场的演化路径为研究对象,本文将供需视角纳入同一解释框架,补充需求视角下的外部市场关联以及需求市场的贸易壁垒措施作为外部力量,试图探究贸易保护、出口溢出效应如何作用于中国出口市场拓展过程。研究发现:①在出口产品结构升级的同时,中国出口目的地结构也在不断地向新兴市场国家和地区拓展。其中,东部与中部地区是出口拓展的主力区域,技术与资本密集型产品是出口拓展的主要产品类型。②中国出口市场的拓展进程呈现出典型的路径依赖特征,包括供给视角下基于本地技术知识溢出的路径依赖与需求视角下基于目的地市场信息溢出的路径依赖。其中后者被长期忽视,但在中国出口市场拓展进程中扮演着十分重要的角色。③贸易保护作为一种外部冲击,可有效地削弱基于本地技术知识溢出和外部市场信息溢出的路径依赖。采用投资、区域合作等方式绕开贸易壁垒,实现出口产品与市场结构的...     

旅游产业生长点的SGGT模式与空间演化——以张家界为例

界定了旅游产业生长点的概念,借鉴“路径依赖”理论重新诠释旅游地产业成长路径,提出具有普遍性SGGT模式,以张家界旅游产业生长点为例,具体分析了SGGT和空间演化过程及其动力机制。结果发现:①历史与现实是武陵源旅游生长点形成的基础,需求与培育是旅游生长点萌发的关键因素,创新与拓展是旅游生长点成长的保证,蜕变促进了旅游生长点成为旅游产业增长极;②张家界国家森林公园、天子山和索溪峪三个旅游生长点,通过“路径创造”,实现了行政管辖权的统一,后被列为世界遗产地,成为张家界旅游产业的核心生长点;③在旅游产业“集聚力”和世界遗产地管控的驱动下,天门山成为张家界新的生长点;④武陵源和天门山两个生长点的形成,是张家界旅游产业集聚和“路径创造”共同作用的结果,也拓展了张家界旅游产业的成长空间。本文有利于为旅游地政府和企业从旅游产业生长点视角理解旅游产业成长路径,更为世界遗产地旅游产业可持续发展提供科学指导。     

Finding shortest paths on real road networks: the case for A*

The problem of identifying the shortest path along a road network is a fundamental problem in network analysis, ranging from route guidance in a navigation system to solving spatial allocation problems. Since this type of problem is solved so frequently, it is important to craft an approach that is as efficient as possible. Based upon past research, it is generally accepted that several efficient implementations of the Dijkstra algorithm are the fastest at optimally solving the ‘one‐to‐one’ shortest path problem (Cherkassky et al. 1996 Cherkassky, B. V., Goldberg, A. V. and Radzik, T. 1996. Shortest paths algorithms: theory and experimental evaluation.. Mathematical Programming: Series A and B, 73: 129–174. [Crossref], [Web of Science ®] , [Google Scholar]). We show that the most efficient state‐of‐the‐art implementations of Dijkstra can be improved by taking advantage of network properties associated with GIS‐sourced data. The results of this paper, derived from tests of different algorithmic approaches on real road networks, will be extremely valuable for application developers and researchers in the GIS community.     

Exploring space–time paths in physical and social closeness spaces: a space–time GIS approach

Exploring the evolution of people’s social interactions along with their changing physical locations can help to achieve a better understanding of the processes that generate the relationships between physical distance and social interactions, which can benefit broad fields of study related to social networks. However, few studies have examined the evolving relationships between physical movements and social closeness evolution. This is partially related to the shortage of longitudinal data in both physical locations and social interactions and the lack of an exploratory analysis environment capable of effectively investigating such a process over space and time. With the increasing availability of sociospatiotemporal data in recent years, it is now feasible to examine the relationships between physical separation and social interactions at the individual level in a space–time context. This research was intended to offer a spatiotemporal exploratory analysis approach to address this challenge. The first step was to propose the concept of a social closeness space–time path, which is an extension of the space–time path concept in time geography, to represent evolving human relationships in a social closeness space. A space–time geographical information system (GIS) prototype was then designed to support the representation and analysis of space–time paths in both physical and social closeness spaces. Finally, the effectiveness of the proposed concept and design in gaining insight into the impact of physical migration on online social closeness was demonstrated through an empirical study. The contributions of this study include an extension of the time–geographic framework from physical space to social closeness space, the development of a multirepresentation approach in a GIS to integrate an individual’s space–time paths in both physical and social closeness spaces, and an exploratory analysis of the evolving relationships between physical separation and social closeness over time.     

An improved ant colony optimization (I-ACO) method for the quasi travelling salesman problem (Quasi-TSP)

Traveling salesman problem (TSP) and its quasi problem (Quasi-TSP) are typical problems in path optimization, and ant colony optimization (ACO) algorithm is considered as an effective way to solve TSP. However, when the problems come to high dimensions, the classic algorithm works with low efficiency and accuracy, and usually cannot obtain an ideal solution. To overcome the shortcoming of the classic algorithm, this paper proposes an improved ant colony optimization (I-ACO) algorithm which combines swarm intelligence with local search to improve the efficiency and accuracy of the algorithm. Experiments are carried out to verify the availability and analyze the performance of I-ACO algorithm, which cites a Quasi-TSP based on a practical problem in a tourist area. The results illustrate the higher accuracy and efficiency of the I-ACO algorithm to solve Quasi-TSP, comparing with greedy algorithm, simulated annealing, classic ant colony algorithm and particle swarm optimization algorithm, and prove that the I-ACO algorithm is a positive effective way to tackle Quasi-TSP.     

基于耗费场的最优路径算法研究

在GIS中,有一类应用是基于连续分布耗费场的最优路径计算问题,如公路选线等。该文首先采用规则格网对耗费场进行建模,进而基于规则格网表现,分别建立网络实现模型和元胞自动机实现模型,并探讨了基于元胞自动机模型的最优路径算法,通过实例研究,说明了算法的正确性。