3 research outputs found

    The Nachtlichter app: a citizen science tool for documenting outdoor light sources in public space

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    The relationship between satellite based measurements of city radiance at night and the numbers and types of physical lights installed on the ground is not well understood. Here we present the "Nachtlichter app", which was developed to enable citizen scientists to classify and count light sources along street segments over large spatial scales. The project and app were co-designed: citizen scientists played key roles in the app development, testing, and recruitment, as well as in analysis of the data. In addition to describing the app itself and the data format, we provide a general overview of the project, including training materials, data cleaning, and the result of some basic data consistency checks

    Development of a Web GIS for small-scale detection and analysis of COVID-19 (SARS-CoV-2) cases based on volunteered geographic information for the city of Cologne, Germany, in July/August 2020

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    Background\bf Background Various applications have been developed worldwide to contain and to combat the coronavirus disease-19 (COVID-19) pandemic. In this context, spatial information is always of great significance. The aim of this study is to describe the development of a Web GIS based on open source products for the collection and analysis of COVID-19 cases and its feasibility in terms of technical implementation and data protection. Methods\bf Methods With the help of this Web GIS, data on this issue were collected voluntarily from the Cologne area. Using house perimeters as a data basis, it was possible to check, in conjunction with the Official Topographic Cartographic Information System object type catalog, whether buildings with certain functions, for example residential building with trade and services, have been visited more frequently by infected persons than other types of buildings. In this context, data protection and ethical and legal issues were considered. Results\bf Results The results of this study show that the development of a Web GIS for the generation and evaluation of volunteered geographic information (VGI) with the help of open source software is possible. Furthermore, there are numerous data protection and ethical and legal aspects to consider, which not only affect VGI per se but also affect IT security. Conclusions\bf Conclusions From a data protection perspective, more attention needs to be paid to the intervention and post-processing of data. In addition, official data must always be used as a reference for the actual spatial consideration of the number of infections. However, VGI provides added value at a small-scale level, so that valid information can also be reliably derived in the context of health issues. The creation of guidelines for the consideration of data protection, ethical aspects, and legal requirements in the context of VGI-based applications must also be considered. Trial registration\textit {Trial registration} The article does not report the results of a health care intervention for human participant

    Modelling the spatial impact of regional planning and climate change prevention strategies on land consumption in the Rhine-Ruhr Metropolitan Area 2017–2030

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    Urban sprawl is a ubiquitous with a complex network of driving forces and human and natural impacts on various scales of the coupled human-environment urban system. In Germany, a land consumption of 30 ha per day is envisaged. In that regard, the effect of growing metropolitan areas on the climate of local neighborhoods becomes more and more a topic in regional planning. Accordingly, the objectives of the study are a) to contribute to the climate change related land cover simulation efforts in Germany in a spatially explicit manner with a resolution of 30 m, b) to investigate future land consumption rates and population growth rates having a view on goal 11 of UN’s SDG, and c) analyze the spatial impact of planning policies in regard to land use planning and official climate change prevention strategies using Rhine-Ruhr Metropolitan Area (RRMA) in Western Germany as a study area. The study makes use of land use and land cover classification of multispectral satellite data and the derivation of land surface temperature based on Landsat satellite in order to calibrate and validate the urban growth model SUSM (scenario-based urban growth simulation model). Two scenarios for future land consumption 2030 are implemented and the future impacts of urban growth with the projection of land consumption rate (LCR), population growth rate (PGR), and LCRPGR index on municipality level, as well as the impact on regions vulnerable to climate change evaluated. The comparison of simulated urban growth to observed urban growth from 2005 to 2017 shows that the PA of SUSM for historic scenario is 68.06% with an overall accuracy of 97.15%, a Matthews correlation coefficient of 0.66, a figure of merit of 0.51 and area under curve of 0.84. The total quantity of new urban areas of our SUSM simulation 2030 were approximately 283 km2. While the difference in the simulated total quantity is nearly zero, the simulated allocation of new urban areas across the districts can differ by up to 25 km2 in the two scenarios. The number of municipalities with efficient urban land development rates increases in the SUSM scenario where no regional land development plan has been incorporated. This holds true for the number of municipalities with inefficient land use where even an increase from no plan to plan can be observed. LCRPGR is negative in most municipalities reflecting opposing trends of population and land consumption development. Most of new urban areas are distributed in open spaces important for the regional climate change prevention strategy. 32.98 % of new urban areas in our region of interest can be found in these zones in the planning scenario and 25.76 % in the scenario without planning information in SUSM model. It can be concluded that regional planning in RRMA region has no positive effect on the interregional development of future land consumption in terms of quantity, allocation, and impact on climate change prevention
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