Geographic Data Acquisition Research Articles

STRATEGY FOR EXTRACTION OF FOURSQUARE’S SOCIAL MEDIA GEOGRAPHIC INFORMATION THROUGH DATA MINING

Abstract This aim of this paper is the acquisition of geographic data from the Foursquare application, using data mining to perform exploratory and spatial analyses of the distribution of tourist attraction and their density distribution in Rio de Janeiro city. Thus, in accordance with the Extraction, Transformation, and Load methodology, three research algorithms were developed using a tree hierarchical structure to collect information for the categories of Museums, Monuments and Landmarks, Historic Sites, Scenic Lookouts, and Trails, in the foursquare database. Quantitative analysis was performed of check-ins per neighborhood of Rio de Janeiro city, and kernel density (hot spot) maps were generated The results presented in this paper show the need for the data filtering process - less than 50% of the mined data were used, and a large part of the density of the Museums, Historic Sites, and Monuments and Landmarks categories is in the center of the city; while the Scenic Lookouts and Trails categories predominate in the south zone. This kind of analysis was shown to be a tool to support the city's tourist management in relation to the spatial localization of these categories, the tourists’ evaluations of the places, and the frequency of the target public.

Multi-Criteria Analysis Framework for Potential Flood Prone Areas Mapping

A fundamental component of the European natural disaster management policy is the detection of potential flood-prone areas, which is directly connected to the European Directive (2007/60). This study presents a framework for mapping potential flooding areas incorporating geographic information systems (GIS), fuzzy logic and clustering techniques, and multi-criteria evaluation methods. Factors are divided in different groups which do not have the same level of trade off. These groups are related to geophysical, morphological, climatological/meteorological and hydrological characteristics of the basin as well as to anthropogenic land use. GIS and numerical simulation are used for geographic data acquisition and processing. The selected factor maps are considered in order to estimate the spatial distribution of the potential flood prone areas. Using these maps, the study area is classified into five categories of flood vulnerable areas. The Multi-Criteria Analysis (MCA) techniques consist of the crisp and fuzzy analytical hierarchy processes (AHP) and are enhanced with different standardization methods. The classification is based on different clustering techniques and it is applied in two approaches. In the first approach, all criteria are normalized before the MCA process and then, the clustering techniques are applied to derive the final flood prone area maps. In the second approach, the criteria are clustered before and after the MCA process for the potential flood prone area mapping. The methodology is demonstrated in Xerias River watershed, Thessaly region, Greece. Xerias River floodplain was repeatedly flooded in the last few years. These floods had major impacts on agricultural areas, transportation networks and infrastructure. Historical flood inundation data has been used for the validation of the methodology. Results show that multiple MCA techniques should be taken into account in initial low-cost detection surveys of flood-prone areas and/or in preliminary analysis of flood hazard mapping.

Statistical Analysis of the Massive Traffic Data Based on Cloud Platform

Currently, with the rapid development of various geographic data acquisition technologies, the data-intensive geographic calculation is becoming more and more important. The urban motor vehicles loaded with GPS, namely the transport vehicles, can real-timely collect a large number of urban traffic information. If these massive transportation vehicle data can be real-timely collected and analyzed, the real-time and accurate basic information will be provided for monitoring the large area of traffic status as well as the intelligent traffic management. Based on the requirements of the organization, the processing, the statistics and the analysis of the massive urban traffic data, the new framework of the massive data-intensive calculation under the environment of cloud platform has been proposed through employing Bigtable, Mapreduce and other technologies.

GeoDADIS: A framework for the development of geographic data acquisition and dissemination servers

The homogeneous access to sensor data in data monitoring and analysis applications is gaining much interest nowadays. To tackle this problem from an application independent perspective, the design and implementation of a framework called GeoDADIS for the development of data acquisition and dissemination servers is discussed in the present paper. Those servers are of common use in monitoring applications as they perform as gateways between decision support and data visualization technologies used in application developments and the heterogeneous collection of protocols and interfaces available in the industrial area for sensor data access. To achieve its objective, the architecture of GeoDADIS consists of: (i) a bottommost data acquisition layer that communicates with sensors, (ii) a middle kernel layer that provides general purpose functionality related to data management and system control and (iii) a topmost external interaction layer that enables the access from applications. The frameworks design does extensive use of the adapter (wrapper) design pattern to ease the incorporation of new data acquisition channels at the data acquisition layer and new data and remote control services in the external interaction layer. This makes GeoDADIS a very flexible and general purpose tool with broad application in many data monitoring domains.

Geographic perspectives on vulnerability analysis

This special issue of GeoJournal is centered on geographic approaches to vulnerability analysis. Six papers addressing several core areas of active research in vulnerability analysis are included in this volume of work. In particular, network analysis methods, geographic data acquisition and use, measurement of vulnerability, evaluation of spatial and temporal variability in vulnerability, as well as related theoretical and policy issues are examined in detail.

Combining geographic information system, multicriteria evaluation techniques and fuzzy logic in siting MSW landfills

This study presents a methodology for siting municipal solid waste landfills, coupling geographic information systems (GIS), fuzzy logic, and multicriteria evaluation techniques. Both exclusionary and non-exclusionary criteria are used. Factors, i.e., non-exclusionary criteria, are divided in two distinct groups which do not have the same level of trade off. The first group comprises factors related to the physical environment, which cannot be expressed in terms of monetary cost and, therefore, they do not easily trade off. The second group includes those factors related to human activities, i.e., socioeconomic factors, which can be expressed as financial cost, thus showing a high level of trade off. GIS are used for geographic data acquisition and processing. The analytical hierarchy process (AHP) is the multicriteria evaluation technique used, enhanced with fuzzy factor standardization. Besides assigning weights to factors through the AHP, control over the level of risk and trade off in the siting process is achieved through a second set of weights, i.e., order weights, applied to factors in each factor group, on a pixel-by-pixel basis, thus taking into account the local site characteristics. The method has been applied to Evros prefecture (NE Greece), an area of approximately 4,000 km2. The siting methodology results in two intermediate suitability maps, one related to environmental and the other to socioeconomic criteria. Combination of the two intermediate maps results in the final composite suitability map for landfill siting.

デジタル写真測量システム‐ＣＶ２の開発及び応用

This paper aims to present our research and discussion on establishing a practical system which integrates the technologies of Image Processing, Photogrammetry and GIS for the purpose of middle and large scale map making and revision. As it is very difficult for a computer to understand an image automatically and the low effiency of the data aquisition is still the big limitation of the application of GISs now, an idea of operator-guided semi-automatic processing for geographic data acquisition was proposed and studied in this paper.

Spatial Sampling: A Technique for Acquisition of Geographic Data from Aerial Photographs and Maps, Gunnar Olsson, National Technical Service Report AD 725 612, U.S. Department of Commerce, Springfield, 1971. 215 x 280 mm., vii and 254 pages, 39 tables and 47 diagrams and maps, typescript with paper covers.

<b>Spatial Sampling: A Technique for Acquisition of Geographic Data from Aerial Photographs and Maps</b>, Gunnar Olsson, National Technical Service Report AD 725 612, U.S. Department of Commerce, Springfield, 1971. 215 x 280 mm., vii and 254 pages, 39 tables and 47 diagrams and maps, typescript with paper covers.