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1.
OpenStreetMap (OSM) represents one of the most well‐known examples of a collaborative mapping project. Major research efforts have so far dealt with data quality analysis but the modality of OSM's evolution across space and time has barely been noted. This study aims to analyze spatio‐temporal patterns of contributions in OSM by proposing a contribution index (CI) in order to investigate the dynamism of OSM. The CI is based on a per cell analysis of the node quantity, interactivity, semantics, and attractivity (the ability to attract contributors). Additionally this research explores whether OSM has been constantly attracting new users and contributions or if OSM has experienced a decline in its ability to attract continued contributions. Using the Stuttgart region of Germany as a case study the empirical findings of the CI over time confirm that since 2007, OSM has been constantly attracting new users, who create new features, edit the existing spatial objects, and enrich them with attributes. This rate has been dramatically growing since 2011. The utilization of a Cellular Automata‐Markov (CA‐Markov) model provides evidence that by the end of 2016 and 2020, the rise of CI will spread out over the study area and only a few cells without OSM features will remain.  相似文献   

2.
This study adopts a near real‐time space‐time cube approach to portray a dynamic urban air pollution scenario across space and time. Originating from time geography, space‐time cubes provide an approach to integrate spatial and temporal air pollution information into a 3D space. The base of the cube represents the variation of air pollution in a 2D geographical space while the height represents time. This way, the changes of pollution over time can be described by the different component layers of the cube from the base up. The diurnal ambient ozone (O3) pollution in Houston, Texas is modeled in this study using the space‐time air pollution cube. Two methods, land use regression (LUR) modeling and spatial interpolation, were applied to build the hourly component layers for the air pollution cube. It was found that the LUR modeling performed better than the spatial interpolation in predicting air pollution level. With the availability of real‐time air pollution data, this approach can be extended to produce real‐time air pollution cube is for more accurate air pollution measurement across space and time, which can provide important support to studies in epidemiology, health geography, and environmental regulation.  相似文献   

3.
Geographically weighted regression (GWR) is an important local method to explore spatial non‐stationarity in data relationships. It has been repeatedly used to examine spatially varying relationships between epidemic diseases and predictors. Malaria, a serious parasitic disease around the world, shows spatial clustering in areas at risk. In this article, we used GWR to explore the local determinants of malaria incidences over a 7‐year period in northern China, a typical mid‐latitude, high‐risk malaria area. Normalized difference vegetation index (NDVI), land surface temperature (LST), temperature difference, elevation, water density index (WDI) and gross domestic product (GDP) were selected as predictors. Results showed that both positively and negatively local effects on malaria incidences appeared for all predictors except for WDI and GDP. The GWR model calibrations successfully depicted spatial variations in the effect sizes and levels of parameters, and also showed substantially improvements in terms of goodness of fits in contrast to the corresponding non‐spatial ordinary least squares (OLS) model fits. For example, the diagnostic information of the OLS fit for the 7‐year average case is R2 = 0.243 and AICc = 837.99, while significant improvement has been made by the GWR calibration with R2 = 0.800 and AICc = 618.54.  相似文献   

4.
Many social phenomena have a spatio‐temporal dimension and involve dynamic decisions made by individuals. In the past, researchers have often turned to geographic information systems (GIS) to model these interactions. Although GIS provide a powerful tool for examining the spatial aspects of these interactions, they are unable to model the dynamic, individual‐level interactions across time and space. In an attempt to address these issues, some researchers have begun to use simulation models. But these models rely on artificial landscapes that do not take into account the environment in which humans move and interact. This research presents the methodology for ‘situating’ simulation through the use of a new modeling tool, Agent Analyst, which integrates agent‐based modeling (ABM) and GIS. Three versions of a model of street robbery are presented to illustrate the importance of using ‘real’ data to inform agent activity spaces and movement. The successful implementation of this model demonstrates that: (1) agents can move along existing street networks; (2) land use patterns can be used to realistically distribute agent's homes and activities across a city; and (3) the incidence and pattern of street robberies is significantly different when ‘real’ data are used.  相似文献   

5.
6.
全球导航卫星系统(global navigation satellite system,GNSS)‐声学海底定位是面向海底俯冲带板块形变监测需求提出的一种定位技术,也是建设海洋时空基准网的一种重要技术,有着广阔的应用前景。虽然目前GNSS‐声学海底定位技术的研究成果还不能满足海洋时空基准网的建设需求,但其数据处理方法尤其是声速误差精细处理方法,对海洋时空基准网海底部分(海底大地基准)的建设具有重要借鉴意义。介绍了GNSS‐声学海底定位技术的起源,并将其分为静态测量和动态测量两类,同时将声速误差处理方法作为该技术的发展脉络进行梳理,提炼了该技术的3个发展阶段:仅假设海洋声速垂向分层、考虑声速的时域变化、考虑声速的水平梯度。对于仅假设海洋声速垂向分层的阶段,国外学者采用几何结构对称的方式来削弱声速误差的影响;国内学者则主要对声速以外误差源(杆臂矢量误差、时标偏差、姿态角误差等)进行了研究,并用优化随机模型的方式削弱系统误差对定位的影响。对于考虑声速时域变化的阶段,国外学者利用拟合方法(多项式拟合或三次样条拟合)结合参数平滑约束来解算声速的时域变化量,提高定位的稳定性;国内学者基于此细化了参数拟合的方法(考虑参数长周期项的变化特征),并创新性地提出了水下差分定位算法。对于考虑声速水平梯度的阶段,国内外学者在GNSS‐声学海底定位中解算了声速水平梯度参数,提高了水平方向定位的稳定性,并利用海洋数值模型验证了结果的可靠性。展望了将GNSS‐声学海底定位高精度数据处理方法应用于海底大地基准建设的前景,并引入了小时空尺度声速层析的概念(基于海洋时空基准网的声速误差处理方法),以期解决数值预报模型不能提供小时空尺度产品的问题,进而为水下潜器提供更高精度的声速误差改正服务。  相似文献   

7.
Abstract

The outward expansion of cities in the United States has been a source of concern and policy debate for well over forty years. This sprawling urban landscape has been cited as a contributing factor behind the loss of open space, environmental damage and increased congestion. To better understand urban expansion, monitoring programs are required to facilitate the systematic observation of urban expansion, and to provide critical information in order to adjust urban development policies. Monitoring the urban landscape has been a major application focus of satellite remote sensing technologies. Yet, research has shown that the complexity of the urban landscape frustrates simple characterization of cumulative land cover processes such as sprawl. In this paper an approach to the remote detection and characterization of sprawl is introduced based on the use of Dempster‐Shafer Theory of Evidence. Functioning as a soft‐classification algorithm, Demptster‐Shafer Theory offers a unique solution to the mapping problem when evidence of class structure in underscored by uncertainty. Through the use of this technique it was possible to model uncertainty based on the concept of belief. This conceptualization was instrumental in deciphering the complexities of urban land cover arrangements and offered an alternative logic which enhanced delineation of subtle changes in land cover indicative of sprawl.  相似文献   

8.
Human activities and more generally the phenomena related to human behaviour take place in a network‐constrained subset of the geographical space. These phenomena can be expressed as locations having their positions configured by a road network, as address points with street numbers. Although these events are considered as points on a network, point pattern analysis and the techniques implemented in a GIS environment generally consider events as taking place in a uniform space, with distance expressed as Euclidean and over a homogeneous and isotropic space. Network‐spatial analysis has developed as a research agenda where the attention is drawn towards point pattern analytical techniques applied to a space constrained by a road network. Little attention has been put on first order properties of a point pattern (i.e. density) in a network space, while mainly second order analysis such as nearest neighbour and K‐functions have been implemented for network configurations of the geographical space. In this article, a method for examining clusters of human‐related events on a network, called Network Density Estimation (NDE), is implemented using spatial statistical tools and GIS packages. The method is presented and compared to conventional first order spatial analytical techniques such as Kernel Density Estimation (KDE). Network Density Estimation is tested using the locations of a sample of central, urban activities associated with bank and insurance company branches in the central areas of two midsize European cities, Trieste (Italy) and Swindon (UK).  相似文献   

9.
We used GIS‐based techniques and inductive‐spatial modelling to analyse spatial interactions between predator and prey populations, a unique example of an extension to an existing ecological approach. The approach identifies spatial predictors of predation and is demonstrated for braided riverbed habitat in the Mackenzie Basin, New Zealand. This habitat is highly modified and is the focus of intensive management because of the presence of introduced mammalian predators and their native prey (primarily nests of ground‐nesting native birds that are extremely vulnerable to predators). Native prey are currently in decline due to predation; GIS techniques therefore have the potential to augment conventional ecological techniques and management practices. Predation risk to nests of ground‐nesting birds was interpolated across an area using inverse distance weighting. A linear regression model for spatio‐temporal predictors of nest predation was deter‐mined using a predation risk surface and three separate surfaces representing predator abundance, prey abundance, and habitat structure. These measures can enhance the non‐spatial results from conventional ecological inquiry and help solve pest management problems affecting the natural environment.  相似文献   

10.
Street‐level images taken by vehicles and pedestrians have found a role in various companies’ location‐based intelligence services. Some platforms collect their images using their own cars and drivers, while others rely on crowdsourcing; however, to what extent can we expect crowdsourced approaches to reach the imagery coverage levels obtained by paid drivers? Is capturing every single street a useful or obtainable goal? We use online coverage maps to compare Google Street View, Mapillary, and OpenStreetCam in 24 major world cities and 25 differently sized cities in Brazil. We find that Google has often taken an all‐or‐nothing approach to collecting coverage in world cities, whereas crowdsourced platforms have achieved a more even distribution of coverage across space. Extremely low‐ and high‐income neighborhoods are sometimes omitted due to visible and invisible barriers. Coverage patterns are influenced by how and why each company procures imagery, along with other social, economic, and geographic factors.  相似文献   

11.
This study develops new types of hotspot detection methods to describe the micro‐space variation of the locations of crime incidents at the street level. It expands on two of the most widely used hotspot detection methods, Spatial and Temporal Analysis of Crime and Spatial Scan Statistic, and applies them to the analysis of the network space. The study first describes the conceptual and the methodological framework of the new methods followed by analyses using: (1) a simulated distribution of points along the street network; and (2) real street‐crime incident data. The simulation study using simulated point distributions confirms that the proposed methods is more accurate, stable and sensitive in detecting street‐level hotspots than their conventional counterparts are. The empirical analysis with real crime data focuses on the distribution of the drug markets and robberies in downtown Buffalo, NY in 1995 and 1996. The drug markets are found to form hotspots that are dense, compact and stable whereas hotspots of the robberies are observed more thinly across a wider area. The study also reveals that the location of the highest risk remains on the same spot over time for both types of crimes, indicating the presence of hotbeds which requires further attention.  相似文献   

12.
A Predictive Model for Frequently Viewed Tiles in a Web Map   总被引:1,自引:0,他引:1  
Distributing pre‐generated image tiles from a server‐side cache is a fast and popular way of serving maps on the Web. However, these caches can grow unmanageably large for maps covering many scales over a broad extent. This research presents a model for determining high‐priority geographic areas for tile caching. The model considers variables found in previous research to be of interest to Web map users, such as populated places, major roads, coastlines, and tourist attractions. The proportion of area, disk space, and time saved when creating a partial cache (consisting only of high‐interest areas) and a cache of the entire map extent are compared to establish that marked savings are possible. Several applications of the model beyond tile caching are briefly discussed.  相似文献   

13.
Socio‐demographic data are typically collected at various levels of aggregation, leading to the modifiable areal unit problem. Spatial non‐stationarity of statistical associations between variables further influences the demographic analyses. This study investigates the implications of these two phenomena within the context of migration‐environment associations. Global and local statistical models are fit across increasing levels of aggregation using household level survey data from rural South Africa. We raise the issue of operational scale sensitivity, which describes how the explanatory power of certain variables depends on the aggregation level. We find that as units of analysis (households) are aggregated, some variables become non‐significant in the global models, while others are less sensitive to aggregation. Local model results show that aggregation reduces spatial variation in migration‐related local associations but also affects variables differently. Spatial non‐stationarity appears to be the driving force behind this phenomenon as the results from the global model mask this relationship. Operational scale sensitivity appears related to the underlying spatial autocorrelation of the non‐aggregated variables but also to the way a variable is constructed. Understanding operational scale sensitivity can help to refine the process of selecting variables related to the scale of analysis and better understand the effects of spatial non‐stationarity on statistical relationships.  相似文献   

14.
Urbanization and the associated change in land cover has been intensifying across the globe in recent decades. Regional studies on the rate and amount of urban expansion are critical for understanding how patterns of change differ within and among cities with varying structure and development characteristics. Yet spatially consistent and timely information on urban development is difficult to access particularly across international jurisdictions. Remote sensing based technologies offer a unique perspective on urban land cover with the data offering significant potential to urban studies due to its consistent and ubiquitous nature. In this research we applied a pixel-based image composite technique to generate annual gap-free surface reflectance Landsat composites from 1984 to 2012 for 25 urban environments across 12 countries in the Pacific Rim. Using time series composites, spectral indices were calculated and compared using a hexagonal grid ring model to assess changes in vegetative and urban patterns. Trajectories were then clustered to further investigate the spatio-temporal dynamics and relationships among the 25 cities. Performance of the clustering analyses varied depended on the temporal and spatial metrics however overall clustering results indicated relatively strong spatio-temporal similarities among a number of key cities. Three pairs of cities—Melbourne and Sydney; Tianjin and Manila; and Singapore City and Kuala Lumpur were found to be highly similar in their urban and vegetation dynamics temporally and spatially. In contrast Vancouver and Las Vegas had no similar analogous. This work demonstrates the value of utilising annual Landsat time series composites for assessing urban vegetation and urban dynamics at regional scales and potential use in sustainable urban planning, resources allocation, and policy making.  相似文献   

15.
Outdoor navigation is widely used in daily life, but faces various issues related to the fidelity of outdoor navigation networks. For instance, agents (pedestrians) are often guided via unrealistic detours around places without clear paths (e.g., squares) or if there are vertical constraints such as overpasses/bridges. This is partly explained by the fact that the main sources of navigation networks in current outdoor navigation are two‐dimensional road/street networks. Utilizing a three‐dimensional space‐based navigation model, compatible with some indoor approaches, is a popular way to address the above‐mentioned issues. A 3D space‐based navigation model is generated by treating 3D spaces as nodes and the shared faces as edges. Inputs of this model are enclosed 3D spaces (volumes). However, outdoor spaces are generally open and unbounded. This article puts forward an approach to enclose outdoor spaces and mimic the indoor environments to derive a network based on connectivity and accessibility of spaces. The approach uses 2.5D maps and consists of three major steps: object footprint determination, footprint classification and space creation. Two use cases demonstrate the proposed approach. Enclosing outdoor spaces opens a new research direction toward providing seamless indoor/outdoor navigation for a range of agents.  相似文献   

16.
For landscape models to be applied successfully in management situations, models must address appropriate questions, include relevant processes and interactions, be perceived as credible and involve people affected by decisions. We propose a framework for collaborative model building that can address these issues, and has its roots in adaptive management, computer‐supported collaborative work and landscape ecology. Models built through this framework integrate a variety of information sources, address relevant questions, and are customized for the particular landscape and policy environment under study. Participants are involved in the process from the start, and because their input is incorporated, they feel ownership of the resulting models, increasing the chance of model acceptance and application. There are two requirements for success: a tool that supports rapid model prototyping and modification, that makes a clear link between a conceptual and implemented model, and that has the ability to implement a wide range of model types; and a core team with skills in communication, research and analysis, and knowledge of ecology and forestry in addition to modelling. SELES (Spatially Explicit Landscape Event Simulator) is a tool for building and running models of landscape dynamics. It combines discrete event simulation with a spatial database and a relatively simple modelling language to allow rapid development of landscape simulations, and provides a high‐level means of specifying complex model behaviours ranging from management actions to natural disturbance and succession. We have applied our framework in several forest modelling projects in British Columbia, Canada. We have found that this framework increases the interest by local experts and decision‐makers to participate actively in the model building process. The workshop process and resulting models have efficiently provided insight into the dynamics of large landscapes over long time frames. The use of SELES has facilitated this process by providing a flexible, transparent environment in which models can be rapidly implemented and refined. As a result, model findings may be more readily incorporated into decision‐support systems designed to assist resource managers in making informed decisions.  相似文献   

17.
星地多源数据的区域土壤有机质数字制图   总被引:4,自引:0,他引:4  
周银  刘丽雅  卢艳丽  马自强  夏芳  史舟 《遥感学报》2015,19(6):998-1006
土壤有机质(SOM)是全球碳循环、土壤养分的重要组成部分,精确估算土壤有机质含量具有重要意义。本文以中国东北—华北平原为研究区,收集了1078个土壤样本,以遥感数据(MODIS,TRMM和STRM数据)与土壤地面光谱数据为预测因子,运用基于树形结构的数据挖掘技术构建土壤有机质-环境预测因子模型进行数字土壤制图。通过不同建模样本数建模精度比较,选择300个样本数时的模型为最优模型。建模结果表明土壤光谱和气候因子是研究区SOM变异的主控因子,生物因子次之,而地形因子影响最小。预测结果经检验,RMSE为7.25,R2为0.69,RPD为1.53制图结果与基于第二次全国土壤普查数据的土壤有机质地图具有相似的分布规律,呈现SOM自东北向西南递减的趋势。通过比较分析发现,经过20年左右的土地开发与利用,研究区低SOM和高SOM含量土壤面积减少,而中等SOM含量土壤面积增加。  相似文献   

18.
Quality Assessment of Cartographic Generalisation   总被引:2,自引:1,他引:2  
This paper proposes a methodology to assess the quality of cartographic generalisa‐tion, which consists of representing geographic space in a simplified way according to the scale and the objectives of the intended map. The automation of this process makes the derivation of data easier, but the quality of the results is often not evaluated. This paper proposes an assessment model based on: (1) characterisation of the data in their initial and final states at different levels of analysis; (2) a data quality assessment by comparison of the two characterisations; and (3) aggregation of the various assessment results to summarise data quality. The assessment algorithm has been implemented and the method has been tested to assess the generalisation of a small urban area. A visualisation tool for assessment of the results has been developed to validate the generalisation evaluation. The results of the research are presented and discussed at the end of the paper.  相似文献   

19.
20.
Individuals and other entities move through space as a function of local characteristics of place, their internal behavioral models, and the topological structure of the underlying space. When a collection of locations (i.e. geotagged photos or other geotagged social media information) from a large number of individuals is assembled, it becomes possible to understand the interrelationship between the individuals and the space they occupy. This research systematically considers this interrelationship through an examination of the effect of the intersection of behavioral and spatial characteristics on individuals moving on street networks. The research illustrates how social media data, in combination with a biased random walker, can be used to understand and model the interaction of spatial structure and social‐environmental factors on influencing individuals' use of their environment. The biased walker offers a flexible approach to incorporate consideration of both social‐environmental and structural factors into a model and we demonstrate this through a case study wherein we are able to use the random walker to model the characteristics of Flickr users in New York City.  相似文献   

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