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1.
ABSTRACT

Road intersection data have been used across a range of geospatial analyses. However, many datasets dating from before the advent of GIS are only available as historical printed maps. To be analyzed by GIS software, they need to be scanned and transformed into a usable (vector-based) format. Because the number of scanned historical maps is voluminous, automated methods of digitization and transformation are needed. Frequently, these processes are based on computer vision algorithms. However, the key challenges to this are (1) the low conversion accuracy for low quality and visually complex maps, and (2) the selection of optimal parameters. In this paper, we used a region-based deep convolutional neural network-based framework (RCNN) for object detection, in order to automatically identify road intersections in historical maps of several cities in the United States of America. We found that the RCNN approach is more accurate than traditional computer vision algorithms for double-line cartographic representation of the roads, though its accuracy does not surpass all traditional methods used for single-line symbols. The results suggest that the number of errors in the outputs is sensitive to complexity and blurriness of the maps, and to the number of distinct red-green-blue (RGB) combinations within them.  相似文献   

2.
Abstract

Map compilation, or conflation, is now being accomplished by computer. Interactive routines manipulate the graphic images of two different digital maps of the same region in order to permit map similarities and differences to be recognized more easily. Rubber-sheeting one or both of the maps permits an operator or the computer to align the maps in stages through methods of successive approximation and to review each new alignment. The computer recognizes matches using mathematical relations of geometric position and graph network configuration to test for feature matches and, when the tests are satisfied, corresponding features can be flagged automatically as matches or highlighted for review by the operator. Techniques and methods developed for conflation systems have important applications in other areas of automated cartography and in image processing and computer graphics  相似文献   

3.
ABSTRACT

The importance of including a contextual underpinning to the spatial analysis of social data is gaining traction in the spatial science community. The challenge, though, is how to capture these data in a rigorous manner that is translational. One method that has shown promise in achieving this aim is the spatial video geonarrative (SVG), and in this paper we pose questions that advance the science of geonarratives through a case study of criminal ex-offenders. Eleven ex-offenders provided sketch maps and SVGs identifying high-crime areas of their community. Wordmapper software was used to map and classify the SVG content; its spatial filter extension was used for hot spot mapping with statistical significance tested using Monte Carlo simulations. Then, each subject’s sketch map and SVG were compared. Results reveal that SVGs consistently produce finer spatial-scale data and more locations of relevance than the sketch maps. SVGs also provide explanation of spatial-temporal processes and causal mechanisms linked to specific places, which are not evident in the sketch maps. SVG can be a rigorous translational method for collecting data on the geographic context of many phenomena. Therefore, this paper makes an important advance in understanding how environmentally immersive methods contribute to the understanding of geographic context.  相似文献   

4.
One common problem with geographic data is that, for a specific geographic event, only occurrence information is available; information about the absence of the event is not available. We refer to these specific types of geospatial data as geographic one-class data (GOCD). Predicting the potential spatial distributions that a particular geographic event may occur from GOCD is difficult because traditional binary classification methods that require availability of both positive and negative training samples cannot be used. The objective of this research is to define GOCD and propose novel approaches for modelling potential spatial distributions of geographic events using GOCD. We investigate the effectiveness of one-class support vector machine (OCSVM), maximum entropy (MAXENT) and the newly proposed positive and unlabelled learning (PUL) algorithm for solving GOCD problems using a case study: species distribution modelling from synthetic data. Our experimental results indicate that generally OCSVM, MAXENT and PUL are effective in modelling the GOCD. Each method has advantages and disadvantages, but PUL seems to be the most promising method.  相似文献   

5.
ABSTRACT

Terrain feature detection is a fundamental task in terrain analysis and landscape scene interpretation. Discovering where a specific feature (i.e. sand dune, crater, etc.) is located and how it evolves over time is essential for understanding landform processes and their impacts on the environment, ecosystem, and human population. Traditional induction-based approaches are challenged by their inefficiency for generalizing diverse and complex terrain features as well as their performance for scalable processing of the massive geospatial data available. This paper presents a new deep learning (DL) approach to support automatic detection of terrain features from remotely sensed images. The novelty of this work lies in: (1) a terrain feature database containing 12,000 remotely sensed images (1,000 original images and 11,000 derived images from data augmentation) that supports data-driven model training and new discovery; (2) a DL-based object detection network empowered by ensemble learning and deep and deeper convolutional neural networks to achieve high-accuracy object detection; and (3) fine-tuning the model’s characteristics and behaviors to identify the best combination of hyperparameters and other network factors. The introduction of DL into geospatial applications is expected to contribute significantly to intelligent terrain analysis, landscape scene interpretation, and the maturation of spatial data science.  相似文献   

6.
ABSTRACT

Spatiotemporal association pattern mining can discover interesting interdependent relationships among various types of geospatial data. However, existing mining methods for spatiotemporal association patterns usually model geographic phenomena as simple spatiotemporal point events. Therefore, they cannot be applied to complex geographic phenomena, which continuously change their properties, shapes or locations, such as storms and air pollution. The most salient feature of such complex geographic phenomena is the geographic dynamic. To fully reveal dynamic characteristics of complex geographic phenomena and discover their associated factors, this research proposes a novel complex event-based spatiotemporal association pattern mining framework. First, a complex geographic event was hierarchically modeled and represented by a new data structure named directed spatiotemporal routes. Then, sequence mining technique was applied to discover the spatiotemporal spread pattern of the complex geographic events. An adaptive spatiotemporal episode pattern mining algorithm was proposed to discover the candidate driving factors for the occurrence of complex geographic events. Finally, the proposed approach was evaluated by analyzing the air pollution in the region of Beijing-Tianjin-Hebei. The experimental results showed that the proposed approach can well address the geographic dynamic of complex geographic phenomena, such as the spatial spreading pattern and spatiotemporal interaction with candidate driving factors.  相似文献   

7.

Significant interaction challenges arise in both developing and using interactive map applications. Users encounter problems of information overload in using interactive maps to complete tasks. This is further exacerbated by device limitations and interaction constraints in increasingly popular mobile platforms. Application developers must then address restrictions related to screen size and limited bandwidth in order to effectively display maps on mobile devices. In order to address issues of user information overload and application efficiency in interactive map applications, we have developed a novel approach for delivering personalized vector maps. Ongoing task interactions between users and maps are monitored and captured implicitly in order to infer individual and group preferences related to specific map feature content. Personalized interactive maps that contain spatial feature content tailored specifically to users' individual preferences are then generated. Our approach addresses spatial information overload by providing only the map information necessary and sufficient to suit user interaction preferences, thus simplifying the completion of tasks performed with interactive maps. In turn, tailoring map content to specific user preferences considerably reduces the size of vector data sets necessary to transmit and render maps on mobile devices. We have developed a geographic information system prototype, MAPPER (MAP PERsonalization), that implements our approach. Experimental evaluations show that the use of personalized maps helps users complete their tasks more efficiently and can reduce information overload.  相似文献   

8.
Abstract

This paper describes the architecture and working of a recently implemented knowledge-based GIS (KBGIS-II) that was designed to satisfy several general criteria for GIS. The system has four major functions, query-answering, learning, editing and training. The main query finds constrained locations for spatial objects that are describable in a predicate-calculus based spatial object language. The main search procedures include a family of constraint-satisfaction procedures that use a spatial object knowledge base to search efficiently for complex spatial objects in large, multi-layered spatial data bases. These data bases are represented in quadtree form. The search strategy is designed to reduce the computational cost of search in the average case. The learning capabilities of the system include the addition of new locations of complex spatial objects to the knowledge base as queries are answered, and the ability to learn inductively definitions of new spatial objects from examples. The new definitions are added to the knowledge base by the system. The system is currently performing all its designated tasks successfully, although currently implemented on inadequate hardware.  相似文献   

9.
《The Journal of geography》2012,111(4):188-189
Abstract

Through analysis of census data, these lessons cover geographic concepts dealing with migration and population change in the United States. Students discuss the historical push and pull factors of immigration to the United States. By focusing on the recent influx of Hispanic immigrants, students look at the geographic concepts of assimilation, discrimination, and time-decay. Students also create graphs and maps to examine the recent increase in the United States Hispanic population and geographic patterns of Hispanic settlement.  相似文献   

10.
This paper develops a knowledge discovery procedure for extracting knowledge of soil-landscape models from a soil map. It has broad relevance to knowledge discovery from other natural resource maps. The procedure consists of four major steps: data preparation, data preprocessing, pattern extraction, and knowledge consolidation. In order to recover true expert knowledge from the error-prone soil maps, our study pays specific attention to the reduction of representation noise in soil maps. The data preprocessing step has exhibited an important role in obtaining greater accuracy. A specific method for sampling pixels based on modes of environmental histograms has proven to be effective in terms of reducing noise and constructing representative sample sets. Three inductive learning algorithms, the See5 decision tree algorithm, Naïve Bayes, and artificial neural network, are investigated for a comparison concerning learning accuracy and result comprehensibility. See5 proves to be an accurate method and produces the most comprehensible results, which are consistent with the rules (expert knowledge) used in producing the soil map. The incorporation of spatial information into the knowledge discovery process is found not only to improve the accuracy of the extracted knowledge, but also to add to the explicitness and extensiveness of the extracted soil-landscape model.  相似文献   

11.
基于等值线分布区域树的分层设色图自动生成研究   总被引：1，自引：0，他引：1  
基于ArcGIS Engine的核心组件功能实现了空间离散点生成等值线,并针对ArcGIS Engine在生成等值线分布区域方面的不足,提出采用等值线分割确定研究区域边界、构建等值线分布区域树的算法,实现了等值线分布区域、拓扑关系构建及高程值的计算,最终实现了分层设色图的自动生成。通过浙江省金华市地下水水位等值线与分层设色图的自动生成试验,表明该文的技术路线是可行的。  相似文献   

12.
Sketching as a natural mode for human communication and creative processes presents opportunities for improving human–computer interaction in geospatial information systems. However, to use a sketch map as user input, it must be localized within the underlying spatial data set of the information system, the base metric map. This can be achieved by a matching process called qualitative map alignment in which qualitative spatial representations of the two input maps are used to establish correspondences between each sketched object and one or more objects in the metric map. The challenge is that, to the best of our knowledge, no method for matching qualitative spatial representations suggested so far is applicable in realistic scenarios due to excessively long runtimes, incorrect algorithm design or the inability to use more than one spatial aspect at a time. We address these challenges with a metaheuristic algorithm which uses novel data structures to match qualitative spatial representations of a pair of maps. We present the design, data structures and performance evaluation of the algorithm using real-world sketch and metric maps as well as on synthetic data. Our algorithm is novel in two main aspects. Firstly, it employs a novel system of matrices known as local compatibility matrices, which facilitate the computation of estimates for the future size of a partial alignment and allow several types of constraints to be used at the same time. Secondly, the heuristic it computes has a higher accuracy than the state-of-the-art heuristic for this task, yet requires less computation. Our algorithm is also a general method for matching labelled graphs, a special case of which is the one involving complete graphs whose edges are labelled with spatial relations. The results of our evaluation demonstrate practical runtime performance and high solution quality.  相似文献   

13.
ABSTRACT

High performance computing is required for fast geoprocessing of geospatial big data. Using spatial domains to represent computational intensity (CIT) and domain decomposition for parallelism are prominent strategies when designing parallel geoprocessing applications. Traditional domain decomposition is limited in evaluating the computational intensity, which often results in load imbalance and poor parallel performance. From the data science perspective, machine learning from Artificial Intelligence (AI) shows promise for better CIT evaluation. This paper proposes a machine learning approach for predicting computational intensity, followed by an optimized domain decomposition, which divides the spatial domain into balanced subdivisions based on the predicted CIT to achieve better parallel performance. The approach provides a reference framework on how various machine learning methods including feature selection and model training can be used in predicting computational intensity and optimizing parallel geoprocessing against different cases. Some comparative experiments between the approach and traditional methods were performed using the two cases, DEM generation from point clouds and spatial intersection on vector data. The results not only demonstrate the advantage of the approach, but also provide hints on how traditional GIS computation can be improved by the AI machine learning.  相似文献   

14.
李凡  朱竑  黄维 《地理科学》2009,29(6):929-937
明以来佛山逐渐形成八图土著宗族文化景观和侨寓宗族文化景观并存的格局,对佛山城市空间发展产生影响。通过从古地图和文献中提取历史时期基本空间数据和祠堂等文化景观地理信息,建立佛山历史GIS数据库。以此为基础,通过景观复原、地图再现、空间分析和景观分析等方法,以祠堂景观为视角,解读明至民国初期佛山宗族文化景观时空演变及其所意涵的社会文化空间意义。结果表明:①宋元时期祠堂主要集中在佛山南部大塘涌沿岸,反映出宋代涌入佛山的移民早期多定居在南部;②明代佛山镇祠堂数量急增,表现出聚落空间由南部向中部扩展的趋势,祠堂景观基本形成了以南部的锦澜、东头、栅下铺和中部的祖庙、黄伞铺为中心的空间格局;③清以后祠堂景观总体空间格局没有大变化,但八图土著宗族内部产生的裂变促使土著祠堂景观发生空间扩散。土著祠堂与侨寓祠堂景观空间上既互补又相互混杂,说明随着侨寓的大量进入,土著传统血缘空间被打破,地缘、业缘等因素增强,这正适应了佛山城市化发展的大趋势。  相似文献   

15.
《The Journal of geography》2012,111(5):241-245
Abstract

Construction of raised-relief maps by students in middle school to high school is a rewarding “hands-on” experience. A major feature of this project is that materials are readily available, inexpensive and manageable by students themselves. Tracing from topographic maps on to inexpensive, easily-carved materials like cardboard or foam-core board involves the student in map interpretation techniques. Concepts such as interpreting elevations from contour lines, recognizing symbolization on a map, seeing raised-relief as representing “the lay of the land,” understanding map scale, and recognition of color in representation of elevations are part of this experience. Carving and construction of the raised-relief map give the student an appreciation of topographic features in 3-D. The finished model can serve as a display and learning tool for the future.  相似文献   

16.
长时间序列的土地利用/ 土地覆被数据是开展全球变化、可持续发展及生态安全等各项研究的重要基础。然而,早期的土地利用/ 土地覆被数据,特别是卫星遥感数据出现之前 的土地利用/ 土地覆被信息通常很难获取。利用TM、MSS 遥感影像数据和地形图、气候、地质、地貌、土壤、植被、水文等自然环境背景图件以及数据,社会经济统计数据等多源数 据,选择大庆市杜尔伯特蒙古族自治县作为典型案例区,在GIS 技术支持下建立了土地利用/ 土地覆被数字重建模型,再现了典型研究区20 世纪30 年代和50 年代土地利用/ 土地覆被空间分布状况。通过野外调查和历史文献资料对土地利用数字重建结果进行精度评价并初步得到以下结论：① 采用逐个图斑跟踪记录的方法对研究区各个时期土地利用/ 覆被变化的敏感 性进行分析,有利于揭示区域土地利用/ 土地覆被变化的规律;② 在定量、定位分析环境背景对土地利用/ 土地覆被分布及其变化的影响基础上,综合判断各种土地利用/ 土地覆被分布概率,其结果可为土地利用数字重建提供依据;③ 对1:10 万地形图提取土地利用信息的可行性与可信度分析表明,地形图中土地利用信息完全能够达到一级土地利用分类精度,同时疏林地、灌木林、沼泽地、盐碱地、沙地等二级分类信息也能获取。  相似文献   

17.
Clustering allows considering groups of similar data elements at a higher level of abstraction. This facilitates the extraction of patterns and useful information from large amounts of spatio-temporal data. Till now, most studies have focused on the extraction of patterns from a spatial or a temporal aspect. Here we use the Bregman block average co-clustering algorithm with I-divergence (BBAC_I) to enable the simultaneous analysis of spatial and temporal patterns in geo-referenced time series (time evolving values of a property observed at fixed geographical locations). In addition, we present three geovisualization techniques to fully explore the co-clustering results: heatmaps offer a straightforward overview of the results; small multiples display the spatial and temporal patterns in geographic maps; ringmaps illustrate the temporal patterns associated to cyclic timestamps. To illustrate this study, we used Dutch daily average temperature data collected at 28 weather stations from 1992 to 2011. The co-clustering algorithm was applied hierarchically to understand the spatio-temporal patterns found in the data at the yearly, monthly and daily resolutions. Results pointed out that there is a transition in temperature patterns from northeast to southwest and from ‘cold’ to ‘hot’ years/months/days with only 3 years belonging to ‘cool’ or ‘cold’ years. Because of its characteristics, this newly introduced algorithm can concurrently analyse spatial and temporal patterns by identifying location-timestamp co-clusters that contain values that are similar along both the spatial and the temporal dimensions.  相似文献   

18.
《The Journal of geography》2012,111(3):131-136
Abstract

This article describes the benefits of combining field-based learning within the context of a competitive setting in the geography curriculum. Findings and data are presented based on experiences gathered from teaching an upper-level university geography course that combined geographic techniques and theory into a game of capture-the-flag. Students analyzed a variety of geospatial data sources, using ArcMap Geographic Information System software, to prepare a series of maps for the game. Students reported a first-time understanding of many geographic skills that were previously ambiguous to them when the material was presented in a different format, such as lectures and labs.  相似文献   

19.
目前普遍使用的基于图层的空间数据库模型存在许多问题。基于特征的空间数据库模型是一种新的空间数据存储模式,它在很大程度上代表了GIS的发展方向。采用超图数据模型分析、设计和描述土地利用特征在概念和逻辑层次的提取与定义,建立土地特征分类体系,进行基于特征的土地利用空间数据库建模。  相似文献   

20.
利用卷积神经网络从遥感影像中提取水体时,水体对象边缘像素的特征与内部像素的特征之间往往存在较大差异,导致提取结果中边界模糊、内部像素与边缘像素的提取精度差异较大,影响了整体精度的提高。针对如何从高分辨率遥感影像中进行水体高精度、自动化提取的问题,文章首先以高分辨率遥感图像为基础,利用边缘提取算法生成边缘图像,然后以高分辨率遥感图像和边缘图像作为输入,建立了语义特征和边缘特征融合的高分辨率遥感图像水体提取模型（Semantic Feature and Edge Feature Fusion Network, SEF-Net）,用于从高分辨率遥感图像中提取水体对象。实验结果表明,SEF-Net模型在3个数据集中的召回率（91.97%、92.07%、93.97%）,精确率（91.12%、98.37%、97.88%）,准确率（89.56%、95.07%、94.06%）和F1分数（91.54%、95.12%、95.88%）均优于对比模型,说明SEF-Net模型从高分辨率遥感图像中提取水体时,具有更高的精度和泛化能力。  相似文献   

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