空间数据关联规则挖掘的不确定性处理及度量

针对传统空间数据关联规则挖掘缺乏不确定性处理及度量的局限性,将空间数据的不确定性和空间数据挖掘的不确定性有机结合,初步建立了空间数据关联规则挖掘的不确定性处理模型及度量指标,包括空间数据不确定性的Monte Carlo模拟、基于不确定性空间数据的空间自相关度量和关联规则不确定性度量等,并以我国某地区环境调查数据为例进行验证。     

地形特征与山地气候变化空间关联规则数据挖掘研究

以四川省的地形、气候为研究对象,针对山地地形特征与气候变化研究中,传统的统计分析、非线性拟合等方法缺乏分析处理海量数据和提取隐含信息能力的问题,提出将关联规则数据挖掘与栅格图像处理、地形分析相结合的研究方法。该方法利用栅格图像处理和地形分析技术,对地形和气候栅格图像进行坐标转换、裁剪、分类、因子提取、离散化等预处理,再用Apriori算法对提取的地形特征因子和气候因子进行分析,得到反映两者之间相关性的强关联规则。通过对60余万组数据的分析,得到22条满足最小支持度和置信度的关联规则,并由此综合分析得到6条复合关联规则。实验证明,这些反映地形特征与气候变化幅度之间关联性的关联规则可信度较高。     

空间关联规则挖掘研究进展

随着空间数据获取技术的进步, 空间数据量日益增大, 已超出人们的分析能力。传统的空 间数据分析方法只能进行简单的数据分析, 无法满足人们获取知识的需要。空间关联规则是空间 数据挖掘一个基本的任务, 是从具有海量、多维、多尺度、不确定性边界等特性的空间数据中进行 知识发现的重要方法。本文从基本概念、分类、挖掘过程、挖掘方法、目前研究成果等方面对其进 行综述, 重点阐述了空间关联规则挖掘效率的改进策略、基于不确定空间信息的挖掘方法、挖掘 过程及结果的可视化、弱空间关联规则的挖掘方法等。通过对现有空间关联规则研究成果和存在 问题的深入剖析, 指出了其未来主要的发展方向。     

北极水汽输送的时空分布特征研究

水汽输送可以通过直接或间接的方式影响北极地区(60°N—90°N)的水文、辐射和动力等气候因子。了解水汽输送的分布和变化特征,对研究北极气候变化具有重要意义。本文基于ERA5、JRA-55和MERRA-2再分析资料,分析了1980—2018年沿70°N水汽通量的水平分布、垂直分布和月平均分布,以及北极地区整层水汽通量在不同季节的变化特征和线性趋势。基于三种再分析资料的分析结果均表明,沿70°N的水汽输送在东北极主要为向北,在西北极为向南和向北相间分布且相对于东北极更活跃;沿70°N的向北水汽输送在垂直方向上的900hPa高度附近较为强烈。此外,沿70°N的向北水汽输送通量平均高于向南,说明了北极地区整体体现为水汽汇入地。北极地区的向北水汽输送在夏秋季比冬春季节更活跃,且夏秋季的水汽通量在向北水汽输送通道附近和北大西洋区域的增速更为明显。对沿70°N的水汽入侵的时间变化和水平分布结果进行分析后发现,水汽入侵主要发生在向北水汽输送通道附近,且水汽入侵受比湿的影响比经向风更大,这使得水汽入侵的年平均次数在2008年之后出现剧烈波动。整体上,相比ERA5和JRA-55, MERRA-2与IGR...     

北极航线的世界航运网络格局影响分析

北冰洋冰层的加速融化,引发了世界对北极航线相关问题的关注和思考,尤其是北极航线全线贯通之后,将会对当今世界航运网络格局产生更加深远的影响。本文分析了世界航运网络格局的内涵和现状,随后讨论了世界航运网络格局的要素,并以此为基础,分析了北极航线通航后对世界航运网络格局的影响,进而提出北极航线通航后我国的应对策略。     

空间关联规则在土地利用与地形特征关系研究中的应用

空间关联规则是空间数据挖掘的重要内容,其结果表明了各种空间对象之间的关联关系．本研究以福州地区作为试验区,以DEM、坡度、坡向等地形特征以及2009年福州地区土地利用现状作为基础数据,利用Apriori算法从中提取出地形特征与土地利用现状之间的关联关系,讨论并分析两者之间关联规则的提取结果及空间关联规则提取方法的优缺点;研究结果表明了2009年福州地区的土地利用现状分布,即林地多,耕地、住宅用地等偏少的情况,林地分布在各种地形上且与坡向之间无强关联性;而且对于不同的最小置信度和支持度,该算法所提取的结果有所不同,如何提高算法效率、合理的设置最小置信度和支持度以及提取结果的评价与解释等将是今后进一步研究的重点．     

空间关联规则在土地利用与地形特征关系研究中的应用

空间关联规则是空间数据挖掘的重要内容,其结果表明了各种空间对象之间的关联关系．本研究以福州地区作为试验区,以DEM、坡度、坡向等地形特征以及2009年福州地区土地利用现状作为基础数据,利用Apriori算法从中提取出地形特征与土地利用现状之间的关联关系,讨论并分析两者之间关联规则的提取结果及空间关联规则提取方法的优缺点...     

珠江三角洲腹地洪水特征变异因素的关联分析

采用关联分析法,对珠江三角洲网河区腹地代表站近期洪水位变异的各种成因的主次作用进行分析,结果表明,近期导致腹地洪水位异变的主要因素依次是,河口水流不畅和潮流顶托、西江向三角洲腹地河网分流以及三角洲网河上部水情.三角洲河口水流顶托与上游分流增加、流速加快(均与人类活动造成的河床变异有关)在腹地形成"水流挤压"共同导致腹地的异高洪水位;同时,三角洲腹地河滩占用严重,桥梁、码头建设密度大,更加剧了腹地河道水位壅高.     

甘肃省粮食生产的多尺度及关联分析

采用甘肃省1949-2011年时间尺度的粮食产量历史数据,在对粮食产量时空尺度分析的基础上,基于33 a时间序列的粮食产量及其相关的11个变量的基础数据作为样本,建立粮食生产灰色系统模型对驱动机制进行分析,期望为农业部门粮食生产决策提供科学借鉴。分析结果表明:(1)1949-2011年,甘肃省粮食生产在波动中增长;粮食总产量、人均粮食产量及单产的曲线的动态变化基本吻合;甘肃省粮食产量变化主要存在23 a、15 a左右的年代际振荡周期和准9 a的年际波动周期,其中23 a、15 a左右的振荡周期较强烈;(2)单产、农村从业人口和有效灌溉面积是甘肃省粮食生产的主要驱动力。     

中南半岛植被物候与极端降水的变化特征及关联

利用MCD12Q2数据提取中南半岛的植被物候指标,采用Sen+Mann-Kendall法、灰色关联分析及R/S分析等方法,分析中南半岛地区生长季开始、生长季结束、生长季长度及极端降水指标的时空分布特征及其关联,并预测物候指标的未来变化趋势。结果表明：1) 2001—2018年中南半岛生长季开始及结束时间均表现出东部地区早于西部的空间特征,半岛生长季长度多保持在8～9个月左右;除暴雨日数指标,极端降水指标的空间分布特征与年总降水量的空间分布相似,大致呈西高东低;2）生长季始期与生长季末期以提前趋势为主,生长季长度以缩短趋势为主;年尺度降水量与强度无明显变化,但单日最大降水量、极强降水量和暴雨日数指标呈下降趋势,中雨日数、大雨日数和连续有雨日数指标均呈上升趋势,表明中南半岛极强降水事件减少,中等强度极端事件增多,降水事件的持续时间变长;3）各物候指标的主控极端降水指标类型空间分布模式相似且集中,植被物候与区域气候密切相关;4）中南半岛各物候指标未来变化趋势与过去变化趋势相反,且以延后趋势为主。     

北极航线战略利益争夺的博弈态势与中国对策

北极航线包括东北航线、西北航线与北冰洋中央的穿极航线。作为联结亚欧最短的航运线路,北极航线独有的战略地位与潜在开发价值已吸引北极域内外国家的关注并对北极区域作出战略倾斜,北极航线由此成为各国战略利益争夺的前线阵地。虽然北极航线由于其自身地缘特征实际为北极航线沿线国家所掌控,但航线自身的公共属性决定了其战略价值的“外溢”,北极域外国家在北极航线同样具有重要的国家利益。北极航线目前存在国际规则不成体系、国内法与国际规则相冲突等矛盾,俄罗斯与加拿大将东北航线与西北航线“内水化”是造成国内外规则冲突的根本因素。中国作为北半球航运大国,北极航线的开通将进一步推动我国进出口贸易以及保障我国石油能源安全储备,对我国具有重大战略意义。由此,提升北极航运的参与度,以“负责任大国”形象与北极国家合作的方式参与北极事务以维护本国航运利益,进而推动北极航运治理规则体系的完善,是适合现实参与北极航线实践的中国对策。     

基于新闻大数据的北极地区地缘关系研究

随着全球气候变暖,北极地区海冰大面积消融,引发了严重环境问题,同时使得北极航道成为可能,北极地区的战略地位显著提升.作为近北极国家,北极地区国际关系变化对中国的北极政策有直接影响.全面实时地分析北极地区地缘关系及其变化特征,对中国制定北极地区的政治、经济、外交政策具有重要指导作用.海量全球实时开放数据库的出现以及大数据...     

Effect of shipping activity on warming trends in the Canadian Arctic

This paper presents a detailed account of the effect of shipping activity on the increasing trends of air temperatures in the Canadian Arctic region for the period of 1980–2018. Increasing trend of temperature has gained significant attention with respect to shipping activities and sea ice area in the Canadian Arctic. Temperature, sea ice area and shipping traffic datasets were investigated, and simple linear regression analyses were conducted to predict the rate of change(per decade) of the average temperature, considering winter(January) and summer(July) seasons. The results indicate that temperature generally increased over the studied region. Significant warming trend was observed during July, with an increase of up to 1℃, for the Canadian Arctic region. Such increasing trend of temperature was observed during July from the lower to higher latitudes. The increase in temperature during July is speculated to increase the melting of ice. Results also show a decline in sea ice area has a significant positive effect on the shipping traffic, and the numbers of marine vessel continue to increase in the region. The increase in temperature causes the breaking of sea ice due to shipping activities over northern Arctic Canada.     

Spatio-temporal association analysis of county potential in the Pearl River Delta during 1990-2009

According to the highway data and some socioeconomic data of 1990, 1994, 2000, 2005 and 2009 of county units in the Pearl River Delta, this paper measured urban integrated power of different counties in different years by factor analysis, and estimated each county’s potential in each year by means of expanded potential model. Based on that, the spatio-temporal association patterns and evolution of county potential were analyzed using spatio-temporal autocorrelation methods, and the validity of spatio-temporal association patterns was verified by comparing with spatial association patterns and cross-correlation function. The main results are shown as follows: (1) The global spatio-temporal association of county potential showed a positive effect during the study period. But this positive effect was not strong, and it had been slowly strengthened during 1994-2005 and decayed during 2005-2009. The local spatio-temporal association characteristics of most counties’ potential kept relatively stable and focused on a positive autocorrelation, however, there were obvious transformations in some counties among four types of local spatio-temporal association (i.e., HH, LL, HL and LH). (2) The distribution difference and its change of local spatio-temporal association types of county potential were obvious. Spatio-temporal HH type units were located in the central zone and Shenzhen-Dongguan region of the eastern zone, but the central spatio-temporal HH area shrunk to the Guangzhou-Foshan core metropolitan region only after 2000; the spatio-temporal LL area in the western zone kept relatively stable with a surface-shaped continuous distribution pattern, new LL type units emerged in the south-central zone since 2005, the eastern LL area expanded during 1994-2000, but then gradually shrunk and scattered at the eastern edge in 2009; the spatio-temporal HL and LH areas varied significantly. (3) The local spatio-temporal association patterns of county potential among the three zones presented significant disparity, and obvious difference between the eastern and central zones tended to decrease, whereas that between the western zone and the central and eastern zones further expanded. (4) Spatio-temporal autocorrelation methods can efficiently mine the spatio-temporal association patterns of county potential, and can better reveal the complicated spatio-temporal interaction between counties than ESDA methods.     

Spatio-temporal evolution and influencing factors of geopolitical relations among Arctic countries based on news big data

Global warming has caused the Arctic Ocean ice cover to shrink. This endangers the environment but has made traversing the Arctic channel possible. Therefore, the strategic position of the Arctic has been significantly improved. As a near-Arctic country, China has formulated relevant policies that will be directly impacted by changes in the international relations between the eight Arctic countries(regions). A comprehensive and real-time analysis of the various characteristics of the Arctic geog...     

Spatial co-location pattern mining of facility points-of-interest improved by network neighborhood and distance decay effects

The aim of mining spatial co-location patterns is to find the corresponding subsets of spatial features that have strong spatial correlation in the real world. This is an important technology for the extraction and comprehension of implicit knowledge in large spatial databases. However, existing methods of co-location mining consider events as taking place in a homogeneous and isotropic context in Euclidean space, whereas the physical movement in an urban space is usually constrained by a road network. Furthermore, previous works do not take the ‘distance decay effect’ of spatial interactions into account, which may reduce the effectiveness of the result. Here we propose an improved spatial co-location pattern mining method, including the network-constrained neighborhood and addition of a distance-decay function, to find the spatial dependence between network phenomena (e.g. urban facilities). The underlying idea is to utilize a model function in the interest measure calculation to weight the contribution of a co-location to the overall interest measure instance inversely proportional to the separation distance. Our approach was evaluated through extensive experiments using facility points-of-interest data sets. The results show that the network-constrained approach is a more effective method than the traditional one in network-structured space. The proposed approach can also be applied to other human activities (e.g. traffic accidents) constrained by a street network.     

Investigation of Arctic and Antarctic spatial and depth patterns of sea water in CTD profiles using chemometric data analysis

In this paper we examine 2- and 3-way chemometric methods for analysis of Arctic and Antarctic water samples. Standard CTD (conductivity–temperature–depth) sensor devices were used during two oceanographic expeditions (July 2007 in the Arctic; February 2009 in the Antarctic) covering a total of 174 locations. The output from these devices can be arranged in a 3-way data structure (according to sea water depth, measured variables, and geographical location). We used and compared 2- and 3-way statistical tools including PCA, PARAFAC, PLS, and N-PLS for exploratory analysis, spatial patterns discovery and calibration. Particular importance was given to the correlation and possible prediction of fluorescence from other physical variables. MATLAB's mapping toolbox was used for geo-referencing and visualization of the results. We conclude that: 1) PCA and PARAFAC models were able to describe data in a satisfactory way, but PARAFAC results were easier to interpret; 2) applying a 2-way model to 3-way data raises the risk of flattening the covariance structure of the data and losing information; 3) the distinction between Arctic and Antarctic seas was revealed mostly by PC1, relating to the physico-chemical properties of the water samples; and 4) we confirm the ability to predict fluorescence values from physical measurements when the 3-way data structure is used in N-way PLS regression.     

时空大数据背景下并行数据处理分析挖掘的进展及趋势

随着互联网、物联网和云计算的高速发展,与时间、空间相关的数据呈现出“爆炸式”增长的趋势,时空大数据时代已经来临。时空大数据除具备大数据典型的“4V”特性外,还具备丰富的语义特征和时空动态关联特性,已经成为地理学者分析自然地理环境、感知人类社会活动规律的重要资源。然而在具体研究应用中,传统数据处理和分析方法已无法满足时空大数据高效存取、实时处理、智能挖掘的性能需求。因此,时空大数据与高性能计算/云计算融合是必然的发展趋势。在此背景下,本文首先从大数据的起源出发,回顾了大数据概念的发展历程,以及时空大数据的特有特征;然后分析了时空大数据研究应用产生的性能需求,总结了底层平台软硬件的发展现状;进而重点从时空大数据的存储管理、时空分析和领域挖掘3个角度对并行化现状进行了总结,阐述了其中存在的问题;最后指出了时空大数据研究发展趋势。     

空间数据统计分析的思想起源与应用演化

系统总结了空间数据统计分析的发展历程,并分为五个时期：① 早期孕育（计量革命之前）,其重要思想是19世纪初德国的区位论;② 计量革命（1950-1960年代）,主要是经典统计学的应用和理论探索;③ 空间统计学（1970-1980年代）,重点是空间点数据、面数据和空间连续性数据的分析;④ 成熟与扩散（1990-2000年代）,空间数据统计分析发展成熟并快速向其他领域扩散;⑤ 时空大数据（2010年以后）。换句话说,计量革命开始后的空间数据统计分析大约每20年有重要的新技术或方法出现,到现在已经具有成熟、系统化的方法和显著的社会效益。而在当前的时空大数据时期,其发展需要计算机科学家、统计学家和地理学家等不同学科领域人员的共同努力。