Combining machine-learning topic models and spatiotemporal analysis of social media data for disaster footprint and damage assessment

Current disaster management procedures to cope with human and economic losses and to manage a disaster’s aftermath suffer from a number of shortcomings like high temporal lags or limited temporal and spatial resolution. This paper presents an approach to analyze social media posts to assess the footprint of and the damage caused by natural disasters through combining machine-learning techniques (Latent Dirichlet Allocation) for semantic information extraction with spatial and temporal analysis (local spatial autocorrelation) for hot spot detection. Our results demonstrate that earthquake footprints can be reliably and accurately identified in our use case. More, a number of relevant semantic topics can be automatically identified without a priori knowledge, revealing clearly differing temporal and spatial signatures. Furthermore, we are able to generate a damage map that indicates where significant losses have occurred. The validation of our results using statistical measures, complemented by the official earthquake footprint by US Geological Survey and the results of the HAZUS loss model, shows that our approach produces valid and reliable outputs. Thus, our approach may improve current disaster management procedures through generating a new and unseen information layer in near real time.     

SinoGrids: a practice for open urban data in China

ABSTRACT

In the past decade, an explosion of data has taken place in Chinese cities due to widespread use of mobile Internet devices, Web 2.0 applications, and the development of the “Wired City.” With advances in data storage and high-performance computing, big/open urban data have opened up important avenues for urban studies, planning practice, and commercial consultancy. Urban researchers and planners are eager to make use of these abundant, sophisticated, and dynamic data to deepen their understanding on urban form and functions. However, in practice, access to such urban data is limited in China due to institutional constraints on data distribution and data holders’ hesitation to share data. And this hampers urban analytics. To draw reliable conclusions about the workings of complex urban systems, efficient and effective interoperation of multisource urban datasets is needed. Also, dealing with the heterogeneity between datasets is an equally critical challenge, especially for urban planners and government officers. They would derive value from data analytics, but have little data processing experience. To address these issues, we initiated SinoGrids (Plan Xu Xiake), a crowdsourcing platform that standardizes (or “downscales”) microscale urban data in China to facilitate its sharing and interoperation. To assess the performance evaluation of SinoGrids, we propose field-testing with actual urban data and their potential users. Digital desert, a son project of SinoGrids is also included.     

基于GIS的城市内涝灾害分析模型研究

根据气象、水文、水利等专业知识,利用GIS的空间分析技术,结合城市地理数据库和数学计算模型及城市暴雨强度经验公式,建立城市内涝灾害分析模型。该模型是城市内涝积水计算和模拟的基础,能够根据城市降雨分布情况,模拟和预测城市的内涝灾害有关特征数据,如内涝积水的空间分布、深度分布、淹没面积和淹没时间等,模拟结果可为防灾减灾部门制定防灾减灾措施提供依据。     

基于格网GIS的地质灾害地形因子危险评估方法

针对地质灾害的复杂性和不确定性,利用格网GIS技术和数学算法对地质灾害的地形危险进行评估研究。以新源县为实验区,创建500m×500m的格网覆盖研究区,选取高程、坡度、岩性、断层等地质地貌条件作为评价因子,运用GIS统计分析、叠置分析等功能将指标格网化和标准化,最后运用熵值法确定权重,进行综合评估。实验结果表明,新源县较高危险和高危险区主要集中在北部、中部及西南部的山区,共包含90.17%的灾害点,表明将格网GIS技术应用到地质灾害危险评估具有一定的实践意义。     

Quantifying the building stock from optical high-resolution satellite imagery for assessing disaster risk

This study uses high-resolution (HR) satellite imagery to quantify the stock of buildings, referred herein as building stock. The risk assessment requires information on the natural hazards and on the element at risk, that is the building stock in this article. This study combines (1) texture-based image processing to map built-up areas, (2) statistical sampling that allows locating the building samples and (3) photo-interpretation to encoding building footprints. Statistical inference is then used to quantify the building stock per class of building size. Legaspi in the Philippines is used as a case study. The results show that texture-based computer algorithms provide accurate area estimations of the built-up, that the detail of HR imagery allows the mapping of single buildings using photo-interpretation, and that a systematic sampling approach that uses building encoding and built-up maps can be used to quantify the building stock.     

Evaluating urban public facilities of Shenzhen by application of open source data

Abstract

This article applies open source data of public facilities through data mining, not only to evaluate the public facilities from an objective dimension, but also to reflect the sensory opinions of the group factually, eventually realizing the evaluation measurement of urban public facilities. The research takes Shenzhen city as an empirical case and chooses typical public facilities to mine data, resolve address and weight to explore the application of public facilities evaluation under dimension reduction of open source data. The empirical study consists of three parts. First, as the objective evaluation, we estimate the density distribution and per capita of public facility through data mining and address resolution. Second, as the subjective evaluation, we carry on the location analysis to high-score public facility through attention and satisfaction data of Internet evaluation. Finally, as mentioned above, we calculate the weight of objective and subjective evaluation of public facility, eventually formatting the comprehensive evaluation of public facilities.     

In-depth examination of spatiotemporal figures in open reproducible research

ABSTRACT

Figures such as maps and time series are essential means to visualize spatiotemporal results in scientific papers. Being able to recompute them using the underlying source code and data is thus a core aspect in reproducible research. However, many scientists see the preparation of code and data for publication as an additional burden without immediate benefits. In this work, we investigate advantages and new capabilities of reproducible research papers. Our key contributions are (i) the extension of a geoscientist’s workflow while examining papers including reproducible figures such as maps and (ii) the prototypical implementation of the workflow as a web application. The workflow is based on current practices of geoscientists and encapsulates benefits of reproducible figures. It is informed by ideas and needs identified by geoscientists in a survey, interviews, and a focus group. Based on their statements, we first extend the traditional workflow steps Discovery and Inspection by additional capabilities and propose two new steps: Manipulation of the content of a spatiotemporal figure and Substitution of the underlying code and data. The extended workflow and its implementation might facilitate in-depth examination and reusability of geoscientific results.     

地灾监测的大数据信息平台研究及应用

重点对地灾监测方面的方案研究进行了阐述,在构建大数据信息平台的设计方案时,以实现高度自动化的全方位监测功能为导向,依托导航卫星数据接收机和多源传感器,集成构建大数据信息平台的系统解决方案,主要包括扼流圈卫星天线、GNSS数据接收机、MEMS传感器、环境测量单元、防雷区域单元等功能元件的组成、多传感器的系统集成,以及全方位监测的功能实现。按照地灾监测大数据信息平台建设、构建大数据平台关键技术突破及检测数据解算软件功能实现的顺序,完成了GNSS实时监测预警应用网络系统HCmonitor的研发。综合应用多种手段实现地灾监测的功能升级,为解决重大灾害预警提供了新的思路和解决方案,该项成果在甘肃舟曲的灾后重建工程得到应用与推广。     

国产高分辨率卫星数据在黄河防凌监测中应用

自2002～2003年度首次启用遥感技术监测黄河凌情以来,到目前已连续进行了10个年度.10个年度的生产实践表明:国产高分辨率卫星遥感数据能够有效跟踪黄河凌情的发展过程,实现黄河凌情的日动态监测、重点时段的精细监测和突发凌汛灾害时的实时监测.黄河凌情尤其在封开河阶段,日变化非常显著,中巴资源卫星作为国产高分辨率可见光民用遥感卫星的代表,以其大视场、高空间、高时间分辨率的特点,动态监测凌情,基本做到每天实现一次全覆盖监测的能力,配合其他如中国遥感卫星等高分辨率可见光、雷达数据,初步实现了凌情发展预估、开河前的河道槽蓄水量计算、封开河期间冰凌险情监测以及发生凌汛灾害时灾情信息采集与评估,为黄河防凌     

三峡库区地质灾害数据管理平台元数据编辑器的设计与实现

本文探讨了建立空间元数据管理系统所涉及的一些标准和技术,重点介绍了ArcCatalog中的元数据管理和XML技术及其在元数据系统中的作用.针对ArcCatalog空间数据管理的特点及开放的扩展机制,深入讨论了用户定制的元数据编辑器开发的步骤、主要技术等,并设计开发出一种基于XML的空间数据元数据编辑器,为地球空间元数据...     

基于多分辨率分析的LiDAR数据处理与可视化

基于多分辨率分析的数据滤波算法对于地形变化单一但地物和地形区别明显的场景,地形多变但连续且地物和地形区别明显的场景具有非常优越的滤波效果.研究基于多分辨率分析的数据滤波算法的基本原理,在Visual C++6.0平台上编程实现该算法,建立LiDAR数据处理与可视化系统,详细介绍各功能模块的实现方法和功能,实现由LiDA...     

基于高光谱数据的壁画底稿信息提取

壁画底稿有助于探测壁画艺术的历史信息,具有重要的研究价值,本文设计了半自动提取壁画底稿信息的“三步法”:针对高光谱数据量大、相邻波段相关性高的特点,利用主成分分析实现原始数据的降维;选出含底稿信息量大的特征波段;并利用最大似然分类法实现基于特征波段合成影像的壁画底稿信息提取.结果表明,该方法能够减少数据处理量,提高分类效率与分类精度,明显恢复壁画的底稿轮廓,为以后的文化遗产保护工作提供一个可行的方案.     

Characterizing wetland dynamics: a post-classification change detection analysis of the East Kolkata Wetlands using open source satellite data

The East Kolkata Wetlands is a unique resource recovery system. The Ramsar Convention recognized it as a ‘Wetland of International Importance’ in August 2002. However, the long-term resource exploitation and land use changes in the dynamic ecosystem have resulted in non-linear environmental responses. This is an attempt using open source remote sensing datasets to capture the spatio-temporal transformation of the wetland resulting from various anthropogenic activities. Landsat MSS and TM imageries of 1973, 1980, 1989, 2001 and 2010 were classified using Maximum Likelihood Classifier to monitor the wetland change; however, to study wetland dynamics, the post-classification wetland change detection maps have been generated for two temporal phases, i.e. 1973–1989 and 1989–2010. This study finds that the area under wetlands has reduced comprehensively in the past 40 years due to the conversion of wetlands into various other uses such as urban expansion of the Kolkata metropolitan city.     

面向地理信息大数据的时空事件关系可视化分析框架

不同类型的地理信息大数据蕴含了丰富的时空关系,反映个体或者群体时空事件之间的变化模式,在资源、环境、交通等领域的智慧应用中起到关键性作用。然而,地理信息大数据拥有的多尺度和多语义特性,在挖掘地理信息大数据的时空关系时会存在许多困难。如何有效地构建多尺度多语义时空关系,并直观地表达这些时空关系是一个重大挑战。本文设计了一种时空事件关系可视化分析框架,通过定义事件间时空关系的描述,设计了一种多视图协同的可视化分析方法,结合时空关系的可视化协同交互,实现地理信息大数据时空事件可视分析。基于时空轨迹数据,通过试验说明该方法可以探寻时空事件及背景间的时空关系,实现时空事件的交互可视分析。     

GPS工程测量网数据处理与质量评估方法研究

探讨直接利用平差结果分析GPS网起算点的兼容性问题,达到剔除含有粗差已知点的目的.针对短基线(10～15 km以下)工程测量网,总结GPS工程测量网数据处理与质量评估方法.对某铁路工程测量控制网的观测资料进行数据处理与质量评估试验,结果表明:平面点位精度在x方向上优于0.75 cm,y方向上优于0.70 cm,点位精度...     

GPS监测网数据质量分析

为保证GPS监测网络满足监测精度要求,本文提出了GPS外业数据采集,基线解算应采取的措施及数据处理方法,并对两期观测数据及处理结果进行质量分析,以保证变形分析的可靠性。     

基于哨兵数据的云南地表形变监测

云南省作为我国西南地区与西藏相连的省份,其地势由西北向东南逐渐降低且山峦众多,山区面积占全省面积的88％.除此之外,云南省还位于印度洋板块和亚欧板块交界处附近,其地震带众多,地质运动频繁,经常出现地震、滑坡、泥石流等地质灾害.因此,本文选取覆盖地势较高的云南西北部地区的哨兵数据,利用SBAS-InSAR技术进行数据处理...     

用时间序列分析法进行建筑物沉降观测数据处理的研究

本文将时间序列分析法用于建筑物沉降观测数据处理,给出了用此法进行沉降观测数据处理时模型阶数确定的统计检验方法、模型参数估计以及预报分析的方法,以某建筑物沉降观测第30期的测量成果为例说明应用此法的全过程,并对计算结果进行了分析比较。     

多源遥感数据在土地利用图件更新中的应用--以怀柔区为例

本文阐述了以怀柔区为试验区,从遥感数据的应用着手,选择SPOT-5、QUICK BIRD、航空摄影像片三种遥感数据源对该区7幅土地利用基础图件作了更新,从而分析了三种数据源在土地利用基础图件更新中不同的适宜程度及其性价比,为土地部门选择合适的遥感数据源进行更新调查提供技术依据。     

Maize drought disaster risk assessment of China based on EPIC model

Abstract

Digital Agriculture is one of the important applications of Digital Earth. As the global climate changes and food security becomes an increasingly important issue, agriculture drought comes to the focus of attention. China is a typical monsoon climate country as well as an agricultural country with the world's largest population. The East Asian monsoon has had a tremendous impact upon agricultural production. Therefore, a maize drought disaster risk assessment, in line with the requirements of sustainable development of agriculture, is important for ensuring drought disaster reduction and food security. Meteorology, soil, land use, and agro-meteorological observation information of the research area were collected, and based on the concept framework of ‘hazard-inducing factors assessment (hazard)-vulnerability assessment of hazard-affected body (vulnerability curve)-risk assessment (risk),’ importing crop model EPIC (Erosion-Productivity Impact Calculator), using crop model simulation and digital mapping techniques, quantitative assessment of spatio-temporal distribution of maize drought in China was done. The results showed that: in terms of 2, 5, 10, and 20 year return periods, the overall maize drought risk decreased gradually from northwest to southeast in the maize planting areas. With the 20 year return period, high risk value regions (drought loss rate ≥0.5) concentrate in the irrigated maize region of Northwest china, ecotone between agriculture and animal husbandry in Northern China, Hetao Irrigation Area, and north-central area of North China Plain, accounting for 6.41% of the total maize area. These results can provide a scientific basis for the government's decision-making in risk management and drought disaster prevention in China.