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1.
从自发地理信息(VGI)的概念与应用出发,对国内外相关研究中较有代表性的文献进行分析,并从数据的管理理论基础及其对实践活动的积极作用两个方面入手,对VGI技术的管理与应用进行探讨。结果表明:在全球范围内,VGI数据的研究热度不断增加,并主要集中于极具实践意义的两个方面:一是对VGI数据的管理研究,包括对数据的质量评价及高效管理方式的探索;二是在诸如地面信息采集、旅游景观研究、灾害监控预防等维度对VGI数据的应用研究。同时,随着Web技术、GIS技术的成熟以及社交媒体、便携式GPS终端设备的普及,VGI数据将得到更为广泛的应用,并将在旅游业领域扮演日益重要的角色。 相似文献
2.
基于GIS的区县级暴雨洪涝风险评估方法 总被引：1，自引：0，他引：1
在全球变暖大背景下,极端灾害性天气事件频繁发生,其中以暴雨洪涝灾害表现最为明显。文章基于灾害系统理论及风险评估原理,利用基础地理数据、气象数据、社会经济数据、历史灾情数据等,分别从致灾因子危险性、孕灾环境敏感性、承灾体易损性、防灾减灾能力4个评价指标,建立基于评价因子的暴雨洪涝风险评估模型,并指出区县级暴雨洪涝风险评估需要解决的重点问题包括数据空间化、气象数据的序列延长、参数的确定等。最后以暴雨洪涝多发地区福建省石狮市（县级市）为研究区,利用GIS技术生成100 m×100 m分辨率的致灾因子危险性空间分布图、孕灾环境敏感性空间分布图、承灾体易损性空间分布图、防灾减灾能力空间分布图、暴雨洪涝风险评估空间分布图。结果显示：风险最高地区主要位于湖滨街道和凤里街道;其次是祥芝镇东部和西部,灵秀镇大部份地区、蚶江镇中南部、宝盖镇中南部和锦尚镇大部分地区;风险较低的地区主要是蚶江镇北部、宝盖镇北部和永宁镇大部分地区。 相似文献
3.
1949-2015年中国典型自然灾害及粮食灾损特征 总被引：6，自引：0，他引：6
中国是一个自然灾害频发的国家,研究其自然灾害演变特征及粮食灾损规律,对实现中国社会经济可持续发展、解决中国粮食安全问题具有重要意义。本文先基于Python语言编程获取1949-2015年中国31省市自然灾害造成的受灾、成灾、绝收面积,构建灾害强度指数分析不同灾种的时序特征分异,利用趋势分析、ESDA方法分析不同灾种在省域空间的分布特征及冷热区;再获取1949-2015年粮食种植数据,通过粮食灾损估算模型、定义粮食灾损率、地理空间探测器,计算并检验中国粮食损失时空特征及分异性。结果表明：① 相比受灾面积曲线,本文构建的灾害程度指数能够更好揭示自然灾害时序演变特征;② 1949-2015年期间中国两大主力灾害（洪灾、旱灾）交替出现,未来5~10年以洪灾为主;③ 灾种排序旱灾>洪灾>风雹>低温>台风,其中旱灾、洪灾受灾占比过半;④ 省域不同灾种间空间趋势变化特征明显,区域受灾面积东部>西部,北部>南部,且北部灾种单一、南部多灾并发;⑤ 自然灾害受灾总和、旱灾、雹灾、低温空间上全局自相关性不显著,呈随机模式分布,洪涝、台风在空间分布上具有显著的全局自相关性,呈集聚模式;⑥ 1949-2015年灾害、灾损量、灾损率整体时序趋势呈现先升后降,2000年为临界点,空间分布具有异质性,单因子解释力度差异显著,多因子交互均呈非线性增强关系,胡焕庸线两侧冷热点分布呈两极化且其重心向北迁移。建议政府加强除旱减雹（西北）、除旱排内涝（东北）、排涝防冻（中部）、排涝预台（东南沿海）等工程技术措施;同时西北（环境恶劣）、东北（中国粮仓）应作为防灾减灾重点保护区,制定专项保护方案,以保证中国粮食丰产增收。 相似文献
4.
地理科学发展与新技术应用 总被引：3，自引：3，他引：0
当代计算机、互联网、航天航空、自动化和传感网、环境和生态修复等技术发展很快,并渗透到许多基础与应用基础研究学科。以综合性、交叉性和区域性为特点的地理学借力于新技术应用,学科发展得到有力促进,突出表现包括：① 研究时空拓展到近实时和全球,基本解决异域和极端地理环境数据难获取问题;② 数据获取方式和渠道多样性促进了数据的爆发性增加,对规律和格局的分析从依赖有限时空表观信息发展到依靠新技术获取高时空动态数据开展大数据挖掘;③ 研究内容从静态知识获取、机理分析拓展到包括生态修复和环境治理等能动性的工作;④ 学科发展呈现领域拓展和新技术学科交叉趋势,地理学通过与新技术进一步融合发展获得新生命力。借助新技术和地理大数据“燃料”的注入,新时期地理科学发展将在全球和区域社会经济建设过程中通过提供“复方”解决方案而发挥重要的作用。 相似文献
5.
《山地学报》2016,(1)
彭州地处成都平原与龙门山的过渡地带,土地利用状况具有强度高、类型多、复杂度大的特点,土地类型变化非常快。同时,"5·12"汶川大地震严重破坏了该区域的生态环境,这场大灾难导致了地震灾区土地利用在类型和结构上都发生了巨大变化。因此,如何快速的获取最新的土地利用信息对于灾后重建及政府决策具有重要意义。利用无人机高空间分辨率影像作为数据源,首先引入SIFT算法完成了无人机影像的自动拼接,然后采用面向对象的分析技术获取了两期无人机影像的土地利用类型,着重研究了影像最优分割尺度的获取,最后建立了土地利用动态监测系统获取了两期土地利用信息的变化量,提出了一种适用于四川盆地多云雾山地区域土地信息动态监测方法。通过对实验区两期影像的分析研究,快速获取了各类型地类的变化量,并对变化原因进行了分析。研究结果表明:利用无人机影像进行土地利用动态监测能克服多云雾山地区域卫星影像难以实时获取问题,能快速、高效的获得土地变更信息。 相似文献
6.
文章以环北京地区资源与生态环境遥感监测项目为依托,讨论了资源与生态环境遥感监测业务化工作中数据预处理、信息提取、动态监测分析、外业调查、数据质量控制等技术关键环节,并重点阐述了资源与生态环境遥感监测工作中亟需解决的若干问题及思路,以期为今后全国范围内资源与生态环境遥感监测提供指导和借鉴。 相似文献
7.
运用RS、GPS和GIS技术进行大比例尺土地利用动态监测的实验研究 总被引：42，自引：5，他引：37
土地利用数据的更新是土地管理工作的重要内容之一。依靠常规的手段不仅更新速度慢、难以主动发现变化区域,而且成图周期长、误差大。依靠遥感（RS）手段可以主动快速地发现变化区域,运用差分GPS技术可以精确获取土地利用变化的数量和性质,GIS则是管理土地利用的图形数据和属性数据（如土地利用类型、权属、图斑号等）的有效工具。基于RS、GIS和GPS的集成技术建立面向工程目标的土地利用动态监测新方法是本文研究的内容。 相似文献
8.
GIS在河流洪泛区灾害监测中应用研究 总被引：6，自引：3，他引：6
以灾前、灾中、灾后为三条主线，应用“3S”技术、卫星通信技术及防洪决策支持系统等多种高新技术建立的一个复杂和难度大的业务运行系统，及时、准确地监测和评估辽河下游地区洪灾及其损失，为决策部门提供现势、客观数据与决策辅助方案。 相似文献
9.
《西部资源》2017,(1)
通过对灾后重建土地利用规划编制过程中关键性问题研究,用科学合理的规划手段来规范和调整人类活动行为,从而使自然灾害对人类造成的伤害及损失降到最低限度。通过定性分析法、描述性研究法、经验总结法。其结果表明,探索建立土地利用规划快速反应机制,以逐步提高其科学性和适应性,也为今后开展灾后重建土地利用规划提供有益探索和参考依据。由此可见,灾后重建土地利用规划应更注重跨越性和提升性,应有更长远的考虑,将灾后重建和人类的可持续发展结合起来。在灾后土地利用规划编制的基础上,通过做好规划环境影响评价、强化公众参与、建立规划实施监测及评估机制等,强化土地利用规划对土地利用的引导作用。 相似文献
10.
南极数据管理是南极条约协商会议（ＡＴＣＭ）、南极科学研究委员会（ＳＣＡＲ）、国家南极局局长理事会（ＣＯＭＮＡＰ）共同关心并且一直关注的热点问题，也是以新的研究方式、先进的技术手段来积极促进国际南极研究发展的综合性问题。南极数据管理特别规划组在一些成员国和国际机构作出许多主动性努力的基础上把建立和开发南极数据目录系统（ＡＤＤＳ）作为建立和发展国际南极数据（信息）管理系统的首要基础建设加以规划。ＳＣＡＲ－ＣＯＭＮＡＰ南极数据管理联合委员会（ＪＣＡＤＭ）将全面组织和协调国际南极数据管理工作的发展和ＡＤＤＳ的实施。本文介绍了相关的国际背景，解析了南极数据管理国际框架的构成。在这个基本框架下，针对我国南极数据管理工作的现实情况进行了初部探讨，提出了便于付诸实际操作的若干方法，并阐述了相应的学术见解。 相似文献
11.
汶川Ms 8.0地震极重灾区的经济韧性测度及恢复效率 总被引：1，自引：0，他引：1
揭示灾后经济发展状态和恢复过程,按照灾区经济韧性科学制定灾后经济重建的调控政策与恢复手段,对增强灾害防范与系统应对能力具有重要意义。以汶川地震极重灾区为案例,基于长时序社会经济面板数据与ARIMA模型,测算灾区经济韧性指数,并运用改进的规模报酬可变DEA模型、Malmquist生产率指数分析灾后年际经济恢复效率及影响效应。结果显示：① 汶川地震极重灾区经济韧性指数为0.877,地震导致灾区短期经济衰退,但2年内恢复至震前水平,工业经济韧性低于农业和服务业。② 受灾当年灾区经济恢复综合效率为0.603,其中,平原丘陵区综合效率、纯技术效率、规模效率均显著优于高原山地区。③ 灾后全要素生产率的年际波动强烈,经济恢复效率显著下降造成短期经济衰退,灾后2年TFP指数下降33.7%和15.2%后恢复至稳态。④ 灾后恢复效率显著下降主因为技术变动因素,而生产体系更新程度决定了灾后经济韧性。随着灾后经济恢复的规模收益下降,灾区经济恢复主要依赖纯技术效率,提升纯技术效率是保持灾后经济长期增长的动力。可见,针对重建自然条件和经济发展阶段的差异性,灾区当地需积极进行经济结构调整和再适应,同时,通过生产体系更新提升技术进步水平,以发挥灾后大规模资金、设施、人力等要素投入的规模效应,从而增强应对灾害冲击的经济韧性与恢复效率。 相似文献
12.
《地理学报(英文版)》2020,(8)
The border areas of the Tibetan Plateau and the neighboring mountainous areas have a high incidence of earthquakes with a magnitude greater than Ms 5.0, as well as having a dense distribution of geological disasters such as collapses, landslides, and debris flows. Revealing the post-disaster economic development and recovery process is very important for enhancing disaster prevention and response capacity in order to formulate control policies and recovery methods for post-disaster economic reconstruction based on economic resilience. Using long-term socioeconomic data and the autoregressive integrated moving average(ARIMA) model, this paper calculated the economic resilience index of the areas most severely affected by the Wenchuan Earthquake of 2008 and adopted the improved variable returns to scale(VRS) date envelopment analysis(DEA) model and the Malmquist productivity index to analyze the efficiency and effect of annual post-disaster recovery. The results show that:(1) the economic resilience index of the areas most severely affected by the Wenchuan Earthquake was 0.877. The earthquake resulted in a short-term economic recession in the affected areas, but the economy returned to pre-quake levels within two years. In addition, the industrial economy was less resilient than agriculture and the service industry.(2) The comprehensive economic recovery efficiency of the disaster-stricken area in the year following the disaster was 0.603. The comprehensive efficiency, the pure technical efficiency, and the scale efficiency of the plain and hilly areas were significantly greater than those of the plateau and mountain areas.(3) The annual fluctuation in total factor productivity(TFP) following the disaster was considerable, and the economic recovery efficiency decreased significantly, resulting in a short-term economic recession. The TFP index returned to steady state following decreases of 33.7% and 15.2%, respectively, in the two years following the disaster.(4) The significant decrease in the post-disaster recovery efficiency was caused mainly by technological changes, and the renewal of the production system was the leading factor in determining the economic resilience following the disaster. With the decline in the scale of economic recovery following the earthquake, long-term economic recovery in the disaster-stricken areas depended mainly on pure technical efficiency, and the improvement in the latter was the driving force for maintaining the long-term growth of the post-disaster economy. Therefore, according to the local characteristics of natural environment and economic system, the disaster-stricken areas need to actively change and readjust their economic structures. At the same time, attention should be paid to updating the production system to enhance the level of technological progress and give full play to the scale effects of large-scale capital, new facilities, human resources, and other investment factors following the disaster so as to enhance the impact of economic resilience and recovery efficiency in response to the disaster. 相似文献
13.
基于内生经济增长视角,将海洋灾害损失与海洋科技进步内生化,与海洋劳动力和资本要素一并作为海洋经济生产驱动因素,测度海洋灾害对海洋经济增长的影响。研究表明,海洋灾害对当年海洋经济增长有负向影响,对灾后第2年海洋经济增长具有拉动作用,且长期呈现负作用。究其原因,海洋灾害主要通过破坏海洋经济生产基础设施、设备以及渔业资源等生产资本影响当期海洋经济增长;通过更新海洋科技和海洋经济生产资本存量拉动灾后海洋经济增长;长期来看,海洋灾害对海洋经济生产要素破坏作用大于对要素的更新作用。 相似文献
14.
Zhanjun He Jiannan Cai Zhong Xie Qingfeng Guan Chao Yang 《International journal of geographical information science》2020,34(6):1162-1187
ABSTRACTSpatiotemporal 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
15.
Yao Yao Xia Li Jinbao Zhang Zhaotang Liang Ke Mai 《International journal of geographical information science》2017,31(6):1220-1244
Fine-scale population distribution data at the building level play an essential role in numerous fields, for example urban planning and disaster prevention. The rapid technological development of remote sensing (RS) and geographical information system (GIS) in recent decades has benefited numerous population distribution mapping studies. However, most of these studies focused on global population and environmental changes; few considered fine-scale population mapping at the local scale, largely because of a lack of reliable data and models. As geospatial big data booms, Internet-collected volunteered geographic information (VGI) can now be used to solve this problem. This article establishes a novel framework to map urban population distributions at the building scale by integrating multisource geospatial big data, which is essential for the fine-scale mapping of population distributions. First, Baidu points-of-interest (POIs) and real-time Tencent user densities (RTUD) are analyzed by using a random forest algorithm to down-scale the street-level population distribution to the grid level. Then, we design an effective iterative building-population gravity model to map population distributions at the building level. Meanwhile, we introduce a densely inhabited index (DII), generated by the proposed gravity model, which can be used to estimate the degree of residential crowding. According to a comparison with official community-level census data and the results of previous population mapping methods, our method exhibits the best accuracy (Pearson R = .8615, RMSE = 663.3250, p < .0001). The produced fine-scale population map can offer a more thorough understanding of inner city population distributions, which can thus help policy makers optimize the allocation of resources. 相似文献
16.
Jizhe Xia Zhipeng Gui Kai Liu Zhenlong Li 《International journal of geographical information science》2014,28(7):1459-1481
A variety of Earth observation systems monitor the Earth and provide petabytes of geospatial data to decision-makers and scientists on a daily basis. However, few studies utilize spatiotemporal patterns to optimize the management of the Big Data. This article reports a new indexing mechanism with spatiotemporal patterns integrated to support Big Earth Observation (EO) metadata indexing for global user access. Specifically, the predefined multiple indices mechanism (PMIM) categorizes heterogeneous user queries based on spatiotemporal patterns, and multiple indices are predefined for various user categories. A new indexing structure, the Access Possibility R-tree (APR-tree), is proposed to build an R-tree-based index using spatiotemporal query patterns. The proposed indexing mechanism was compared with the classic R*-tree index in a number of scenarios. The experimental result shows that the proposed indexing mechanism generally outperforms a regular R*-tree and supports better operation of Global Earth Observation System of Systems (GEOSS) Clearinghouse. 相似文献
17.
Research on disaster response frequently uses volunteered geographic information (VGI), due to its capability to provide near real-time information during and after a disaster. It is much less commonly used in spatial planning related to disaster management. However, VGI appears to have considerable potential for use in spatial planning and offers some advantages over traditional methods. For example, VGI can capture residents' preferences in a much faster, more timely, and more comprehensive fashion than is possible with, for example, questionnaires and surveys. This research investigates the usefulness of VGI for planning flood evacuation shelters. Using Jakarta, Indonesia, as a case study, we use VGI to capture the locations of flood evacuation shelters based on residents' preferences during flood periods in 2013–2014 and 2014–2015 and compare these with the locations of official shelters. Floods frequently affect Jakarta and the city administration uses VGI in flood emergency responses. Moreover, Jakarta has been identified as having the largest number of active Twitter users among cities worldwide. Thus, Jakarta is an appropriate place to study the use of VGI for planning evacuation shelters. VGI generated by Twitter users was used to identify the shelter locations preferred by Jakarta residents, and more precisely the flood evacuees. Of 171,046 tweets using keywords relating to flood evacuation, the content of 306 tweets indicated that they had been sent from inside or near evacuation shelters. The spatial pattern showed that those tweets were sent from 215 locations, mostly located near flooded areas. The analysis further showed that 35.6% of these shelter locations preferred by residents intersected with the locations of official evacuation shelters. As a general conclusion, our study demonstrates the advantages of using VGI for spatial planning, which mainly relates to the ease of capturing community preferences over a large area. 相似文献
18.
南海及沿岸地带是亚太地区经济发展最有活力和潜力的地区之一,受全球变化和人类活动的影响,南海资源环境正发生快速变化,对社会、经济、生态和环境带来新压力。本文从地理空间信息角度,以海岸资源、海洋资源和珊瑚礁资源的地理研究为综述内容,梳理了该区域岸线遥感监测、油气资源储量及渔业资源渔获量的地理差异、珊瑚礁地貌遥感监测与珊瑚白化等相关研究进展,讨论了已有研究的成果及其薄弱方向,依据发展趋势探讨了未来研究工作的重点。综述发现,南海资源环境的地理空间研究中,主要成果表现在资源环境的大面积快速监测与地理分异性方面,但在资源分布的内在机制及资源开发的环境效应影响方面仍缺少足够的研究。未来可望获得突破的研究主要包括：区域时空多尺度特征及其效应,区域间自然和社会发展的分异和规律,多源数据融合的南海资源动态监测的精度与时效的提高,以及资源变化过程的海洋生态与环境综合效应研究等。 相似文献
19.
Investigating survivors' behaviour prior to, during and after a disaster provides emergency management agencies with greater understanding of the complexities which influence public response. This information can then be used to develop better community-based disaster risk-reduction strategies. In this paper, we review three post-tsunami disaster case studies: the Indian Ocean tsunami (IOT) on 26 December 2004, the Java tsunami on 17 July 2006 and the South Pacific tsunami on 29 September 2009. The 2004 IOT and 2006 Java tsunami surveys involved delayed-response post-disaster research using video interviewing. The 2009 South Pacific tsunami entailed rapid-response post-disaster research using questionnaire interviews. We highlight the major outcomes of each case study and, based on these, make recommendations for improving tsunami education programs in Australia. These include educating the public about tsunami risk, natural warning signs of tsunamis and regionally specific behavioural response. To help facilitate improvements to future post-disaster research, discussion on survey-related issues from each case study is provided. 相似文献
20.
Hansi Senaratne Amin Mobasheri Ahmed Loai Ali Cristina Capineri Mordechai Haklay 《International journal of geographical information science》2017,31(1):139-167
With the ubiquity of advanced web technologies and location-sensing hand held devices, citizens regardless of their knowledge or expertise, are able to produce spatial information. This phenomenon is known as volunteered geographic information (VGI). During the past decade VGI has been used as a data source supporting a wide range of services, such as environmental monitoring, events reporting, human movement analysis, disaster management, etc. However, these volunteer-contributed data also come with varying quality. Reasons for this are: data is produced by heterogeneous contributors, using various technologies and tools, having different level of details and precision, serving heterogeneous purposes, and a lack of gatekeepers. Crowd-sourcing, social, and geographic approaches have been proposed and later followed to develop appropriate methods to assess the quality measures and indicators of VGI. In this article, we review various quality measures and indicators for selected types of VGI and existing quality assessment methods. As an outcome, the article presents a classification of VGI with current methods utilized to assess the quality of selected types of VGI. Through these findings, we introduce data mining as an additional approach for quality handling in VGI. 相似文献