大数据背景下地质云的构建与应用

地质学属于数据密集型科学,并与地球科学面临的问题息息相关。已经收集的和将要收集的大量数字国土相关数据,由于科学研究的需要,正在不断加以检验和扩充。大数据时代背景下,中国国土资源数字化、信息化的战略行动具有深远意义,大数据的相关技术应用为实现地质工作的现代化和信息化提供了有效的支撑。重点介绍大数据背景下的“地质云”构建理念与方法,以及大数据在地学领域的应用。大数据为非结构化、半结构化的地质数据带来了新的处理方法与理念。地质云的构建旨在探索以需求带动的地质核心数据的应用,挖掘非结构化数据的新数据信息,以支撑国土资源管理决策。     

最近十年来中国地理科学的进展

最近十年来中国地理科学的最重要进展有:自然地理学与人文地理学的平衡发展,人口、资源、环境的研究,遥感的应用与地理信息系统的建立,自然地理定位观测,青藏高原隆起对自然环境的影响,城市与城市规划,中国历史地理研究等。最近,并已开始研究气候变化与海平面上升对中国的影响,使我国地理科学研究紧紧跟上世界发展的步伐。     

Bayesian data fusion in a spatial prediction context: a general formulation

In spite of the exponential growth in the amount of data that one may expect to provide greater modeling and predictions opportunities, the number and diversity of sources over which this information is fragmented is growing at an even faster rate. As a consequence, there is real need for methods that aim at reconciling them inside an epistemically sound theoretical framework. In a statistical spatial prediction framework, classical methods are based on a multivariate approach of the problem, at the price of strong modeling hypotheses. Though new avenues have been recently opened by focusing on the integration of uncertain data sources, to the best of our knowledges there have been no systematic attemps to explicitly account for information redundancy through a data fusion procedure. Starting from the simple concept of measurement errors, this paper proposes an approach for integrating multiple information processing as a part of the prediction process itself through a Bayesian approach. A general formulation is first proposed for deriving the prediction distribution of a continuous variable of interest at unsampled locations using on more or less uncertain (soft) information at neighboring locations. The case of multiple information is then considered, with a Bayesian solution to the problem of fusing multiple information that are provided as separate conditional probability distributions. Well-known methods and results are derived as limit cases. The convenient hypothesis of conditional independence is discussed by the light of information theory and maximum entropy principle, and a methodology is suggested for the optimal selection of the most informative subset of information, if needed. Based on a synthetic case study, an application of the methodology is presented and discussed.     

地学知识可视化概念特征与研究进展

地学知识可视化是将知识可视化研究的理论、技术、方法引入地学研究领域,形成一个新的研究方向。通过分析地学知识可视化国内外研究现状,在总结其研究特点的基础上,对地学知识可视化的定义进行阐述,讨论其概念特征、理论基础以及表达方法,并对其应用研究现状与发展趋势进行概括总结。     

信息化对区域经济发展的组织作用

在科学认知信息化多重形态(包括要素形态、技术形态、设施形态、经济形态和运动形态)特征的基础上,分别阐述其对区域经济发展的组织作用。信息资源通过改变原有生产要素的结构对区域经济发生作用;信息技术不仅可推动传统产业的升级换代,还将企业和贸易扩展到网络空间;信息基础设施拓展了信息通达性,促进了主体间的信息交流,并使原有的区域空间结构发生了微调下的整体增强变化;信息产业在直接促进区域经济增长的同时,还通过前后向联系带动其他产业发展;信息流对物流、人流、资金流和技术流具有组织作用,有助于实现流动的组织和组织的流动。     

Predicting the visualization intensity for interactive spatio-temporal visual analytics: a data-driven view-dependent approach

The continually increasing size of geospatial data sets poses a computational challenge when conducting interactive visual analytics using conventional desktop-based visualization tools. In recent decades, improvements in parallel visualization using state-of-the-art computing techniques have significantly enhanced our capacity to analyse massive geospatial data sets. However, only a few strategies have been developed to maximize the utilization of parallel computing resources to support interactive visualization. In particular, an efficient visualization intensity prediction component is lacking from most existing parallel visualization frameworks. In this study, we propose a data-driven view-dependent visualization intensity prediction method, which can dynamically predict the visualization intensity based on the distribution patterns of spatio-temporal data. The predicted results are used to schedule the allocation of visualization tasks. We integrated this strategy with a parallel visualization system deployed in a compute unified device architecture (CUDA)-enabled graphical processing units (GPUs) cloud. To evaluate the flexibility of this strategy, we performed experiments using dust storm data sets produced from a regional climate model. The results of the experiments showed that the proposed method yields stable and accurate prediction results with acceptable computational overheads under different types of interactive visualization operations. The results also showed that our strategy improves the overall visualization efficiency by incorporating intensity-based scheduling.     

教育公共服务设施可达性评价与规划——以江苏省仪征市高级中学为例

学校是公共服务设施的重要组成部分,其空间分布以及可达性的优劣,直接影响到受教育者接受教育的机会和方便程度。把可达性的概念引入到教育公共设施的规划中,利用Mapinfo公司的控件MapX和Borland公司的可视化编程语言Delphi,开发了基于时间最短的路径选择信息系统,生成了学校可达性的等时线图和学校服务范围图,通过该系统可直观地看到区域内任何一点到达学校所花费的最短时间以及通过的路径。以江苏省仪征市的高级中学为例,运用该系统对高级中学的可达性进行了评价,并提出了其规划方案。     

地理信息系统技术在区域城镇发展用地评价中的应用——以海南省为例

区域城镇发展用地评价是区域经济开发的先行步骤。作者利用地理信息系统的技术,建立地形评价模型、基础设施辐射范围扩散模型、分区多幅图覆盖分析模型等一整套模型,使评价工作较以往更为科学、系统,且省时省力。本文研究了海南省城镇发展用地条件。     

基于互联网信息的城市商业游憩网点空间竞争域划分研究

提出了一种基于互联网信息的空间竞争域划分方法。在Voronoi图的模型中尝试以网络平台数据作加权因子,使空间竞争域体现互联网中的消费者偏好差异,通过对加权Voronoi图的类型划分和地理学解释,描述竞争环境的空间特征。以北京市健身俱乐部为例,选择大众点评网、爱帮等网络平台信息作为权重因子,构建样本网点的传统Voronoi、互联网信息加权Voronoi计算模型并对比边界线、面积等空间特征分析的结果表明:互联网信息对城市商业游憩网点的空间竞争力产生着不同的影响强度,对Voronoi图空间特征的分类和地理解释可以指示商业网点跨越距离阻碍的消费吸引力及竞争差异,弥补传统加权方法未考虑消费者偏好和购物习惯而对竞争域划分表达不足的缺点。     

The consequences of land-cover changes on soil erosion distribution in Slovakia

Soil erosion is a complex process determined by mutual interaction of numerous factors. The aim of erosion research at regional scales is a general evaluation of the landscape susceptibility to soil erosion by water, taking into account the main factors influencing this process. One of the key factors influencing the susceptibility of a region to soil erosion is land cover. Natural as well as human-induced changes of landscape may result in both the diminishment and acceleration of soil erosion. Recent studies of land-cover changes indicate that during the last decade more than 4.11% of Slovak territory has changed. The objective of this study is to assess the influence of land-cover and crop rotation changes over the 1990–2000 period on the intensity and spatial pattern of soil erosion in Slovakia. The assessment is based on principles defined in the Universal Soil Loss Equation (USLE) modified for application at regional scale and the use of the CORINE land cover (CLC) databases for 1990 and 2000. The C factor for arable land has been refined using statistical data on the mean crop rotation and the acreage of particular agricultural crops in the districts of Slovakia. The L factor has been calculated using sample areas with parcels identified by LANDSAT TM data. The results indicate that the land-cover and crop rotation changes had a significant influence on soil erosion pattern predominately in the hilly and mountainous parts of Slovakia. The pattern of soil erosion changes exhibits high spatial variation with overall slightly decreased soil erosion risks. These changes are associated with ongoing land ownership changes, changing structure of crops, deforestation and afforestation.