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1.
ABSTRACT

In the past decade, an explosion of data has taken place in Chinese cities due to widespread use of mobile Internet devices, Web 2.0 applications, and the development of the “Wired City.” With advances in data storage and high-performance computing, big/open urban data have opened up important avenues for urban studies, planning practice, and commercial consultancy. Urban researchers and planners are eager to make use of these abundant, sophisticated, and dynamic data to deepen their understanding on urban form and functions. However, in practice, access to such urban data is limited in China due to institutional constraints on data distribution and data holders’ hesitation to share data. And this hampers urban analytics. To draw reliable conclusions about the workings of complex urban systems, efficient and effective interoperation of multisource urban datasets is needed. Also, dealing with the heterogeneity between datasets is an equally critical challenge, especially for urban planners and government officers. They would derive value from data analytics, but have little data processing experience. To address these issues, we initiated SinoGrids (Plan Xu Xiake), a crowdsourcing platform that standardizes (or “downscales”) microscale urban data in China to facilitate its sharing and interoperation. To assess the performance evaluation of SinoGrids, we propose field-testing with actual urban data and their potential users. Digital desert, a son project of SinoGrids is also included.  相似文献   

2.
Big data analytics: six techniques   总被引：1，自引：0，他引：1  
Abstract

Big data have 4V characteristics of volume, variety, velocity, and veracity, which authentically calls for big data analytics. However, what are the dominant characteristics of big data analysis? Here, the analytics is related to the entire methodology rather than the individual specific analysis. In this paper, six techniques concerning big data analytics are proposed, which include: (1) Ensemble analysis related to a large volume of data, (2) Association analysis related to unknown data sampling, (3) High-dimensional analysis related to a variety of data, (4) Deep analysis related to the veracity of data, (5) Precision analysis related to the veracity of data, and (6) Divide-and-conquer analysis related to the velocity of data. The essential of big data analytics is the structural analysis of big data in an optimal criterion of physics, computation, and human cognition. Fundamentally, two theoretical challenges, ie the violation of independent and identical distribution, and the extension of general set-theory, are posed. In particular, we have illustrated three kinds of association in geographical big data, ie geometrical associations in space and time, spatiotemporal correlations in statistics, and space-time relations in semantics. Furthermore, we have illustrated three kinds of spatiotemporal data analysis, ie measurement (observation) adjustment of geometrical quantities, human spatial behavior analysis with trajectories, data assimilation of physical models and various observations, from which spatiotemporal big data analysis may be largely derived.  相似文献   

3.
ABSTRACT

In this opinion paper, we, a group of scientists from environmental-, geo-, ocean- and information science, argue visual data exploration should become a common analytics approach in Earth system science due to its potential for analysis and interpretation of large and complex spatio-temporal data. We discuss the challenges that appear such as synthesis of heterogeneous data from various sources, reducing the amount of information and facilitating multidisciplinary, collaborative research. We argue that to fully exploit the potential of visual data exploration, several bottlenecks and challenges have to be addressed: providing an efficient data management and an integrated modular workflow, developing and applying suitable visual exploration concepts and methods with the help of effective and tailored tools as well as generating and raising the awareness of visual data exploration and education. We are convinced visual data exploration is worth the effort since it significantly facilitates insight into environmental data and derivation of knowledge from it.  相似文献   

4.
ABSTRACT

This paper highlights a selection of core ideas articulated by Bertin and leveraged by many researchers over time, with particular attention to how the ideas relate to developments in cartography, big data, and visual analytics. A primary contribution is a bibliometric analysis of the impact of Bertin’s Semiology of Graphics at its 50th anniversary. A briefer bibliometric assessment of Graphics and Graphic Information Processing impacts is also provided. The bibliometric analysis includes exploration of citations to Semiology of Graphics over the entire time span (in both English and French editions) as well as more focused analysis by topic and outlet since the advent of visual analytics as a research domain. Then, very recent research related to cartography, visual analytics, and big data is examined in detail to determine if and how Bertin’s ideas continue to be leveraged and extended for current data representation and analysis challenges. After outlining some limitations of the bibliometric analysis, discussion reflects on the current relevance of Bertin’s ideas, potential applications in visual analytics, and the need for a complement to Sémiologie Graphique focused on interactive visual interfaces to an increasingly diverse array of display forms. The paper concludes with thoughts on next steps.  相似文献   

5.
ABSTRACT

Urban functional zones (UFZs) are important for urban sustainability and urban planning and management, but UFZ maps are rarely available and up-to-date in developing countries due to frequent economic and human activities and rapid changes in UFZs. Current methods have focused on mapping UFZs in a small area with either remote sensing images or open social data, but large-scale UFZ mapping integrating these two types of data is still not be applied. In this study, a novel approach to mapping large-scale UFZs by integrating remote sensing images (RSIs) and open social data is proposed. First, a context-enabled image segmentation method is improved to generate UFZ units by incorporating road vectors. Second, the segmented UFZs are classified by coupling Latent Dirichlet Allocation (LDA) and Support Vector Machine (SVM). In the classification framework, physical features from RSIs and social attributes from POI (Point of Interest) data are integrated. A case study of Beijing was performed to evaluate the proposed method, and an overall accuracy of 85.9% was achieved. The experimental results demonstrate that the presented method can provide fine-grained UFZs, and the fusion strategy of RSIs and POI data can distinguish urban functions accurately. The proposed method appears to be promising and practical for large-scale UFZ mapping.  相似文献   

6.
ABSTRACT

Light detection and ranging (LiDAR) data are essential for scientific discoveries such as Earth and ecological sciences, environmental applications, and responding to natural disasters. While collecting LiDAR data over large areas is quite possible the subsequent processing steps typically involve large computational demands. Efficiently storing, managing, and processing LiDAR data are the prerequisite steps for enabling these LiDAR-based applications. However, handling LiDAR data poses grand geoprocessing challenges due to data and computational intensity. To tackle such challenges, we developed a general-purpose scalable framework coupled with a sophisticated data decomposition and parallelization strategy to efficiently handle ‘big’ LiDAR data collections. The contributions of this research were (1) a tile-based spatial index to manage big LiDAR data in the scalable and fault-tolerable Hadoop distributed file system, (2) two spatial decomposition techniques to enable efficient parallelization of different types of LiDAR processing tasks, and (3) by coupling existing LiDAR processing tools with Hadoop, a variety of LiDAR data processing tasks can be conducted in parallel in a highly scalable distributed computing environment using an online geoprocessing application. A proof-of-concept prototype is presented here to demonstrate the feasibility, performance, and scalability of the proposed framework.  相似文献   

7.
Abstract

This article introduces a novel low rank approximation (LRA)-based model to detect the functional regions with the data from about 15 million social media check-in records during a year-long period in Shanghai, China. We identified a series of latent structures, named latent spatio-temporal activity structures. While interpreting these structures, we can obtain a series of underlying associations between the spatial and temporal activity patterns. Moreover, we can not only reproduce the observed data with a lower dimensional representative, but also project spatio-temporal activity patterns in the same coordinate system. With the K-means clustering algorithm, five significant types of clusters that are directly annotated with a combination of temporal activities can be obtained, providing a clear picture of the correlation between the groups of regions and different activities at different times during a day. Besides the commercial and transportation dominant areas, we also detected two kinds of residential areas, the developed residential areas and the developing residential areas. We further interpret the spatial distribution of these clusters using urban form analytics. The results are highly consistent with the government planning in the same periods, indicating that our model is applicable to infer the functional regions from social media check-in data and can benefit a wide range of fields, such as urban planning, public services, and location-based recommender systems.  相似文献   

8.
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9.
ABSTRACT

This paper aims to demonstrate results and considerations regarding the use of remote sensing big data for archaeological and Cultural Heritage management large scale applications. For this purpose, the Earth Engine© developed by Google© was exploited. Earth Engine© provides a robust and expandable cloud platform where several freely distributed remote sensing big data, such as Landsat, can be accessed, analysed and visualized. Two different applications are presented here as follows: the first one is based on the evaluation of multi-temporal Landsat series datasets for the detection of buried Neolithic tells (‘magoules’) in the area of Thessaly, in Greece using linear orthogonal equations. The second case exploits European scale multi-temporal DMSP-OLS Night-time Lights Time Series to visualize the impact of urban sprawl in the vicinity of UNESCO World Heritage sites and monuments. Both applications highlight the considerable opportunities that big data can offer to the fields of archaeology and Cultural Heritage, while the studies also demonstrate the great challenges that still are needed to be overcome in order to make the exploitation of big data process manageable and fruitful for future applications.  相似文献   

10.
Abstract

Landsat Thematic Mapper (TM) data have been used to monitor land cover types and to estimate biophysical parameters. However, studies examining the spatial relationships between land cover change and biophysical parameters are generally lacking. With the integration of remote sensing and Geographic Information Systems (GIS), these relationships can be better explored. The research reported in this paper applies this integrated approach for detecting urban growth and assessing its impact on vegetative greenness in the Zhujiang Delta, China. Multi‐temporal Landsat TM data were utilized to map urban growth and to extract and identify changes in vegetative greenness. GIS analyses were conducted to examine the changing spatial patterns of urban growth and greenness change. Statistical analyses were then used to examine the impact of urban growth on vegetative greenness. The results revealed that there was a notably uneven urban growth pattern in the delta, and urban development had reduced the scaled Normalized Difference Vegetation Index (NDVI) value by 30% in the urbanized area.  相似文献   

11.
ABSTRACT

There is an increasing availability of geospatial data describing patterns of human settlement and population such as various global remote-sensing based built-up land layers, fine-grained census-based population estimates, and publicly available cadastral and building footprint data. This development constitutes new integrative modeling opportunities to characterize the continuum of urban, peri-urban, and rural settlements and populations. However, little research has been done regarding the agreement between such data products in measuring human presence which is measured by different proxy variables (i.e. presence of built-up structures derived from different remote sensors, census-derived population counts, or cadastral land parcels). In this work, we quantitatively evaluate and cross-compare the ability of such data to model the urban continuum, using a unique, integrated validation database of cadastral and building footprint data, U.S. census data, and three different versions of the Global Human Settlement Layer (GHSL) derived from remotely sensed data. We identify advantages and shortcomings of these data types across different geographic settings in the U.S., which will inform future data users on implications of data accuracy and suitability for a given application, even in data-poor regions of the world.  相似文献   

12.
ABSTRACT

Novel sensor technologies are rapidly emerging. They enable a monitoring and modelling of our environment in a level of detail that was not possible a few years ago. However, while the raw data produced by these sensors are useful to get a first overview, it usually needs to be post-processed and integrated with other data or models in different applications. In this paper, we present an approach for integrating several geoprocessing components in the TaMIS water dam monitoring system developed with the Wupperverband, a regional waterbody authority in Germany. The approach relies upon the OGC Web Processing Service and is tightly coupled with Sensor Observation Service instances running at the Wupperverband. Besides implementing the standardized XML-based interface, lightweight REST APIs have been developed to ease the integration with thin Web clients and other Web-based components. Using this standards-based approach, new processing facilities can be easily integrated and coupled with different observation data sources.  相似文献   

13.
ABSTRACT

As an important advanced technique in the field of Earth observations, Synthetic Aperture Radar (SAR) plays a key role in the study of global environmental change, resources exploration, disaster mitigation, urban environments, and even lunar exploration. However, studies on imaging, image processing, and Earth factor inversions have often been conducted independently for a long time, which significantly limits the application effectiveness of SAR remote sensing due to the lack of an overall integrated design scheme and integrated information processing. Focusing on this SAR application issue, this paper proposes and describes a new SAR data processing methodology – SAR data integrated processing (DIP) oriented on Earth environment factor inversions. The simple definition, typical integrated modes and overall implementation ideas are introduced. Finally, focusing on building information extraction (man-made targets) and sea ice classification (natural targets) applications, three SAR DIP methods and experiments are conducted. Improved results are obtained under the guidance of the SAR DIP framework. Therefore, the SAR DIP theoretical framework and methodology represent a new SAR science application mode that has the capability to improve the SAR remote sensing quantitative application level and promote the development of new theories and methodologies.  相似文献   

14.
ABSTRACT

Mixed use has been extensively applied as an urban planning principle and hinders the study of single urban functions. To address this problem, it is worth decomposing the mixed use. Inspired by the concept of spectral unmixing in remote sensing applications, this paper proposes a framework for mixed-use decomposition based on big geo-data. Mixed-use decomposition in terms of human activities differs from traditional land use research, and it is more reasonable to infer the actual urban function of land. The framework consists of four steps, namely temporal activity signature extraction, urban function base curve extraction, mixed-use decomposition, and result validation. First, the temporal activity signatures (TASs) of each zone are extracted as the proxy of human activity patterns. Second, the diurnal TASs of routine activities are extracted as urban function base curves (i.e. endmembers). Third, a linear decomposition model is used to decompose the mixed use and obtain multiple results (urban function composition, dynamic activity proportions, and the mixing index). Finally, result validation strategies are concluded. This framework offers method extensibility and has few requirements for the input data. It is validated by means of a case study of Beijing, based on a social media check-in dataset.  相似文献   

15.
Abstract

Developing countries like India are an urbanization hotspot with many upcoming towns and cities. Growth in small and medium sized towns and cities have been unnoticed and growing without appropriate urban planning. Utilizing the available medium resolution satellite data and geospatial platforms, the growth dynamics of Kurukshetra city was analysed over a period of 24 years. The study employed a combination of change detection technique and spatial metrics (six each of class and landscape levels) analysis to delineate the growth track of the city and its environs. A significant increase in urban built up (dense 237%; open 1038%) is seen majorly at the cost of open area (70%) and tree clad (58%). Phases of city’s aggregation and diffusion are observed using class and landscape level spatial metrics. Understanding and monitoring of land use changes in and around city limits using integrated spatial tools provide better decision making capability.  相似文献   

16.
ABSTRACT

National spatial data infrastructures are key to achieving the Digital Earth vision. In many cases, national datasets are integrated from local datasets created and maintained by municipalities. Examples are address, building and topographic information. Integration of local datasets may result in a dataset satisfying the needs of users of national datasets, but is it productive for those who create and maintain the data? This article presents a stakeholder analysis of the Basisregistratie Adressen en Gebouwen (BAG), a collection of base information about addresses and buildings in the Netherlands. The information is captured and maintained by municipalities and integrated into a national base register by Kadaster, the Cadastre, Land Registry and Mapping Agency of the Netherlands. The stakeholder analysis identifies organisations involved in the BAG governance framework, describes their interests, rights, ownerships and responsibilities in the BAG, and maps the relationships between them. Analysis results indicate that Kadaster and the municipalities have the highest relative importance in the governance framework of the BAG. The study reveals challenges of setting up a governance framework that maintains the delicate balance between the interests of all stakeholders. The results provide guidance for SDI role players setting up governance frameworks for national or global datasets.  相似文献   

17.
ABSTRACT

Spatial online analytical processing (OLAP) and spatial data warehouse (SDW) systems are geo-business intelligence technologies that enable the analysis of huge volumes of geographic data. In the last decade, the conceptual design and implementation of SDWs that integrate spatial data, which are represented using the vector model, have been extensively investigated. However, the integration of field data (a continuous representation of spatial data) in SDWs is a recent unresolved research issue. Enhancing SDWs with field data improves the spatio-multidimensional analysis capabilities with continuity and multiresolutions. Motivated by the need for a conceptual design tool and relational online analytical processing (ROLAP) implementation, we propose a UML profile for SDWs that integrates a regular grid of points and supports continuity and multiresolutions. We also propose an efficient implementation of a ROLAP architecture.  相似文献   

18.
主要探讨了大数据时代下的海南城乡规划研究,从空间大数据技术在城乡规划各个阶段的应用入手,讨论了空间大数据技术对海南城乡规划的影响,指出了海南城乡规划目前存在的问题,指明了海南自由贸易试验区和中国特色自由贸易港建设背景下海南城乡规划的发展方向.  相似文献   

19.
建设黄河“智能大脑”服务流域生态保护和高质量发展   总被引：1，自引：0，他引：1  
本文首先介绍了黄河流域水文、地理景观和地貌特征,下游河道变迁和河口变迁历史及生态治理,流域历史水旱灾害等基本背景,分析了黄河流域生态保护和高质量发展面临的主要问题和具有的优势。然后重点论述黄河“智能大脑”如何服务流域保护和发展,提出黄河“智能大脑”三要素,即感知系统（天地一体智能感知网）、存储管理系统（资源池）和操作系统（时空大数据平台）;论述了流域一体化时空大数据中心的构成及其基本功能,时空大数据平台及其目标要求,分析并提出了基于网格集成与弹性云的混合式时空大数据平台技术体制和构建技术,提出采用“共用时空大数据平台+”应用概念模型及其具体应用模式。最后讨论了时空大数据平台服务黄河流域城市数字化、网络化和智能化,加强流域上中下游7大城市群的新型智慧城市建设,推动流域生态保护和社会经济发展,提出基于流域时空大数据平台构建服务保护和发展的综合科技信息咨询服务平台,支撑流域协同创新共同体构建,增强流域整体性和协同性发展。  相似文献   

20.
王昌翰 《测绘科学》2012,(4):184-186,190
本文介绍了重庆城市空间数据生产管理现状、数据更新保障机制,着重介绍了综合运用全野外数据采集、规划管理成果、航空摄影测量、卫星遥感影像、缩编等手段更新系列比例尺空间数据的技术方法;针对院空间数据生产库(制图库)与应用库(GIS库)衔接不紧密的现状,提出了生产库与应用库双库存储模式解决方案,既解决了复杂生产数据的数据库管理问题,又满足即时向政府部门及社会提供地理信息服务。  相似文献   

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