Digital Earth from vision to practice: making sense of citizen-generated content

Abstract

The vision of Digital Earth (DE) put recently forward under the auspices of the International Society for DE extends the paradigm of spatial data infrastructures by advocating an interactive and dynamic framework based on near-to-real time information from sensors and citizens. This paper contributes to developing that vision and reports the results of a two-year research project exploring the extent to which it is possible to extract information useful for policy and science from the large volumes of messages and photos being posted daily through social networks. Given the noted concerns about the quality of such data in relation to that provided by authoritative sources, the research has developed a semi-automatic workflow to assess the fitness for purpose of data extracted from Twitter and Flickr, and compared them to that coming from official sources, using forest fires as a case study. The findings indicate that we were able to detect accurately six of eight major fires in France in the summer of 2011, with another four detected by the social networks but not reported by our official source, the European Forest Fire Information Service. These findings and the lessons learned in handling the very large volumes of unstructured data in multiple languages discussed in this study provide useful insights into the value of social network data for policy and science, and contribute to advancing the vision of DE.     

Hexagonal connectivity maps for Digital Earth

Geospatial data are gathered through a variety of different methods. The integration and handling of such datasets within a Digital Earth framework are very important in many aspects of science and engineering. One means of addressing these tasks is to use a Discrete Global Grid System and map points of the Earth's surface to cells. An indexing mechanism is needed to access the data and handle data queries within these cells. In this paper, we present a general hierarchical indexing mechanism for hexagonal cells resulting from the refinement of triangular spherical polyhedra representing the Earth. In this work, we establish a 2D hexagonal coordinate system and diamond-based hierarchies for hexagonal cells that enables efficient determination of hierarchical relationships for various hexagonal refinements and demonstrate its usefulness in Digital Earth frameworks.     

联合热红外与微波的作物辐射方向性模型研究

热红外遥感提供地表表层辐射信息为主,被动微波遥感可更好地提供植被和土壤背景垂直结构的辐射信息。结合热红外与被动微波遥感的优势协同反演植被和土壤组分温度是提高组分温度反演精度的一种思路。本文在对热红外辐射传输模型和微波辐射模型进行比较的基础上,构建均匀作物的统一场景,将统一场景的参数分为直接参数和间接参数。基于统一场景,修改微波辐射模型的场景结构及叶倾角分布,并增加组分温度参数以计算辐射亮温,最终构建热红外与微波辐射联合模拟模型(UEasmmes模型)。针对均匀玉米作物,利用UEasmmes模型进行联合模拟,分析了组分温度、组分发射率、叶面积指数LAI及叶倾角分布LAD对热红外与微波的方向性亮温DBT的敏感性响应差异。分析结果表明:协同热红外与被动微波遥感反演植被和土壤组分温度是可行的,但对于如何克服组分发射率、LAI及LAD对植被有效发射率的影响而导致的微波辐射亮温变化以及实现热红外表皮温度与微波等效温度之间的转化仍是需要深入研究和探讨的问题。     

不规则三角网（TIN）VB 6.0编程实现

系统阐述了基于等高线数据建立高质量DEM的理论和方法,分析比较了国内外建立DEM的方法。采用VB 6.0环境下实现了等高线数据构建不规则三角网（TIN）。在DEM的研究中,DEM精度关系到DEM的生产者与使用者,人们总是希望DEM能够完全准确、客观地反映地球表面的起伏变化。     

云南地震数字遥测台网子台地动噪声分析

介绍了云南数字遥测台网的基本情况，阐述了地动噪声有效值和功率谱的计算方法。对选取的资料进行预处理后，计算分析了云南数字遥测台网全部子台的地动噪声水平，按地动噪声水平对子台进行了分类。指出了地动噪声分析对台网建设的作用。     

新疆历史地震前兆模拟资料转入数字化平台的实现

近年来随着数字化技术的不断发展、成熟和稳定,我国的地震前兆观测技术也逐步实现由模拟观测向数字观测转变,地震前兆数字化观测技术日趋成热、稳定,地震前兆数字化观测普及程度越来越高,产出的数字化观测资料已得到越来越广泛的应用。通过介绍新疆数字地震前兆台网中心模拟资料和数字化资料的管理,分析了历史模拟数据转入数字化平台的实现方法,阐述了地震前兆资料进入数字化统一平台的实际应用。     

基于Daubechies小波分析的南京数字化钻孔形变震前变化特征研究

应用小波分析理论及其时频分析方法,阐述了高低频信息的识别和小波基的选取,并对南京地区2006—2012年数字化应变观测整点值资料进行了小波多分辨率分析。结果表明,六合台体应变小波分解7—9阶是频率最低的部分,异常信号的周期在24—30天左右,持续时间在1—2个月之间,具有明显的短期、临震异常特征;江宁台四分量应变的整点观测值的第9阶小波分解表明,在发生2次地震前,四分量中至少有3个方向的分量出现了明显的异常情况,这种异常周期通常在20—30天左右,其与高淳台的异常周期时间相当,它可能是地震的前兆信号。     

A multiscale adjoint method to compute sensitivity coefficients for flow in heterogeneous porous media

A multiscale adjoint (MSADJ) method is developed to compute high-resolution sensitivity coefficients for subsurface flow in large-scale heterogeneous geologic formations. In this method, the original fine-scale problem is partitioned into a set of coupled subgrid problems, such that the global adjoint problem can be efficiently solved on a coarse grid. Then, the coarse-scale sensitivities are interpolated to the local fine grid by reconstructing the local variability of the model parameters with the aid of solving embedded adjoint subproblems. The approach employs the multiscale finite-volume (MSFV) formulation to accurately and efficiently solve the highly detailed flow problem. The MSFV method couples a global coarse-scale solution with local fine-scale reconstruction operators, hence yielding model responses that are quite accurate at both scales. The MSADJ method is equally efficient in computing the gradient of the objective function with respect to model parameters. Several examples demonstrate that the approach is accurate and computationally efficient. The accuracy of our multiscale method for inverse problems is twofold: the sensitivity coefficients computed by this approach are more accurate than the traditional finite-difference-based numerical method for computing derivatives, and the calibrated models after history matching honor the available dynamic data on the fine scale. In other words, the multiscale based adjoint scheme can be used to history match fine-scale models quite effectively.     

模型偏差与定位震源深度

简要分析了定位模型偏差对震源深度测定的影响,提出了有利于抑制模型偏差作用,提高测震定位精度的主要途径。     

矿产预测评价中不确定性传播模型

矿产预测与评价是是由多个阶段组成的系统工程,包括数据收集,资料整理,信息提取,信息综合,预测评价、成果表达等.由于地质的复杂性和变化多样性及人类认识的不完备性致使矿产预测与评价的每一个阶段都包含了一定的不确定性,且前一阶段的不确定性会传播给后一阶段,从而导致相当数量的不确定性积累与传播.本文简要分析了矿产预测与评价不确定性的主要来源,给出矿产预测与评价的不确定性表达模型,研究了矿产预测与评价不确定性的合成算法和传播算法.