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1.
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2.
Attractive regions can be detected and recommended by investigating users’ online footprints. However, social media data suffers from short noisy text and lack of a-priori knowledge, impeding the usefulness of traditional semantic modelling methods. Another challenge is the need for an effective strategy for the selection/recommendation of candidate regions. To address these challenges, we propose a comprehensive workflow which combines semantic and location information of social media data to recommend thematic urban regions to users with specific interests. This workflow is novel in: (1) developing a data-driven geographic topic modelling method which utilizes the co-occurrence patterns of self-explanatory semantic information to detect semantic communities; (2) proposing a new recommendation strategy with the consideration of region’s spatial scale. The workflow was implemented using a real-world dataset and evaluation conducted at three different levels: semantic representativeness, topic identification and recommendation desirability. The evaluation showed that the semantic communities detected were internally consistent and externally differentiable and that the recommended regions had a high degree of desirability. The work has demonstrated the effectiveness of self-explanatory semantic information for geographic topic modelling and highlighted the importance of including region spatial scale into the model for an effective region recommending strategy.  相似文献   

3.
Landing a rescue helicopter in a wilderness environment, such as Yosemite National Park, requires suitable areas that are flat, devoid of tree canopy, and not within close proximity to other hazards. The objective of this study was to identify helicopter landing areas that are most likely to exist based on available geographic data using two GIScience methods. The first approach produced an expert model that was derived from predefined feature constraints based on existing knowledge of helicopter landing area requirements (weighted overlay algorithm). The second model is derived using a machine learning technique (maximum entropy algorithm, Maxent) that derives feature constraints from existing presence-only points; that is, geographic one-class data. Both models yielded similar output and successfully classified test coordinates, but Maxent was more efficient and required no user-defined weighting that is typically subject to human bias or disagreement. The pros and cons of each approach are discussed and the comparison reveals important considerations for a variety of future land suitability studies, including ecological niche modeling. The conclusion is that the two approaches complement each other. Overall, we produced an effective geographic information system product to support the identification of suitable landing areas in emergent rescue situations. To our knowledge, this is the first GIScience study focused on estimating the location of landing zones for a search-and-rescue application.  相似文献   

4.
Increasing efforts to implement marine protected areas (MPAs) as a means of managing marine ecosystems have created a need for evaluating potential spatial management plans. Almost all marine populations are metapopulations, connected reproductively by the dispersal of pelagic larvae. Models of marine population dynamics must account for larval connectivity, but despite recent advances connectivity patterns are still poorly understood. To allow more informed decision making when complete information on dispersal is lacking, we have developed a method based on geographic information systems (GIS) for representing larval dispersal distributions based on bathymetry and typical flows in the coastal ocean. These distributions reflect (1) generally greater flow in directions along, rather than across, lines of constant bathymetry and (2) lesser flow in shallow near-shore waters. We demonstrate how to parameterize this two-dimensional method for depicting larval dispersal based on comparisons to local oceanographic data. We then compare the predictions of the two-dimensional method to those of a simpler one-dimensional alternative in a population model used to evaluate proposed MPAs along the coast of central California. The method produces reasonable larval dispersal patterns and appears to include the effects of bathymetry on population dynamics better than commonly used one-dimensional methods and without requiring the significantly greater investment of developing particle-tracking circulation models. An important advantage of a two-dimensional approach is more realistic portrayal of the dependence of population persistence on the cross-shelf dimension of available habitat.  相似文献   

5.
Great strides have been made in Geographic Information Systems (GIS) research over the past half-century. However, this progress has created both opportunities and challenges. From a geographic perspective, certain challenges remain, including the modelling of geographic-featured environments with GIS data model, the enhancement of GIS’s analysis functions for comprehensive geographic analysis and achieving human-oriented geographic information presentation. Several basic theoretical and technical ideas that follow the workflow and processes of geographic information induction, geographic scenario modelling, geographic process analysis and geographic environment representation are proposed to fill the gaps between GIS and geography. We also call for designing methods for big geographic data-oriented analysis, making best use of videos and developing virtual geographic scenario-based GIS for further evolution.  相似文献   

6.
Environmental simulation models need automated geographic data reduction methods to optimize the use of high-resolution data in complex environmental models. Advanced map generalization methods have been developed for multiscale geographic data representation. In the case of map generalization, positional, geometric and topological constraints are focused on to improve map legibility and communication of geographic semantics. In the context of environmental modelling, in addition to the spatial criteria, domain criteria and constraints also need to be considered. Currently, due to the absence of domain-specific generalization methods, modellers resort to ad hoc methods of manual digitization or use cartographic methods available in off-the-shelf software. Such manual methods are not feasible solutions when large data sets are to be processed, thus limiting modellers to the single-scale representations. Automated map generalization methods can rarely be used with confidence because simplified data sets may violate domain semantics and may also result in suboptimal model performance. For best modelling results, it is necessary to prioritize domain criteria and constraints during data generalization. Modellers should also be able to automate the generalization techniques and explore the trade-off between model efficiency and model simulation quality for alternative versions of input geographic data at different geographic scales. Based on our long-term research with experts in the analytic element method of groundwater modelling, we developed the multicriteria generalization (MCG) framework as a constraint-based approach to automated geographic data reduction. The MCG framework is based on the spatial multicriteria decision-making paradigm since multiscale data modelling is too complex to be fully automated and should be driven by modellers at each stage. Apart from a detailed discussion of the theoretical aspects of the MCG framework, we discuss two groundwater data modelling experiments that demonstrate how MCG is not just a framework for automated data reduction, but an approach for systematically exploring model performance at multiple geographic scales. Experimental results clearly indicate the benefits of MCG-based data reduction and encourage us to continue expanding the scope of and implement MCG for multiple application domains.  相似文献   

7.
The Recreation Opportunity Spectrum (ROS) has been used internationally as a tool to guide recreation planning. The spectrum as a map has primarily been generated manually and through digitisation by analysts with an in-depth knowledge of the region of interest. This paper seeks to outline an alternative method that is objective and repeatable to create a ROS map for New Zealand, using data from a variety of sources and manipulated with spatial tools available in a geographic information system. The result is a map that is consistent on a national scale, and a method that is repeatable. The model can be used to develop scenario modelling, change detection, and help guide management decisions.  相似文献   

8.
An automatic estimate of the number of attendees to events happening in the city can provide valuable information to geographic information systems and geo-located applications. We present a methodology to estimate the number of events’ attendees from cellular network data. In this work, we used anonymized Call Detail Records (CDRs) comprising data on where and when users access the cellular network. Our approach is based on two key ideas: (1) we identify the network cells associated with the event location. (2) We verify the attendance of each user, as a measure of whether (s)he generates CDRs during the event, but not during other times. We evaluate our approach to estimate the number of attendees to a number of events ranging from football matches in stadiums to concerts and festivals in open squares. Comparing our results with the best groundtruth data available, our estimates provide a median error of less than 15% of the actual number of attendees.  相似文献   

9.
There is an increasing need for a quick, simple method to represent diurnal population change in metropolitan areas for effective emergency management and risk analysis. Many geographic studies rely on decennial U.S. Census data that assume that urban populations are static in space and time. This has obvious limitations in the context of dynamic geographic problems. The U.S. Department of Transportation publishes population data at the transportation analysis zone level in fifteen-minute increments. This level of spatial and temporal detail allows for improved dynamic population modeling. This article presents a methodology for visualizing and analyzing diurnal population change for metropolitan areas based on this readily available data. Areal interpolation within a geographic information system is used to create twenty-four (one per hour) population surfaces for the larger metropolitan area of Salt Lake County, Utah. The resulting surfaces represent diurnal population change for an average workday and are easily combined to produce an animation that illustrates population dynamics throughout the day. A case study of using the method to visualize population distributions in an emergency management context is provided using two scenarios: a chemical release and a dirty bomb in Salt Lake County. This methodology can be used to address a wide variety of problems in emergency management.  相似文献   

10.
X. Yao  L.G. Tham  F.C. Dai 《Geomorphology》2008,101(4):572-582
The Support Vector Machine (SVM) is an increasingly popular learning procedure based on statistical learning theory, and involves a training phase in which the model is trained by a training dataset of associated input and target output values. The trained model is then used to evaluate a separate set of testing data. There are two main ideas underlying the SVM for discriminant-type problems. The first is an optimum linear separating hyperplane that separates the data patterns. The second is the use of kernel functions to convert the original non-linear data patterns into the format that is linearly separable in a high-dimensional feature space. In this paper, an overview of the SVM, both one-class and two-class SVM methods, is first presented followed by its use in landslide susceptibility mapping. A study area was selected from the natural terrain of Hong Kong, and slope angle, slope aspect, elevation, profile curvature of slope, lithology, vegetation cover and topographic wetness index (TWI) were used as environmental parameters which influence the occurrence of landslides. One-class and two-class SVM models were trained and then used to map landslide susceptibility respectively. The resulting susceptibility maps obtained by the methods were compared to that obtained by the logistic regression (LR) method. It is concluded that two-class SVM possesses better prediction efficiency than logistic regression and one-class SVM. However, one-class SVM, which only requires failed cases, has an advantage over the other two methods as only “failed” case information is usually available in landslide susceptibility mapping.  相似文献   

11.
Wildlife ecologists frequently make use of limited information on locations of a species of interest in combination with readily available GIS data to build models to predict space use. In addition to a wide range of statistical data models that are more commonly used, machine learning approaches provide another means to develop predictive spatial models. However, comparison of output from these two families of models for the same data set is not often carried out. It is important that wildlife managers understand the pitfalls and limitations when a single set of models is used with limited GIS data to try to predict and understand species distribution. To illustrate this, we carried out two sets of models (generalized linear mixed models (GLMMs) and boosted regression trees (BRTs)) to predict geographic occupancy of the eastern coyote (Canis latrans) on the island of Newfoundland, Canada. This exercise is illustrative of common spatial questions in wildlife research and management. Our results show that models vary depending on the approach (GLMM vs. BRT) and that, overall, BRT had higher predictive ability. Although machine learning has been criticized because it is not explicitly hypothesis-driven, it has been used in other areas of spatial modelling with success. Here, we demonstrate that it may be a useful approach for predicting wildlife space use and to generate hypotheses when data are limited. The results of this comparison can help to improve other models for species distributions and also guide future sampling and modelling initiatives.  相似文献   

12.
杜云艳  易嘉伟  薛存金  千家乐  裴韬 《地理学报》2021,76(11):2853-2866
地理事件作为描述地理过程的基本单元,逐渐成为地理信息科学（GIS）核心研究内容。由于受人类活动数据获取限制,GIS对地理事件的建模和分析主要关注事件所引起的地理空间要素变化及要素之间的相互影响与作用机制。然而,近年来随着基于位置服务数据（LBS）爆炸式的增长和人类活动大数据定量刻画手段的快速发展,地理事件对人类活动的影响以及公众对地理事件的网络参与度都引起了多个领域的广泛关注,对地理事件的时空认知、建模方法和分析框架提出了巨大的挑战。对此,本文首先深入分析了大数据时代地理事件的概念与分类体系;其次,基于地理事件的时空语义给出了基于图模型的事件数据建模,建立了事件本体及其次生或级联事件的“节点—边”表达结构,开展了事件自身时空演化及其前“因”后“果”的形式化描述;第三,从时空数据分析与挖掘的角度,给出了大数据时代地理事件建模与分析的整体框架,拟突破传统“地理实体空间”事件探测与分析方法的局限性,融合“虚拟空间”事件发现与传播模拟思路,实现多源地理大数据支撑下的面向地理事件的人类活动多尺度时空响应与区域差异分析;最后,本文以城市暴雨事件为例诠释了本文所提出的地理事件建模与分析方法,从城市和城市内部两个尺度进行了暴雨事件与人类活动的一致性响应及区域差异分析,得到了明确的结论,验证了前文分析框架的可行性与实用性。  相似文献   

13.
Kobresia pygmaea Willd. dominates the alpine meadow ecosystem on the Qinghai-Tibet Plateau. Knowledge of this species’ distribution and ecological environment could provide valuable insights into the alpine ecosystem and key species living there, support species and ecosystem conservation in alpine regions, and build on species origin and evolutionary research. To avoid modelling uncertainty encountered in a single approach, four species distribution model algorithms (Surface Range Envelope (SRE), Generalized Linear Model (GLM), Generalized Boosted Regression (GBM) and Maximum Entropy (MAXENT)), were used to simulate the distribution of K. pygmaea based on occurrence samples that were verified using DNA sequencing techniques. Species distribution modelling revealed a vast distribution region of K. pygmaea in the northern Tibetan Highlands and alpine meadows in the southern and eastern declivity of the plateau. A high evaluation performance was found for the GLM, GBM and MAXENT models. Different potential range size patterns for the four models were found between 374340-482605 km2 (average = 421591 km2). Precipitation during growing seasons was found to be the dominant factor accounting for the distribution, consistent with patterns of heat and water patterns conditions of alpine ecosystems on the plateau. Species distribution models provide a simple and reliable approach to simulating the spatial patterns of species inhabiting the Qinghai-Tibet Plateau.  相似文献   

14.
The paper describes the development of a new methodological approach for simulating geographic processes through the development of a data model that represents a process. This methodology complements existing approaches to dynamic modelling, which focus on the states of the system at each time step, by storing and representing the processes that are implicit in the model. The data model, called nen, focuses existing modelling approaches on representing and storing process information, which provides advantages for querying and analysing processes. The flux simulation framework was created utilizing the nen data model to represent processes. This simulator includes basic classes for developing a domain specific simulation and a set of query tools for inquiring after the results of a simulation. The methodology is prototyped with a watershed runoff simulation.  相似文献   

15.
Volunteered geographic information (VGI) contains valuable field observations that represent the spatial distribution of geographic phenomena. As such, it has the potential to provide regularly updated low-cost field samples for predictively mapping the spatial variations of geographic phenomena. The predictive mapping of geographic phenomena often requires representative samples for high mapping accuracy, but samples consisting of VGI observations are often not representative as they concentrate on specific geographic areas (i.e. spatial bias) due to the opportunistic nature of voluntary observation efforts. In this article, we propose a representativeness-directed approach to mitigate spatial bias in VGI for predictive mapping. The proposed approach defines and quantifies sample representativeness by comparing the probability distributions of sample locations and the mapping area in the environmental covariate space. Spatial bias is mitigated by weighting the sample locations to maximize their representativeness. The approach is evaluated using species habit suitability mapping as a case study. The results show that the accuracy of predictive mapping using weighted sample locations is higher than using unweighted sample locations. A positive relationship between sample representativeness and mapping accuracy is also observed, suggesting that sample representativeness is a valid indicator of predictive mapping accuracy. This approach mitigates spatial bias in VGI to improve predictive mapping accuracy.  相似文献   

16.
To solve the problem of handling numerous data from drillings and geophysical surveys for specific information of subsurface geological formations, the use of databases and geographic information systems (GIS) is demonstrated. Geological formations are in 3D and commercial GIS packages are normally in 2D. This problem is solved here by a 1D database of the layering of the drillings and export of query results from the database to a 2D GIS. The queries will ask for grain size and altitude for the actual sedimentary layers. To include point data from ground penetrating radar (GPR) data survey profiles in a 2D GIS, a stepwise technique of dynamic segmentation has been developed. The points are digitized along sedimentary boundaries from 2D GPR profiles. The concept was applied on a small area of glacial sediments in Telemark, Norway. Results from the processes were clustering of points with properties connected to specific geological formations. The clustering subsurface geological formations were moraine ridges, a diamict layer, gravel and coarse sand above and below the diamict layer, till above bedrock, and glaciomarine deposits of gravel and sand. Information about extension of these geological formations is useful and essential for modelling of sedimentary environments and for aquifer modelling.  相似文献   

17.
This project combines qualitative data of personal narratives with geographic information science (GIScience) technologies to explore the potential for critical cartography in the study of mass atrocity. The case study used is northern Uganda, where millions have been affected by physical violence and hardship, displacement, and fear. Web-based virtual globes as a ready source of imagery for remote areas and derived spatial data imported to geographic information systems (GIS) provide quantified data that complement testimonials and other qualitative data from the field. Cartographic functions, geovisualization, and spatial analyses available in GIS are used to extract information from high-resolution remote sensing images documenting internally displaced persons (IDP) camps and quantifying evidence of crimes against humanity. These techniques explore spatial relationships and communicate results on the extent and impact of the atrocities in northern Uganda.  相似文献   

18.
ABSTRACT

With large amounts of digital map archives becoming available, automatically extracting information from scanned historical maps is needed for many domains that require long-term historical geographic data. Convolutional Neural Networks (CNN) are powerful techniques that can be used for extracting locations of geographic features from scanned maps if sufficient representative training data are available. Existing spatial data can provide the approximate locations of corresponding geographic features in historical maps and thus be useful to annotate training data automatically. However, the feature representations, publication date, production scales, and spatial reference systems of contemporary vector data are typically very different from those of historical maps. Hence, such auxiliary data cannot be directly used for annotation of the precise locations of the features of interest in the scanned historical maps. This research introduces an automatic vector-to-raster alignment algorithm based on reinforcement learning to annotate precise locations of geographic features on scanned maps. This paper models the alignment problem using the reinforcement learning framework, which enables informed, efficient searches for matching features without pre-processing steps, such as extracting specific feature signatures (e.g. road intersections). The experimental results show that our algorithm can be applied to various features (roads, water lines, and railroads) and achieve high accuracy.  相似文献   

19.
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20.
Pattern analysis techniques currently common within geography tend to focus either on characterizing patterns of spatial and/or temporal recurrence of a single event type (e.g., incidence of flu cases) or on comparing sequences of a limited number of event types where relationships between events are already represented in the data (e.g., movement patterns). The availability of large amounts of multivariate spatiotemporal data, however, requires new methods for pattern analysis. Here, we present a technique for finding associations among many different event types where the associations among these varying event types are not explicitly represented in the data or known in advance. This pattern discovery method, known as T-pattern analysis, was first developed within the field of psychology for the purpose of finding patterns in personal interactions. We have adapted and extended the T-pattern method to take the unique characteristics of geographic data into account and implemented it within a geovisualization toolkit for an integrated computational-geovisual environment we call STempo. To demonstrate how T-pattern analysis can be employed in geographic research for discovering patterns in complex spatiotemporal data, we describe a case study featuring events from news reports about Yemen during the Arab Spring of 2011–2012. Using supplementary data from the Global Database of Events, Language, and Tone, we briefly summarize and reference a separate validation study, then evaluate the scalability of the T-pattern approach. We conclude with ideas for further extensions of the T-pattern technique to increase its utility for spatiotemporal analysis.  相似文献   

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