A geographical information system managing geotechnical data for Athens (Greece) and its use for automated seismic microzonation

This article presents a geographical information system (GIS) which manages geotechnical data obtained from detailed geotechnical surveys as well as from in situ observations in Athens, Greece. Thoroughly examined data from more than 2,000 exploratory boreholes and trial pits located in the wider area of Athens have been incorporated using a relational database system. From the analysis of these results, thematic maps are compiled to illustrate the distribution of engineering geological information (e.g. the depth of the “Athens schist” head). In addition, a methodology for an automated GIS-aided seismic microzonation study is outlined and is being employed taking into account the aforementioned geotechnical and engineering geological information, as well as existing seismological data to estimate the variability of seismic ground motion for the southern part of Athens.     

Spatial analysis of anthropogenic impact on karst geomorphology (Slovenia)

The objective of this contribution is analyzing, visualizing, interpreting and discussing the impacts of anthropogenic influences on karst geomorphology through various geomorphologically based environmental indicators. The primary data sources are digital terrain models (DTMs) as continuous surface data, supported by aerial photographs, satellite images, topographic maps and databases of natural and anthropogenic features. The sources are supplemented by written information about surface changes and in situ inspections. Spatial analyses as quantitative methods in combination with enhanced visualizations as qualitative methods performed in a geographical information system (GIS) on different data sets are introduced as an important methodology. This enables explaining many anthropogenic influences on the terrain surface (landform), which were not perceived before by classical surveying techniques and verifications.     

Application of geomorphologic knowledge for erosion hazard mapping

An erosion hazard map was elaborated using geomorphologic and lithological information; this was the base to characterize the erodibility of the territory. The aim of the proposed methodology is to define the areas where more detailed studies are necessary (e.g., to estimate rates of soil erosion, mitigation measurements, land use) to prevent future problems. Field work and remote sensing data (study of historical aerial photographs and satellite images) were used to understand the geomorphologic evolution and the current processes taking place in an area; this information was used to group the units according to its lithology, dynamic and slope inclination. The map was processed using the geographical information system and categorized in zones of very high, high, moderate, low and null fluvial erosion hazards. The map covers the Metropolitan Area of San Salvador, which is experiencing serious problems of mass wasting processes, collapse and settlements of foundations. Most affected areas belong to the Tierra Blanca Joven tephras which are unsaturated and cover most of the surface; nowadays, the urban projects and infrastructure resting in this material are suffering from extensive damage. The geotechnical information on the tephras shows a decrease in strength and collapsible behavior when saturated. Due to this, the use of Quickdraw tensiometers (suction) and TMS3 (soil moisture content) is proposed for monitoring. The methodology of erosion hazard mapping correlates well with mass wasting reported in the studied area, and for this reason, it could be a good way to protect the natural resources and improve the land use.     

Spatial data availability and its implications for sustainable development of the Brazilian Amazon

In the Amazonia region, general policy based on sustainable development must be adopted to counterbalance natural conservation and the needs of people. To discuss and monitor the regional development requires a significant variety of spatial data. However, making data available is not simple and various solutions usually are presented in non-standardized and non-interchangeable databases. This paper presents an overview of spatial data available for the Amazonia region, and initiatives of data dissemination systems, considering various geographical scales and data access. From this general perspective, we discuss some ideas about the importance of spatial data for sustainability and suggest interactive systems that could contribute to local development and environmental conservation. The limitation on the promotion of spatial information and data sharing in Amazonia is neither computational nor technological. Rather, it is a matter of informing those who generate the data about the benefits of knowledge as a public good and promoting collaborative work. Creating a convergent spatial consciousness about the territory, and bringing together every environmental player, is a step towards the discussion and planning of the sustainable development of the Amazonia.     

Digital national land information

The digital land data maintained in the Geographic Survey Institute are listed in Tab 1. They are computerized for the digital national land information to establish a geographical data bank of land information.The digital national land information contains many kinds of land data, which have been maintained mainly as maps, aerial photos and statistics, and is stored as magnetic tape.The smallest geographical unit is either the standard mesh, geodetic coordinate or dots, according to accuracy of the original data.The digital national land information can be used in the various fields of geographical researches and in national or local land planning.In this paper, as an example of application, the housing land selection method is introduced, using the natural land data and the land use data.     

A Blocking Markov Chain Monte Carlo Method for Inverse Stochastic Hydrogeological Modeling

An adequate representation of the detailed spatial variation of subsurface parameters for underground flow and mass transport simulation entails heterogeneous models. Uncertainty characterization generally calls for a Monte Carlo analysis of many equally likely realizations that honor both direct information (e.g., conductivity data) and information about the state of the system (e.g., piezometric head or concentration data). Thus, the problems faced is how to generate multiple realizations conditioned to parameter data, and inverse-conditioned to dependent state data. We propose using Markov chain Monte Carlo approach (MCMC) with block updating and combined with upscaling to achieve this purpose. Our proposal presents an alternative block updating scheme that permits the application of MCMC to inverse stochastic simulation of heterogeneous fields and incorporates upscaling in a multi-grid approach to speed up the generation of the realizations. The main advantage of MCMC, compared to other methods capable of generating inverse-conditioned realizations (such as the self-calibrating or the pilot point methods), is that it does not require the solution of a complex optimization inverse problem, although it requires the solution of the direct problem many times.     

Scale matching of multiscale digital elevation model (DEM) data and the Weather Research and Forecasting (WRF) model: a case study of meteorological simulation in Hong Kong

It is becoming easier to combine geographical data and dynamic models to provide information for problem solving and geographical cognition. However, the scale dependencies of the data, model, and process can confuse the results. This study extends traditional scale research in static geographical patterns to dynamic processes and focuses on the combined scale effect of multiscale geographical data and dynamic models. The capacity for topographical expression under the combined scale effect was investigated by taking multiscale topographical data and meteorological processes in Hong Kong as a case study. A meteorological simulation of the combined scale effect was evaluated against data from Hong Kong Observatory stations. The experiments showed that (1) a digital elevation model (DEM) using 3 arc sec data with a 1 km resolution Weather Research and Forecasting (WRF) model gives better topographical expression and meteorological reproduction in Hong Kong; (2) a fine-scale model is sensitive to the resolution of the DEM data, whereas a coarse-scale model is less sensitive to it; (3) better topographical expression alone does not improve weather process simulation; and (4) uncertainty arising from a scale mismatch between the DEM data and the dynamic model may account for 38 % of the variance in certain meteorological variables (e.g., temperature). This case study gives a clear explanation of the significance and implementation of scale matching for multiscale geographical data and dynamic models.     

The relevance of flood hazards and impacts in Turkey: What can be learned from different disaster loss databases?

Turkey has been severely affected by many natural hazards, in particular earthquakes and floods. Especially over the last two decades, these natural hazards have caused enormous human and economic damage. Although there is a large body of literature on earthquake hazards and risks in Turkey, comparatively little is known about flood hazards and risks. Therefore, this study aims to investigate the severity of flooding in comparison with other natural hazards in Turkey and to analyse the flood patterns by providing an overview of the temporal and spatial distribution of flood losses. These will act as a metric for the societal and economic impacts of flood hazards in Turkey. For this purpose, Turkey Disaster Database (TABB) was used for the years 1960–2014. As input for more detailed event analyses, the most severe flood events in Turkey for the same time interval will also be retrieved. Sufficiency of the TABB database to achieve the main aim of the study in terms of data quality and accuracy was also discussed. The TABB database was analysed and reviewed through comparison, mainly with the Emergency Events Database (EM-DAT), the Global Active Archive of Large Flood Events—Dartmouth Flood Observatory database, news archives and the scientific literature, with a focus on listing the most severe flood event. The comparative review of these data sources reveals big mismatches in the flood data, i.e. the reported number of events, number of affected people and economic loss all differ dramatically. Owing to the fact that the TABB is the only disaster loss database for Turkey, it is important to explore the reasons for the mismatches between TABB and the other sources with regard to aspects of accuracy and data quality. Therefore, biases and fallacies in the TABB loss data are also discussed. The comparative TABB database analyses show that large mismatches between global and national databases can occur. Current global and national databases for monitoring losses from national hazards suffer from a number of limitations, which in turn could lead to misinterpretations of the loss data. Since loss data collection is gaining more and more attention, e.g. in the Sendai Framework for Disaster Risk Reduction 2015–2030, this study offers a framework for developing guidelines for the Turkey Disaster Database (TABB), implications on how to standardize national loss databases and implement across the other hazard events in Turkey.     

矿产预测基础数据库的数据检查

21世纪的矿产资源预测评价是在GIS平台下,通过建立地质、物探、化探、遥感等信息的空间数据库,并对各数据库进行空间分析和信息转换、提取,最终圈定综合异常的.这项工作的前提是具有高质量的空间数据库.要提高空间数据库的质量,确保入库数据的正确性和完备性是关键,因此数据检查是一个不可回避的难题.矿产预测评价基础空间数据库具有数据量庞大、数据结构复杂、数据类型多样等特点,因此,提出通过元数据技术检查和控制数据的完备性和时效性,通过数据字典技术确保数据的属性精度,借助质量规则控制数据的逻辑一致性和位置精度的数据检查策略,并运用到全国重要成矿区带的基础空间数据库数据检查中,取得了良好的效果.     

Multi-scale European Soil Information System (MEUSIS): a multi-scale method to derive soil indicators

The Multi-scale Soil Information System (MEUSIS) can be a suitable framework for building a nested system of soil data that could facilitate interoperability through a common coordinate reference system, a unique grid coding database, a set of detailed and standardized metadata, and an open exchangeable format. In the context of INSPIRE Directive, MEUSIS may be implemented as a system facilitating the update of existing soil information and accelerating the harmonization of various soil information systems. In environmental data like the soil one, it is common to generalize accurate data obtained at the field to coarser scales using either the pedotransfer rules or knowledge of experts or even some statistical solutions which combine single values of spatially distributed data. The most common statistical process for generalization is averaging the values within the study area. In this paper, we do not present a simple averaging of numerical values without any further processed information. The upscaling process is accompanied with significant statistical analysis in order to demonstrate the method suitability. The coarser resolution nested grids cells (10??? 10?km) represent broad regions where the calculated soil property (e.g., organic carbon) can be accurately upscaled. Multi-scaled approaches are urgently required to integrate different disciplines (such as Statistics) and provide a meta-model platform to improve current mechanistic modeling frameworks, request new collected data, and identify critical research questions. Past papers have described in detail the upscaling methodology while our present approach is to demonstrate an important application of this methodology accompanied with statistical evidence.     

Spatial data for landslide susceptibility, hazard, and vulnerability assessment: An overview

The aim of this paper is to discuss a number of issues related to the use of spatial information for landslide susceptibility, hazard, and vulnerability assessment. The paper centers around the types of spatial data needed for each of these components, and the methods for obtaining them. A number of concepts are illustrated using an extensive spatial data set for the city of Tegucigalpa in Honduras. The paper intends to supplement the information given in the “Guidelines for Landslide Susceptibility, Hazard and Risk Zoning for Land Use Planning” by the Joint ISSMGE, ISRM and IAEG Technical Committee on Landslides and Engineered Slopes (JTC-1). The last few decades have shown a very fast development in the application of digital tools such as Geographic Information Systems, Digital Image Processing, Digital Photogrammetry and Global Positioning Systems. Landslide inventory databases are becoming available to more countries and several are now also available through the internet. A comprehensive landslide inventory is a must in order to be able to quantify both landslide hazard and risk. With respect to the environmental factors used in landslide hazard assessment, there is a tendency to utilize those data layers that are easily obtainable from Digital Elevation Models and satellite imagery, whereas less emphasis is on those data layers that require detailed field investigations. A review is given of the trends in collecting spatial information on environmental factors with a focus on Digital Elevation Models, geology and soils, geomorphology, land use and elements at risk.     

Landslide investigations in Russia and the former USSR

The impact of natural hazards on mankind has increased dramatically over the past decades. Global urbanization processes and increasing spatial concentrations of exposed elements induce natural hazard risk at a uniquely high level. To mitigate affiliated perils requires detailed knowledge about elements at risk. Considering a high spatiotemporal variability of elements at risk, detailed information is costly in terms of both time and economic resources and therefore often incomplete, aggregated, or outdated. To alleviate these restrictions, the availability of very-high-resolution satellite images promotes accurate and detailed analysis of exposure over various spatial scales with large-area coverage. In the past, valuable approaches were proposed; however, the design of information extraction procedures with a high level of automatization remains challenging. In this paper, we uniquely combine remote sensing data and volunteered geographic information from the OpenStreetMap project (OSM) (i.e., freely accessible geospatial information compiled by volunteers) for a highly automated estimation of crucial exposure components (i.e., number of buildings and population) with a high level of spatial detail. To this purpose, we first obtain labeled training segments from the OSM data in conjunction with the satellite imagery. This allows for learning a supervised algorithmic model (i.e., rotation forest) in order to extract relevant thematic classes of land use/land cover (LULC) from the satellite imagery. Extracted information is jointly deployed with information from the OSM data to estimate the number of buildings with regression techniques (i.e., a multi-linear model from ordinary least-square optimization and a nonlinear support vector regression model are considered). Analogously, urban LULC information is used in conjunction with OSM data to spatially disaggregate population information. Experimental results were obtained for the city of Valparaíso in Chile. Thereby, we demonstrate the relevance of the approaches by estimating number of affected buildings and population referring to a historical tsunami event.

     

Spot Satellite Data For Exploration Of Fractured Aquifers In A Semi-Arid Area In Southeastern Botswana

In areas with little primary porosity and low bedrock hydraulic conductivity, hydrogeological properties are mainly determined by secondary factors, such as fracture zones and associated weathering. Fracture zones in areas with limited regolith cover are often detectable on satellite images as linear features originating mainly from pronounced vegatation anomalies, topographic effects or both. SPOT multispectral and panchromatic data of a 2000 km² semi-arid area in southeastern Botswana have, in this study, been merged and interpreted in an image processing system resulting in a detailed lineament map and a delineation of dry season vegetation. The lineament data have been analyzed in a geographical information system and correlation studies of borehole and geophysical data with satellite lineaments have been carried out. The study shows that a digital approach, using satellite data in combination with existing field data, can provide a time- and cost-effective tool for the identification and narrowing of target areas for groundwater exploration in semi-arid areas.     

Defining geographical mobility: Perspectives from higher education

Context is generally overlooked when selecting measures to define geographical mobility in mobility and migration research. This paper contributes to a discussion on the importance of context when defining geographical mobility and draws on examples from higher education in Sweden. Using binary logistic regression, statistical outcomes are compared when different measures of mobility to and mobility from higher education are employed. The measures produce different statistical outcomes, and these differences are illuminated when comparing results of common measures of mobility (e.g. crossing administrative boundaries or moving a certain distance) against two measures constructed specifically for Swedish higher education-related mobility. The results indicate that using municipality boundaries for measuring mobility in the Swedish higher education context is particularly inappropriate because the measure does not differentiate commuters from movers. This challenge surfaces because mobility must be determined in relation to the locations of students’ higher education institutions since administratively registered moves are unreliable in the educational context. These findings emphasize the importance of considering the geographical locations and characteristics of higher education institutions in addition to feasible commuting possibilities in research on higher education-related mobility. The two measures developed for the Swedish higher education context are identified as most appropriate because they center on the geographical distribution of higher education, and this distribution is perceived as having an important role in influencing mobility in this context. Consequently, this study accentuates the need for considering the geographical arrangement of resources (e.g. schools, hospitals) relevant to the context under investigation when determining measures to define mobility.     

GIS-based distributed technique for assessing economic loss from flood damage: pre-feasibility study for the Anyang Stream Basin in Korea

Large national budgets are required for flood damage reduction projects, making it critical to ensure that public money used therein be spent efficiently. Accordingly, reliable assessment of flood damage is a critical issue in analysis of the economic aspects of flood damage reduction projects. To this end, this study aims to provide a GIS (geographical information system)-based technique for distributed flood damage assessment. We consider two aspects of flood damage assessment from an engineering and economic perspective, i.e. flood inundation analysis and multi-dimensional flood damage analysis (MD-FDA). To perform this assessment, we used a GIS-based framework and data processing method to assess damages. The proposed methodology was applied to flood control channel projects for flood disaster prevention in the Anyang Stream Basin in Korea and presents detailed GIS data processing and assessment results. Findings from this study may contribute to the improvement of usability of MD-FDA and may provide research directions for integrating economic and engineering factors. This distributed technique will also assist in the decision-making process when evaluating the economic feasibility of flood damage reduction projects for structural and non-structural measures.     

地理信息技术的发展与应用

地理信息系统是国家信息资源的重要组成部分。地理信息技术经过20多年的飞速发展，已经渗透到社会各个方面，促使人们生产、生活方式发生深刻变化。我国地理信息系统(GIS)技术正在向信息化方向发展，并正在逐步成为面向21世纪的支柱产业一信息产业的重要组成部分。国际GIS技术的发展趋势，主要体现在两个方面，一是综合，二是分化。从空间信息处理的角度看，可将GIS的发展分为空间信息的管理、分析、模拟和调控四个阶段。GIS技术的应用表现在一是面向大型项目，二是面向公众。     

流域地理景观的GIS数据三维可视化

应用以"GIS"为核心的空间信息技术,是开展"数字流域"工程建设自然和最佳的选择。结合"清江流域水文水情与洪水演进仿真系统"的具体研制,分析流域地理数据特点及传统GIS在"数字流域"建设中的优缺点,在应用传统GIS二维方式展示形式管理和预处理先期各类基础流域地理空间数据及其相应属性数据的基础上,为满足仿真系统系列三维可视化要求,建立面向流域空间实体对象的数据模型,定义流域地理空间对象数据结构,将流域地理常规的GIS数据以三维形式展示,在实际的系统开发过程中,取得较好的三维可视化效果,并可满足"数字清江"建设各阶段综合处理、分析、评价、决策以及可视化等方面的需求。     

Geographical location in the information age: from destiny to opportunity?

This article argues for a possibly new significance of geographical location in the information age, a significance amounting to more than mere spatial anchoring, on the one hand, and to less and different than absolute destiny, on the other. Hence, we show a possible change in the significance of geographical location from destiny in the industrial age to potential opportunity in the information age, a transition which applies to geographical units (i.e. cities, regions) and to individuals. First we discuss geographical location as destiny in the industrial age for both geographical entities and individuals. Second, we highlight a transitional period spanning through the 1970s and 1980s during which geographical location lost much of its absolute nature, becoming more of an anchor. Third, we present a conceptual framework for geographical location possibly turning into opportunity in the information age, again for both geographical units and individuals. We demonstrate that this potential opportunity has only partially materialized by individuals in the international use of online shopping, showing that their adoption is wider in North America, and differentiated in Europe. We further demonstrate a partial dissemination of opportunities for cities and regions by focusing on FDI. Finally, in the fourth and concluding section, we briefly discuss pertaining policy issues for the enhancement of locational opportunities.     

GIS-based weights-of-evidence modelling of rainfall-induced landslides in small catchments for landslide susceptibility mapping

Landslide susceptibility mapping is a vital tool for disaster management and planning development activities in mountainous terrains of tropical and subtropical environments. In this paper, the weights-of-evidence modelling was applied, within a geographical information system (GIS), to derive landslide susceptibility map of two small catchments of Shikoku, Japan. The objective of this paper is to evaluate the importance of weights-of-evidence modelling in the generation of landslide susceptibility maps in relatively small catchments having an area less than 4 sq km. For the study area in Moriyuki and Monnyu catchments, northeast Shikoku Island in west Japan, a data set was generated at scale 1:5,000. Relevant thematic maps representing various factors (e.g. slope, aspect, relief, flow accumulation, soil depth, soil type, land use and distance to road) that are related to landslide activity were generated using field data and GIS techniques. Both catchments have homogeneous geology and only consist of Cretaceous granitic rock. Thus, bedrock geology was not considered in data layering during GIS analysis. Success rates were also estimated to evaluate the accuracy of landslide susceptibility maps and the weights-of-evidence modelling was found useful in landslide susceptibility mapping of small catchments.