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In the context of OpenStreetMap (OSM), spatial data quality, in particular completeness, is an essential aspect of its fitness for use in specific applications, such as planning tasks. To mitigate the effect of completeness errors in OSM, this study proposes a methodological framework for predicting by means of OSM urban areas in Europe that are currently not mapped or only partially mapped. For this purpose, a machine learning approach consisting of artificial neural networks and genetic algorithms is applied. Under the premise of existing OSM data, the model estimates missing urban areas with an overall squared correlation coefficient (R 2) of 0.589. Interregional comparisons of European regions confirm spatial heterogeneity in the model performance, whereas the R 2 ranges from 0.129 up to 0.789. These results show that the delineation of urban areas by means of the presented methodology depends strongly on location.  相似文献   
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Obituary     
《The Cartographic journal》2013,50(4):315-322
Abstract

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In the area of volunteered geographical information (VGI), the issue of spatial data quality is a clear challenge. The data that are contributed to VGI projects do not comply with standard spatial data quality assurance procedures, and the contributors operate without central coordination and strict data collection frameworks. However, similar to the area of open source software development, it is suggested that the data hold an intrinsic quality assurance measure through the analysis of the number of contributors who have worked on a given spatial unit. The assumption that as the number of contributors increases so does the quality is known as ‘Linus’ Law’ within the open source community. This paper describes three studies that were carried out to evaluate this hypothesis for VGI using the OpenStreetMap dataset, showing that this rule indeed applies in the case of positional accuracy.  相似文献   
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Fine-resolution population mapping using OpenStreetMap points-of-interest   总被引:1,自引:0,他引:1  
Data on population at building level is required for various purposes. However, to protect privacy, government population data is aggregated. Population estimates at finer scales can be obtained through areal interpolation, a process where data from a first spatial unit system is transferred to another system. Areal interpolation can be conducted with ancillary data that guide the redistribution of population. For population estimation at the building level, common ancillary data include three-dimensional data on buildings, obtained through costly processes such as LiDAR. Meanwhile, volunteered geographic information (VGI) is emerging as a new category of data and is already used for purposes related to urban management. The objective of this paper is to present an alternative approach for building level areal interpolation that uses VGI as ancillary data. The proposed method integrates existing interpolation techniques, i.e., multi-class dasymetric mapping and interpolation by surface volume integration; data on building footprints and points-of-interest (POIs) extracted from OpenStreetMap (OSM) are used to refine population estimates at building level. A case study was conducted for the city of Hamburg and the results were compared using different types of POIs. The results suggest that VGI can be used to accurately estimate population distribution, but that further research is needed to understand how POIs can reveal population distribution patterns.  相似文献   
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Quality assessment of OpenStreetMap data using trajectory mining   总被引:1,自引:0,他引:1  
OpenStreetMap (OSM) data are widely used but their reliability is still variable. Many contributors to OSM have not been trained in geography or surveying and consequently their contributions, including geometry and attribute data inserts, deletions, and updates, can be inaccurate, incomplete, inconsistent, or vague. There are some mechanisms and applications dedicated to discovering bugs and errors in OSM data. Such systems can remove errors through user-checks and applying predefined rules but they need an extra control process to check the real-world validity of suspected errors and bugs. This paper focuses on finding bugs and errors based on patterns and rules extracted from the tracking data of users. The underlying idea is that certain characteristics of user trajectories are directly linked to the type of feature. Using such rules, some sets of potential bugs and errors can be identified and stored for further investigations.  相似文献   
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地面站导航电子地图是操作员用来监控无人驾驶装备的唯一平台,也是进行线路规划和自主决策的重要信息源。现有的导航电子地图一般存在价格昂贵、对高程数据支持不足以及依赖互联网等缺陷。本文提出了一种新的基于OpenStreetMap的地面站导航电子地图实现方法。首先,利用原始OSM数据搭建地图瓦片服务后台;然后将90 m SRTM高程数据处理成地形阴影和地形颜色渐变栅格文件;针对每个栅格文件,在瓦片服务后台的样式配置文件中添加相应图层并定义其渲染格式;最后,在地面站软件中实现地图客户端模块,向瓦片服务后台请求瓦片,并显示在地面站界面上。利用该方法实现的地面站导航电子地图可以提供0~18个缩放级别的中国范围的数据,显示0~13个缩放级别的立体地形地貌,并且无需互联网支持。本文使用该方法实现了某型无人机的地面站导航电子地图模块,并成功应用该无人机仿真系统。  相似文献   
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利用OpenStreetMap数据进行高空间分辨率遥感影像分类   总被引:1,自引:0,他引:1  
针对高分辨率遥感影像分类样本标注困难的问题,提出了一种利用OpenStreetMap (OSM)数据自动获取标注样本的方法。与现有的利用OSM数据进行分类的方法不同,该方法加入了空间特征以弥补单独使用光谱特征分类的不足。首先,基于OSM数据提供的地物类别和位置信息进行样本标注,为了降低OSM数据中少量错误信息对分类结果的影响,采用聚类分析的方法对样本进行提纯;其次,使用形态学轮廓来提取影像的结构特征,挖掘高分辨率遥感影像丰富的空间信息,与光谱特征相叠加并输入分类器进行分类。试验证明,本文提出的方法能够有效避免人工样本标注所需要的人力物力;同时,联合影像的光谱空间特征能够更好地描述地物特性,得到较高的分类精度。  相似文献   
40.
ABSTRACT

OpenStreetMap (OSM) database has previously been used to support spatial disaggregation of population data by partly masking out non-residential impervious areas in the European Copernicus imperviousness layer (IL). However, the exact procedure of OSM data incorporation is unknown, and its contribution to the improvement of estimation accuracy has never been studied. In this article, we present a sensitivity study to find out which road categories should be used for masking of IL and how the linear features might be transformed to raster representation. Using Austria and Slovenia as a study area, 2006 commune population counts are disaggregated into 100 m grid cells using 12 versions of modified IL. Further tuning of estimates is performed using CORINE Land Cover (CLC) data in an iterative algorithm. Disaggregated grids are then validated against reference 1 km census-based data. The results show that overall error was reduced thanks to OSM incorporation in all tested scenarios, although the relative improvement varies between as well as within the two countries. The best result (5.3% reduction) was achieved using railways and three major road categories (motorway, trunk, and primary) with double exaggeration of width.  相似文献   
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