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Tephra fallout is an important type of hazard caused by explosive volcanic eruption,and numerical simulation has become a fast and effective approach to assess the dispersion and deposition of tephra fallout.According to the improved 2D diffusion model of Suzuki( 1983),we edited a tephra diffusion program that can run in the Windows system.Based on previous data,we simulated the diffusion scope of the Jinlongdingzi volcanic eruption,which is the latest eruption in the Longgang volcanic cluster.The simulated results are in good agreement with the results from measurement in situ,indicating that the model is reliable and the parameters used in the model are suitable.By using wind profiles of ten years,7,021 simulations under different wind profiles were carried out,and then probabilistic hazard maps of tephra fallout were constructed for tephra thickness thresholds,1cm and 0.5cm.This study can provide an important scientific basis for volcanic hazard analysis,risk mitigation plans and countermeasures in the Longgang volcanic area. 相似文献
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Weiwei Duan Yao-Yi Chiang Stefan Leyk Johannes H. Uhl Craig A. Knoblock 《International journal of geographical information science》2020,34(4):824-849
ABSTRACTWith 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
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Gbor Timr Balzs Szkely Gbor Molnr Csaba Ferencz Anik Kern Csilla Galambos Gbor Gercsk Lszl Zentai 《Global and Planetary Change》2008,62(1-2):29-38
The area of Banat, a historical region shared by Romania and Serbia, has been hit by a centennial flood event in spring 2005. The Temes (Tamiš/Timiş) River flooded several hundred km2, with many settlements. The extent of the flood was partly unexpected, especially in positional sense. In order to achieve a better understanding of the phenomenon, we analysed the SRTM digital elevation model as well as historical maps. Several historical maps, dating back to the 16th century, indicate marshland or even a large lake in the area, not existing today but almost exactly coinciding with the extent of the 2005 flood.The historical and archive maps document the water regulation measures taken since the early 19th century. The actual flood is found to be a sort of a restoration of the original natural conditions. Via the analysis of the DEM and historical maps the unexpected extent of the flood scenario can be explained and understood. We suggest that an analysis of historical and archive maps, combined (geo-referenced) with high-resolution DEMS in other flood-endangered areas, should be used in order to be better prepared for decadal or centennial flood events induced by climatic change. 相似文献
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ReinaldoPaulPérezMachado ViolêtaSaldanhaKubrusly Ligia Vizeu Barrozo 陈明玉 顾朝林 《地理研究》2016,35(7):1370-1382
空间数据和地理信息系统在城市规划和决策中应用的重要性日见凸显。主要原因在于:重要的人口数据和社会变动经常表现出一定的空间特性,这种特性可以通过空间分析和统计方法被认识和解释。应用多元分析的空间分类方法编制圣保罗大都市区社会分异地图并进行相关分析。研究的主要数据来自2000年巴西全国人口普查,其中包括了圣保罗大都市的所有行政区和39个自治市的21774个人口普查区。为了把都市连绵区从数据全集中分离出来,我们采用混合技术进行互补分析,即在2000年4月30日的陆地卫星7号图像中绘制一个个多边形,这些被识别出来的多边形就是人口普查区。然后,通过目视解译出假彩色多边形集合。应用空间分类评分程序将这些多边形分成五类,并建立人口普查区的数目、覆盖的面积和都市连绵区之间的关系。这种多元分析方法是基于变量的均衡化来生成易于用分级统计图描述平均值,以促进可视化和后续的空间分布分析。基于多元分析的空间分类方法研究,清楚地展现了圣保罗大都市最重要的社会特征,也说明城市社会地图方法和多元分析的空间分类方法在大都市区的管理、公共政策规划和复杂决策中具有重要的应用价值。 相似文献
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TELLEZ Ricardo Delgado WANG Shaohua ZHONG Ershun CAI Wenwen LONG Liang 《资源与生态学报(英文版)》2016,7(6):430-438
This paper uses the expected utility under risk hypothesis to develop a new approach to GIS modeling for land use suitability analysis with competitive learning algorithms (CLG-LUSA). It uses Kohonen’s Self Organized Maps (SOM) and Linear Vector Quantization (LVQ) among other tools to create comprehensive ordering of high number of options. The model uses decision makers preferred locations and environmental data to construct a manifold of the decision’s attribute space. Then, decision and uncertainty maps are derived from this manifold. An application example is provided using the selection of suitable environments for coconut development in a municipality of Cuba. CLG-LUSA model was able to provide accurate visual feedback of key aspects of the decision process, making the methodology suitable for personal or group decision making. 相似文献