Ableitung demographischer Indikatoren aus offenen Datenquellen

Die zunehmende Verfügbarkeit von offenen (Geo-)Daten aus Beständen des öffentlichen Sektors ermöglicht die Generierung neuer Datensätze. Dieser Beitrag geht auf den Bedarf an hoch aufgelösten Daten ein, auf deren Basis kleinräumige Dynamiken abgebildet und ausgewertet werden können. Daraus lassen sich z. B. demographische Indikatoren aus offenen Datenquellen ableiten. Unter Einhaltung datenschutzrechtlicher Bestimmungen kann ein auf Gebäudeebene georeferenzierter Datensatz erstellt werden, der, trotz Abstrichen bezüglich Qualität, Aktualität und Belastbarkeit der Daten, als zweckmäßige Lösung bzw. Ergänzung für verschiedene Forschungsfragen dienen kann

Comparing different machine‐learning techniques to date Nile Delta sediments based on portable X‐ray fluorescence data

Geomorphology generally aims to describe and investigate the processes that lead to the formation of landscapes, while geochronology is needed to detect their timing and duration. Due to restrictions on exporting geological samples from Egypt, modern geoscientific studies in the Nile Delta lack the possibility of dating the investigated sediments and geological features by standard techniques such as OSL or AMS 14C; therefore, this study aims to validate a new approach using machinelearning algorithms on portable X‐ray fluorescence (pXRF) data. Archaeologically dated sediments from the archaeological excavations of Buto (Tell el‐Fara'in; on‐site) that pXRF analyses have geochemically characterized serve as training data for running and comparing Neural Nets, Random Forests, and single‐decision trees. The established pXRF fingerprints are transferred via machine‐learning algorithms to set up a chronology for undated sediments from sediment cores (i.e., the test data) of the nearby surroundings (off‐site). Neural Nets and Random Forests work fine in dating sediments and deliver the best classification results compared with singledecision trees, which struggle with outliers and tend to overfit the training data. Furthermore, Random Forests can be modeled faster and are easier to understand than the complex, less transparent Neural Nets. Therefore, Random Forests provide the best algorithm for studies like this. Furthermore, river features east of Kom el‐Gir are dated to pre‐Ptolemaic times (before 332 B.C.) when Kom el‐Gir had possibly not yet been settled. The research in this paper shows the success of close interactions from various scientific disciplines (Geoinformatics, Physical Geography, Archaeology, Ancient History) to decipher landscape evolution in the long‐term‐settled Nile Delta's environs using machine learning. With the approach's design and the possibility of integrating many other geographical/sedimentological methods, this study demonstrates the potential of the methodological approach to be applied in other geoscientific fields

Zur Identifikation und Visualisierung von Einfamilienhausgebieten der 1950er- bis 1970er-Jahre für eine nachhaltige Raumplanung

Alternde Einfamilienhausgebiete sind eine Herausforderung für die nachhaltige Raumplanung. Insbesondere im ländlichen Raum führt der demografische Wandel vermehrt zu Leerständen in den Gebäudebeständen der 1950er- bis 1970er-Jahre, da der Generationenwechsel von Erstbesitzern zu jungen Familien oder neuen Eigentümern häufig problematisch verläuft. Diese Gebiete zu identifizieren ist daher von entscheidendem Nutzen, um raumplanerische Maßnahmen treffen zu können. Anhand des Baujahres eines Gebäudes lassen sich relevante Einfamilienhausgebiete erfassen. Angaben zu Gebäudebaujahren finden sich u. a. im AFIS-ALKIS-ATKIS-Modell (AAA-Modell). In den konkreten Datensätzen fehlt diese Angabe jedoch zumeist. Daher werden in der jüngeren Forschung die bereits durch die INSPIRE-Richtlinie (Richtlinie 2007/2/EG) flächenmäßig verfügbaren Bebauungspläne behelfsweise herangezogen. Eine Auswertung hinsichtlich Festsetzungen und Datum der Rechtskraft ist hierbei jedoch nur ein Indiz für das Baujahr der Wohngebäude im überplanten Gemeindegebiet. Vor allem in schrumpfenden Regionen, in denen es oft zu Leerständen kommt, gibt es mitunter eine große zeitliche Diskrepanz zwischen dem Rechtskraftdatum eines Bebauungsplans und dem tatsächlichen Baujahr eines Gebäudes. Die Einfamilienhausgebiete lassen sich dort nicht abschließend identifizieren. Durch die Kombination verschiedener heterogener Quellen und Disaggregation von Daten können erforderliche Baujahresklassen identifiziert werden. Diese Methode bietet sich als praktikable Vorgehensweise an, die sowohl als Grundlage für Fragen der Forschung als auch der Raumplanung herangezogen werden kann. Als Evaluation dient ein Negativabgleich mit Erhebungen von Gebäudebaujahren der vergangenen ca. 25 Jahre in einem Testgebiet

A PageRank-based Reputation Model for VGI Data

AbstractQuality of data is one of the key issues in the domain of Volunteered geographic information (VGI). To this purpose, in literature VGI data has been sometime compared with authoritative geospatial data. Evaluation of single contributions to VGI databases is more relevant for some applications and typically relies on evaluating reputation of contributors and using it as proxy measures for data quality. In this paper, we present a novel approach for reputation evaluation that is based on the well known PageRank algorithm for Web pages. We use a simple model for describing different versions of a geospatial entity in terms of corrections and completions. Authors, VGI contributions and their mutual relationships are modeled as nodes of a graph. In order to evaluate reputation of authors and contributions in the graph we propose an algorithm that is based on the personalized version of PageRank

Recent Developments and Future Trends in Volunteered Geographic Information Research: The Case of OpenStreetMap

User-generated content (UGC) platforms on the Internet have experienced a steep increase in data contributions in recent years. The ubiquitous usage of location-enabled devices, such as smartphones, allows contributors to share their geographic information on a number of selected online portals. The collected information is oftentimes referred to as volunteered geographic information (VGI). One of the most utilized, analyzed and cited VGI-platforms, with an increasing popularity over the past few years, is OpenStreetMap (OSM), whose main goal it is to create a freely available geographic database of the world. This paper presents a comprehensive overview of the latest developments in VGI research, focusing on its collaboratively collected geodata and corresponding contributor patterns. Additionally, trends in the realm of OSM research are discussed, highlighting which aspects need to be investigated more closely in the near future

Dating human skeletal remains using 90Sr and 210Pb: case studies. [Dating human skeletal remains using Sr-90 and Pb-210: Case studies]

In legal medicine, the post mortem interval (PMI) of interest covers the last 50 years. When only human skeletal remains are found, determining the PMI currently relies mostly on the experience of the forensic anthropologist, with few techniques available to help. Recently, several radiometric methods have been proposed to reveal PMI. For instance, (14)C and (90)Sr bomb pulse dating covers the last 60 years and give reliable PMI when teeth or bones are available. (232)Th series dating has also been proposed but requires a large amount of bones. In addition, (210)Pb dating is promising but is submitted to diagenesis and individual habits like smoking that must be handled carefully. Here we determine PMI on 29 cases of forensic interest using (90)Sr bomb pulse. In 12 cases, (210)Pb dating was added to narrow the PMI interval. In addition, anthropological investigations were carried out on 15 cases to confront anthropological expertise to the radiometric method. Results show that 10 of the 29 cases can be discarded as having no forensic interest (PMI>50 years) based only on the (90)Sr bomb pulse dating. For 10 other cases, the additional (210)Pb dating restricts the PMI uncertainty to a few years. In 15 cases, anthropological investigations corroborate the radiometric PMI. This study also shows that diagenesis and inter-individual difference in radionuclide uptake represent the main sources of uncertainty in the PMI determination using radiometric methods

Sensor Fusion for Occupancy Estimation: A Study Using Multiple Lecture Rooms in a Complex Building

This paper uses various machine learning methods which explore the combination of multiple sensors for quality improvement. It is known that a reliable occupancy estimation can help in many different cases and applications. For the containment of the SARS-CoV-2 virus, in particular, room occupancy is a major factor. The estimation can benefit visitor management systems in real time, but can also be predictive of room reservation strategies. By using different terminal and non-terminal sensors in different premises of varying sizes, this paper aims to estimate room occupancy. In the process, the proposed models are trained with different combinations of rooms in training and testing datasets to examine distinctions in the infrastructure of the considered building. The results indicate that the estimation benefits from a combination of different sensors. Additionally, it is found that a model should be trained with data from every room in a building and cannot be transferred to other rooms

Comparison of Volunteered Geographic Information Data Contributions and Community Development for Selected World Regions

Volunteered Geographic Information (VGI) projects and their crowdsourced data have been the focus of a number of scientific analyses and investigations in recent years. Oftentimes the results show that the collaboratively collected geodata of one of the most popular VGI projects, OpenStreetMap (OSM), provides good coverage in urban areas when considering particular completeness factors. However, results can potentially vary significantly for different world regions. In this article, we conduct an analysis to determine similarities and differences in data contributions and community development in OSM between 12 selected urban areas of the world. Our findings showed significantly different results in data collection efforts and local OSM community sizes. European cities provide quantitatively larger amounts of geodata and number of contributors in OSM, resulting in a better representation of the real world in the dataset. Although the number of volunteers does not necessarily correlate with the general population density of the urban areas, similarities could be detected while comparing the percentage of different contributor groups and the number of changes they made to the OSM project. Further analyses show that socio-economic factors, such as income, can have an impact on the number of active contributors and the data provided in the analyzed areas. Furthermore, the results showed significant data contributions by members whose main territory of interest lies more than one thousand kilometers from the tested areas

Towards Automatic Vandalism Detection in OpenStreetMap

The OpenStreetMap (OSM) project, a well-known source of freely available worldwide geodata collected by volunteers, has experienced a consistent increase in popularity in recent years. One of the main caveats that is closely related to this popularity increase is different types of vandalism that occur in the projects database. Since the applicability and reliability of crowd-sourced geodata, as well as the success of the whole community, are heavily affected by such cases of vandalism, it is essential to counteract those occurrences. The question, however, is: How can the OSM project protect itself against data vandalism? To be able to give a sophisticated answer to this question, different cases of vandalism in the OSM project have been analyzed in detail. Furthermore, the current OSM database and its contributions have been investigated by applying a variety of tests based on other Web 2.0 vandalism detection tools. The results gathered from these prior steps were used to develop a rule-based system for the automated detection of vandalism in OSM. The developed prototype provides useful information about the vandalism types and their impact on the OSM project data

The Street Network Evolution of Crowdsourced Maps: OpenStreetMap in Germany 2007–2011

The OpenStreetMap (OSM) project is a prime example in the field of Volunteered Geographic Information (VGI). Worldwide, several hundred thousand people are currently contributing information to the “free” geodatabase. However, the data contributions show a geographically heterogeneous pattern around the globe. Germany counts as one of the most active countries in OSM; thus, the German street network has undergone an extensive development in recent years. The question that remains is this: How does the street network perform in a relative comparison with a commercial dataset? By means of a variety of studies, we show that the difference between the OSM street network for car navigation in Germany and a comparable proprietary dataset was only 9% in June 2011. The results of our analysis regarding the entire street network showed that OSM even exceeds the information provided by the proprietary dataset by 27%. Further analyses show on what scale errors can be reckoned with in the topology of the street network, and the completeness of turn restrictions and street name information. In addition to the analyses conducted over the past few years, projections have additionally been made about the point in time by which the OSM dataset for Germany can be considered “complete” in relative comparison to a commercial dataset