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1.
地理空间数据本质特征语义相关度计算模型 总被引：1，自引：1，他引：0
关联数据是跨网域整合多源异构地理空间数据的有效方式,语义丰富的关联是准确、快速发现目标数据的关键。根据地理空间数据在空间、时间、内容上的语义关系,提出地理空间数据本质特征语义相关度计算模型。通过构建本质特征的关联指标体系,分层次逐级计算地理空间数据的语义相关度。与传统的语义相关度计算方式不同,以地理元数据为语料库,充分考虑地理空间数据的特点及空间、时间、内容在检索中不同的重要程度,分别采用几何运算、数值运算、词语语义相似度计算和类别层次相关度计算的方式,构建地理空间数据的语义相关度计算模型。该模型具有构建简单、适用于多源异构数据、充分结合了数学运算和专家经验知识等特点。实验表明：模型能够有效地计算地理空间数据本质特征的语义相关度,并具备一定的扩展性。 相似文献
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城市作为组织结构复杂的开放人地地域系统,一直是地理学的研究核心之一。论文以2000—2020年相关文献为数据源,构建一套定量分析与定性认知相结合的文献分析判读体系,基于地理学视角从概念内涵、研究主题、技术方法等方面综述城市复杂性研究成果并开展讨论。过去20 a来,中国的城市复杂性研究逐渐从单尺度的格局、过程和机制研究转向于多尺度下复杂交互过程的集成与综合研究,并逐步形成了城市设施网络、城市人居环境、城市经济活动以及城市空间治理4个主要主题,在数据方法上逐步转向于空间技术及社会计算支持下的全景式全生命周期数据支撑的多维场景化分析。今后及未来一段时期,地理学视角下的城市复杂性研究需要进一步加强城市数字基础设施建设及全周期信息采集能力,加深对城市生态经济体系的综合测度及监控,增强跨区域发展机制影响下的城市流空间研究。 相似文献
3.
地理空间元数据关联网络的构建 总被引：1，自引：1，他引：0
利用资源描述框架（RDF）设计地理空间元数据关联模型,根据地理空间元数据之间的语义关系和语义相关度的计算,以构建以元数据为节点、元数据之间的语义关系为边、语义相关度为权重的关联网络。在这一网络中,一个节点是一个地理空间元数据的资源描述图,包含属性特征（数据来源、空间特征、时间特征、内容）及其关系特征（元数据之间的语义关系、语义相关度）。实验及其分析表明,地理空间元数据关联网络可以有效地支持地理空间数据语义关联检索、推荐等应用,这与传统的基于关键词的元数据检索方式相比,具有更高的准确度。 相似文献
4.
《Singapore journal of tropical geography》2018,39(1):45-61
Decentralization of governance and natural resource management is an ongoing process in many parts of Africa and Asia. Natural resource management requires spatial land resource data for planning. However, currently the financial and human capacity for natural resource mapping, monitoring and modelling remains low in local governments. In this context, this paper explores how new opportunities provided by the increasing availability of free satellite imagery, digital elevation data and open source spatial analysis software, can be applied by local government and NGOs to conduct sophisticated natural resource mapping and modelling in ways that meet their needs and incorporates local knowledge. Reported are cases of a local government using free geospatial data and GIS software to improve evidence‐based natural resource management in the developing world with a focus on raster data applications for satellite image analysis and terrain modelling. It is argued that, through removing barriers to uptake, such applications provide a means of decentralizing landscape analysis skills to improve local natural resource management. This hypothesis is supported through examples of a local government applying these tools in eastern Indonesia, and within this context barriers to wider adoption are explored. 相似文献
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空间数据立方体的多维数据组织及存储 总被引：1，自引：1，他引：0
邹逸江 《地理与地理信息科学》2006,22(5):26-30
定义空间数据立方体地理空间维、专题维和时间维分别包含的数据种类和内容;设计它们的维和维层次数据结构;表述地理空间维、专题维和时间维在概念层次和物理层次上构成空间数据立方体的方法;确定地理空间维、专题维和时间维数据的多维数组组织方法,以及多维数据的数据文件和虚拟内存存储策略;表达多维数组中记录间的关联运算和多维数组的压缩方法。 相似文献
6.
Lianfa Li Corresponding author Jinfeng Wang Chengyi Wang 《International journal of geographical information science》2013,27(3):363-384
In disaster insurance and reinsurance, GIS has been used to visualize and manage geospatial data and to help vulnerability and risk analysis for years. However, hazard insurance is a multidisciplinary issue that involves complex factors and uncertainty. GIS, if used alone, has limited functionality due to poor incorporation of intelligence and spatial statistics. The Spatial Decision Support System (SDSS) presented in this paper, addresses some of the deficiencies of traditional GIS, by providing powerful tools to support disaster insurance pricing that involves procedural and declarative knowledge. In the SDSS, the knowledge‐based system shell, using the open‐source CLIPS and supporting fuzziness and uncertainty, can be applied in at least three phases: hazard simulation, fuzzy comprehensive evaluation of risk, and query for insurance pricing. The libraries of statistics and spatial statistics provide a robust support for analysis of spatial factors, including spatial correlation between zones vulnerable to hazard and spatial variation of exposures. The GIS components provide sophisticated visualization and database management support for geospatial data, helping easily locate the insured points and risk zones as well as exploratory analysis of spatial data. Standard database management interfaces are used to manage other aspatial data. COM, an industry‐wide interface protocol, tightly integrates these technologies (the expert shell, GIS, spatial statistics and DBM within an integral system), and can be used to develop mixed complex algorithms in support of other COM objects. An application of typhoon insurance pricing is demonstrated with a case study in Guangdong, China. Developed as a suite of generic tools with abilities to deal with the complex problem of disaster insurance involving spatial factors and field knowledge, this prototype SDSS can also be applied to other disaster insurance and fields that involve similar spatial decision making. 相似文献
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Object-based spatial cluster analysis of urban landscape pattern using nighttime light satellite images: a case study of China 总被引：1，自引：0，他引：1
Bailang Yu Song Shu Hongxing Liu Wei Song Jianping Wu Lei Wang 《International journal of geographical information science》2014,28(11):2328-2355
Previous studies have demonstrated urban built-up areas can be derived from nighttime light satellite (DMSP-OLS) images at the national or continent scale. This paper presents a novel object-based method for detecting and characterizing urban spatial clusters from nighttime light satellite images automatically. First, urban built-up areas, derived from the regionally adaptive thresholding of DMSP-OLS nighttime light data, are represented as discrete urban objects. These urban objects are treated as basic spatial units and quantified in terms of geometric and shape attributes and their spatial relationships. Next, a spatial cluster analysis is applied to these basic urban objects to form a higher level of spatial units – urban spatial clusters. The Minimum Spanning Tree (MST) is used to represent spatial proximity relationships among urban objects. An algorithm based on competing propagation of objects is proposed to construct the MST of urban objects. Unlike previous studies, the distance between urban objects (i.e., the boundaries of urban built-up areas) is adopted to quantify the edge weight in MST. A Gestalt Theory-based method is employed to partition the MST of urban objects into urban spatial clusters. The derived urban spatial clusters are geographically delineated through mathematical morphology operation and construction of minimum convex hull. A series of landscape ecologic and statistical attributes are defined and calculated to characterize these clusters. Our method has been successfully applied to the analysis of urban landscape of China at the national level, and a series of urban clusters have been delimited and quantified. 相似文献
8.
珠江三角洲都市经济区地域构成的判别与分析 总被引：7，自引：1，他引：6
随着经济全球化和城市化进程的加快, 单个城市的竞争逐渐转变为城市区域的竞争。 都市经济区是在国家战略需求的推动下应势而生的新概念, 已经广泛应用于全国国土规划和 主体功能区划。准确把握都市经济区内部的地域构成有助于进行有效地加强区域管理和空间调控。以往的相关研究主要集中于宏观分析或以区县为单元的空间分析, 从功能空间的角度对都市经济区内部地域构成的研究较少, 更缺少准确科学的划分和判读方法。为了准确把握 区域空间利用中的主要问题和潜在威胁, 规划者和政府官员需要探索判定都市经济区地域构成的新方法。文章在总结当前几种主要的地域类型判读方法优缺点的基础上, 深入探讨了运 用遥感和GIS 手段进行区域地域构成判别的思路, 并成功应用于珠江三角洲内部地域构成的 空间分析。研究发现, 当前珠江三角洲都市经济区正经历着大规模的城镇化, 大都市的发展 无序蔓延, 存在的用地粗放、结构混杂、功能有待优化等问题, 工业区、居住区等用地的空 间分布呈现较明显的向心型分布和交通导向型分布特征, 同种地域类型的集聚性分布明显增强。通过从单要素和整体特征上认识和把握珠江三角洲地域构成与空间组织特征, 可以有的放矢地进行空间管理和调控。还有助于深化区域地域构成的认识和空间结构的监测和分析, 也可作为制定土地利用政策的依据, 为从区域尺度上制定空间政策提供了新的参考依据。 相似文献
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地理空间中不同分层抽样方式的分层效率 与优化策略 总被引：11，自引：1，他引：10
地理空间对象中分层抽样的效率受抽样总体的空间相关性特征限制,分层效率的提高源于两个方面,一是 抽样总体的空间相关性会使分散的样本布局精度得到提高,二是先验知识使层内方差变小,只有在空间相关性特 征较强时,追逐先验知识的分层方式才会比任意分层方式具有更好的分层效率,当空间相关性较弱时,知识分层并 不会比任意分层得到更高的抽样精度,地理空间相关性特征对分层抽样设计有重要影响,而这在实际应用中往往 被忽视。本文采用蒙特卡罗模拟抽样方法以山东省1985 年和1995 年细小非耕地地物面积比例的抽样调查为例分 析了空间相关性特征对不同分层方式抽样效率的影响,并提出了地理空间对象中分层方式的优化选择策略。 相似文献
11.
Geospatial data and tools are key in locating lost or missing persons in as short a time as possible. In this study, we used a geographic information system (GIS) to analyze four years of search and rescue (SAR) mission data from Colorado to determine the appropriate use of GIS for volunteer-based SAR organizations with limited resources and GIS expertise. GIS can provide more sophisticated analyses of geospatial data than simple mapping technologies, but our findings indicated that complex spatial analysis might not be required on all missions, because the majority of missions were completed within six to ten hours. Instead, new technologies such as tablets with mapping software and online GIS systems that provide quick and easy access to up-to-date geospatial data such as imagery offer capabilities that could improve mission planning. Here we provide a framework in which SAR missions can apply geospatial technologies to aid with missions, identify critical “hotspots,” and enhance postanalysis and training. The work here is highly applicable for nonprofit SAR groups when deciding on what GIS technologies to consider for their areas. 相似文献
12.
Xiaoping Liu Jialv He Jinbao Zhang Haolin Liang Huan Wang 《International journal of geographical information science》2017,31(8):1675-1696
Urban land use information plays an important role in urban management, government policy-making, and population activity monitoring. However, the accurate classification of urban functional zones is challenging due to the complexity of urban systems. Many studies have focused on urban land use classification by considering features that are extracted from either high spatial resolution (HSR) remote sensing images or social media data, but few studies consider both features due to the lack of available models. In our study, we propose a novel scene classification framework to identify dominant urban land use type at the level of traffic analysis zone by integrating probabilistic topic models and support vector machine. A land use word dictionary inside the framework was built by fusing natural–physical features from HSR images and socioeconomic semantic features from multisource social media data. In addition to comparing with manual interpretation data, we designed several experiments to test the land use classification accuracy of our proposed model with different combinations of previously acquired semantic features. The classification results (overall accuracy = 0.865, Kappa = 0.828) demonstrate the effectiveness of our strategy that blends features extracted from multisource geospatial data as semantic features to train the classification model. This method can be applied to help urban planners analyze fine urban structures and monitor urban land use changes, and additional data from multiple sources will be blended into this proposed framework in the future. 相似文献
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中国城市群多中心网络的拓扑结构 总被引：6，自引：1，他引：5
在既有理论基础上扩展了城市群多中心网络的度量工具,考察中国12个城市群总部—分支机构的企业关联网络,比较梳理了地级城市空间联系的拓扑结构。实证研究发现：①包括长三角、珠三角和京津冀三大典型城市群在内,中国城市群内部网络系统的拓扑结构依然发育不完善,在联系数据方面均呈现出一定的稀疏矩阵特征,空间组合关系均为树状结构。②总部区位(出度)的层级性差异均高于分支机构区位(入度)的层级性差异,显示出城市群内部空间“流”的不对称性。③针对12个城市群内部网络的拓扑结构聚类分析表明：长三角、珠三角、京津冀、山东半岛、海峡西岸地区的城市群内部网络联系较为紧密,呈现出一定程度的一体化网络特征;其中三大典型城市群存在明显的企业总部集聚核心,其余城市群内部的网络联系松散,跨城企业联系比重较低,在拓扑结构上大多呈现出以省会或副省级城市为指向的向心式联系。 相似文献
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同位模式表示不同类型的实体在空间邻域内共同频繁出现的规律,是城市实体空间关联的主要表达形式,但不能挖掘出指定实体的空间关联,需要寻找新的计算方法。在城市计算的视角下,通过引入粗糙集研究城市空间关联问题发现：1）该方法能把复杂的地理空间关联问题转换成信息决策问题,在信息决策表中计算城市实体之间的空间关联等拓扑关系,计算过程和结果可以挖掘城市行业之间的空间集聚和关联问题。2）通过属性约简得到属性核可以把高维空间数据降维,找到影响空间关联的重要因子。3）该方法拓宽了城市计算的理论方法体系和粗糙集方法的行业应用。最后,通过Python爬取南宁市城市服务业数据,进行方法的验证,计算结果与成熟的Apriori算法结果,以及南宁市服务业空间关联实际情况基本一致,证明了粗糙空间关联方法的可行性和正确性。 相似文献
15.
Enrico Steiger Bernd Resch Alexander Zipf 《International journal of geographical information science》2016,30(9):1694-1716
ABSTRACTThe investigation of human activity patterns from location-based social networks like Twitter is an established approach of how to infer relationships and latent information that characterize urban structures. Researchers from various disciplines have performed geospatial analysis on social media data despite the data’s high dimensionality, complexity and heterogeneity. However, user-generated datasets are of multi-scale nature, which results in limited applicability of commonly known geospatial analysis methods. Therefore in this paper, we propose a geographic, hierarchical self-organizing map (Geo-H-SOM) to analyze geospatial, temporal and semantic characteristics of georeferenced tweets. The results of our method, which we validate in a case study, demonstrate the ability to explore, abstract and cluster high-dimensional geospatial and semantic information from crowdsourced data. 相似文献
16.
大数据时代的空间交互分析方法和应用再论 总被引：10，自引：1，他引：9
空间交互是理解地表人文过程的重要基础,与空间依赖一起共同体现了地理空间的独特性、关联性以及对嵌入该空间的地理分布格局的影响,具有鲜明的时空属性,因此对于地理学研究具有重要意义。大数据为空间交互研究带来了新的机遇,能够使我们在不同时空尺度感知和观察空间交互模式并对其动态演化特征进行模拟和预测,从而为揭示人类活动规律及区域空间结构提供有力支持。本文在探讨空间交互与地理空间模式关系的基础上,描述了利用地理大数据感知空间交互的方式和定量模型,介绍了空间交互分析方法的研究进展及其在空间规划与交通、公共卫生、旅游等领域的应用情况,并就一些基本问题进行了讨论,以期为大数据支持下空间交互相关研究提供指导。 相似文献
17.
Xiaoping Liu Xingjian Liu He Jin Jinpei Ou Limin Jiao 《International journal of geographical information science》2018,32(4):738-756
To-date few research has successfully integrated big data from multiple sources to characterize urban mixed-use buildings. In this paper, we introduce a probabilistic model to integrate multi-source and geospatial big data (social network data, taxi trajectories, Points of Interest and remote sensing images) to characterize urban mixed-use buildings. The usefulness of our model is demonstrated with a case study of the Tianhe District in megacity Guangzhou, China. The model predicted building functions at 85% accuracy based on ground truth data from field surveys. We further explored the spatial patterns of the identified building functions. Most mixed-use buildings are located along major streets. Our proposed model can identify mixed-use buildings in a city; information is useful for planning evaluation and urban policymaking. 相似文献
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Shihong Du Xiaonan Wang Chen-Chieh Feng Xiuyuan Zhang 《International journal of geographical information science》2017,31(3):542-568
The exponential growth of natural language text data in social media has contributed a rich data source for geographic information. However, incorporating such data source for GIS analysis faces tremendous challenges as existing GIS data tend to be geometry based while natural language text data tend to rely on natural language spatial relation (NLSR) terms. To alleviate this problem, one critical step is to translate geometric configurations into NLSR terms, but existing methods to date (e.g. mean value or decision tree algorithm) are insufficient to obtain a precise translation. This study addresses this issue by adopting the random forest (RF) algorithm to automatically learn a robust mapping model from a large number of samples and to evaluate the importance of each variable for each NLSR term. Because the semantic similarity of the collected terms reduces the classification accuracy, different grouping schemes of NLSR terms are used, with their influences on classification results being evaluated. The experiment results demonstrate that the learned model can accurately transform geometric configurations into NLSR terms, and that recognizing different groups of terms require different sets of variables. More importantly, the results of variable importance evaluation indicate that the importance of topology types determined by the 9-intersection model is weaker than metric variables in defining NLSR terms, which contrasts to the assertion of ‘topology matters, metric refines’ in existing studies. 相似文献
20.
A hybrid parallel cellular automata model for urban growth simulation over GPU/CPU heterogeneous architectures 总被引：1，自引：0，他引：1
Qingfeng Guan Miaoqing Huang Chenggang Lai 《International journal of geographical information science》2016,30(3):494-514
As an important spatiotemporal simulation approach and an effective tool for developing and examining spatial optimization strategies (e.g., land allocation and planning), geospatial cellular automata (CA) models often require multiple data layers and consist of complicated algorithms in order to deal with the complex dynamic processes of interest and the intricate relationships and interactions between the processes and their driving factors. Also, massive amount of data may be used in CA simulations as high-resolution geospatial and non-spatial data are widely available. Thus, geospatial CA models can be both computationally intensive and data intensive, demanding extensive length of computing time and vast memory space. Based on a hybrid parallelism that combines processes with discrete memory and threads with global memory, we developed a parallel geospatial CA model for urban growth simulation over the heterogeneous computer architecture composed of multiple central processing units (CPUs) and graphics processing units (GPUs). Experiments with the datasets of California showed that the overall computing time for a 50-year simulation dropped from 13,647 seconds on a single CPU to 32 seconds using 64 GPU/CPU nodes. We conclude that the hybrid parallelism of geospatial CA over the emerging heterogeneous computer architectures provides scalable solutions to enabling complex simulations and optimizations with massive amount of data that were previously infeasible, sometimes impossible, using individual computing approaches. 相似文献