Tobias Krüger

Land-use monitoring by topographic data analysis

The rate of land consumption is an important factor to be considered within policies on sustainable land use aiming to reduce demand for settlement and traffic areas. As an expression of the political intent to achieve sustainable development, the German government announced to reduce the consumption of open space for settlement or transportation infrastructure significantly by 2020. Progress toward such specific goals can, of course, only be monitored if planning authorities are supplied with up-to-date and precise information on land use. This article presents one approach to the calculation of trends in land use that uses geoprocessing of topographic base data. Among the advantages of this approach are the nationwide availability of data with homogeneous quality and regular mandatory updating by surveying authorities. The spatial analysis of topographic base data is currently a highly automated process, which means geoprocessing procedures can be repeated regularly in order to realize time series. Such systematic monitoring of land use is undertaken by the project Monitor of Settlement and Open Space Development (IOER Monitor). By mid-2013, the fourth time period based on data from 2012 will be available online, ensuring that information on a wide range of land-use types is provided for a time series beginning back in 2006. Thus, the IOER Monitor is a convenient tool for the analysis and monitoring of land use for all administrative units ranging from German municipalities (approximately 12,000 in number) to the country as a whole, as well as for raster cells ranging from 100 m to 10 km.

Using Raster DTM for Dike Modelling

Digital Terrain Models are necessary for the simulation of flood events. Therefore they have to be available for creating flood risk maps. River embankments for flood protection have been in use for centuries. Although they are artificial structures that actually do not belong to the natural elements of the land surface they are usually implicitly embedded in digital terrain data. Being elongated and elevated objects, they appear — depending on the used colour ramp for visualisation — as bright stripes on the surrounding background.

Measuring Land Take: Usability of National Topographic Databases as Input for Land Use Change Analysis: A Case Study from Germany

The implementation of sustainable land policies is in need of monitoring methods that go beyond a mere description of the proportion values of land use classes. The annual statistical surface area report on actual land utilization (German: “Bodenflache nach Art der tatsachlichen Nutzung”), published by the statistical offices of the German federal states and the federation, provides information on a set of pre-defined land use classes for municipalities, districts and federal states. Due to its surveying method of summing up usage information from cadastral registers, it is not possible to determine previous and subsequent usages of land parcels. Hence, it is hard to precisely indicate to what extent particular land use classes contribute to the settlement area increase. Nevertheless, this information is crucial to the understanding of land use change processes, which is needed for a subsequent identification of driving forces. To overcome this lack of information, a method for the spatial and quantitative determination of previous and subsequent land usages has been developed, implemented and tested. It is based on pre-processed land use data for different time slices, which are derived from authoritative geo-topographical base data. The developed method allows for the identification of land use changes considering small geometric shifts and changes in the underlying data model, which can be adaptively excluded from the balance.

Investigating the suitability of Sentinel-2 data to derive the urban vegetation structure

Urban green is indispensable from an urban ecological and social point of view and fulfils important functions such as dust binding, temperature reduction, wind damping or groundwater recharge. Especially for bioclimatic modeling, knowledge of size, structure and green volume of the urban vegetation is essential. Manual mapping of vegetation structures is timeconsuming and cost-intensive and can only ever be carried out in locally limited study areas. Active and passive remote sensing technologies in combination with automated methods for information extraction offer the opportunity to record the green structure in urban areas differentiated according to vegetation types. The new globally and freely available data provided by the European Copernicus Program raises the question whether these data are suitable for mapping and quantifying the urban green structure, including an accuracy estimation. Previous studies on the usability of Sentinel-2 data for vegetation analysis were essentially limited to crop and tree species classification in open space. The approach presented here thus considers for the first time the application of this data in a purely urban environment. Here we present a modeling approach based on multiple regression models. A Sentinel-2A scene from July 4, 2015 covering the greater Dresden area served as the input data set. After atmospheric correction of the satellite image scene 10 spectral channels were available. A high-resolution vegetation cover model with a grid width of 50 cm was available as a reference data set for the entire study area (City of Dresden, Germany). This takes into account the vegetation classes deciduous trees, conifers, shrubs, low (grassy) vegetation and arable land. Thus the area share of these vegetation types could be determined aggregated for each pixel of the satellite image scene. In addition, vegetation indices (NDVI and others) were calculated using suitable channels. For the prediction of each vegetation class, estimation equations were drawn up and evaluated with regard to their quality. Especially for deciduous and coniferous trees, satisfactory model quality values could be obtained, so that the green component prediction in these cases represents a useful basis for the determination of the green structure at the building block level in urban areas.

Bilanzierung zur Siedlungs- und Verkehrsflächenentwicklung

Die Umsetzung einer nachhaltigen Flachenpolitik erfordert ein Monitoring, welches nicht nur den jeweils aktuellen Stand der Nutzungsartenanteile an der Gesamtflache bilanziert, sondern auch den konkreten Wandel der Nutzungsarten hochauflosend beschreiben kann. Zum Prozessverstandnis und zur Beurteilung der Triebkrafte der Siedlungsentwicklung sind Aussagen zur Vor- und Nachnutzung von Flachen erforderlich. Vor diesem Hintergrund ist am Leibniz-Institut fur okologische Raumentwicklung (IOR) ein Verfahren entwickelt worden, mit dem Flachennutzungsanderungen unter Verwendung von aufbereiteten amtlichen Geobasisdaten (ATKIS Digitales Basis-Landschaftsmodell) identifiziert werden konnen, wobei geometrische und semantischen Korrekturen vorgenommen werden, um Fehlklassifizierungen weitgehend ausschliesen zu konnen. Auf Grundlage dieses Verfahrens werden in diesem Artikel deutschlandweite Analyseergebnisse zur Flachenneuinanspruchnahme von Siedlungs- und Verkehrsflachen (SuV-Flachen), differenziert nach Bundeslandern und bestimmten Nutzungsarten, fur die Bezugsjahre 2010 und 2015 vorgestellt. In einem Fazit wird auf die Voraussetzungen fur eine geobasisdatenbasierte Erhebung der Flachenneuinanspruchnahme Bezug genommen sowie kunftig zu erbringende Erganzungen des Datenbestandes benannt, die eine Erhohung der Ergebnisvaliditat herbeifuhren konnen.