National Prioritäre Lebensräume im Regionalen Naturpark Schaffhausen

Die Biodiversität in der Schweiz ist stark unter Druck: mehr als ein Drittel der untersuchten Arten und die Hälfte der Lebensräume sind gefährdet oder ausgestorben. Funktionierende und artenreiche Ökosysteme sind die Basis unserer Lebensgrundlage. Für eine Priorisierung im Bereich Arten- und Lebensraumschutzes wurde die Liste der National Prioritären Arten und Lebensräume erstellt. Im Jahr 2019 aktualisierte das Bundesamt für Umwelt BAFU die Liste der National Prioritären Arten und erstelle dabei zum ersten Mal die Liste der National Prioritären Lebensräume. Bis vor der Erscheinung der Lebensraumkarte im Jahr 2021 fehlten quantitative Angaben über die geografische Verbreitung von Lebensräumen in der Schweiz. Die Karte kategorisiert schweizweit Lebensräume nach TypoCH. Seit der Erscheinung der Lebensraumkarte gibt es noch keine Übersicht für den Kanton Schaffhausen, die darstellt, auf welcher Plattform National Prioritäre Lebensräume am genausten hinterlegt sind. Die vorliegende Bachelorarbeit hat zum Ziel die Datenverfügbarkeit über die räumliche Verteilung von Lebensräumen im Kanton Schaffhausen zu untersuchen. Dabei wird eine Übersicht geschaffen, auf welchen Geoportalen National Prioritäre Lebensräume am genausten hinter-legt sind. Mittels des quantitativen Vorgehens einer Dokumentenanalyse sollen typisierende Lebensrauminformationen aufgesucht, synthetisiert und tabellarisch bewertet werden. Die Forschung zeigte, dass für vier von acht Lebensraumbereichen die Datenlage befriedigend ist. Jedoch stehen für die anderen vier Bereichen nur eine bedingt oder unbefriedigende Datenlage zu Verfügung. In 5 Punkte werden Gründe zu der unterschiedlichen Qualität der Datenlage diskutiert. Vorteile der Lebensrumkarte werden ebenfalls präsentiert. Weil die angewandte Methode die Resultate zur Datenlage aufrundet, könnte die Ergebnisse besser dargestellt werden, als sie in der Realität sind. Somit braucht es noch mehr Forschungen im Kanton Schaffhausen, die die Datenlage zur Lebensraumtypisierung überprüft. Eine zweite Version der Lebensraumkarte könnte ein Teil der unbeantworteten Fragen beantworten.Biodiversity in Switzerland is under severe pressure: more than a third of the species studied and half of the habitats are endangered or extinct. Functioning and species rich ecosystems are the basis of our livelihood. The list of Nationale Prioritären Arten und Lebensräumen was drawn up for prioritisation in the area of species and habitat protection. In 2019, the Federal Office for the Environment (FOEN) updated the list of National Priority Species and, in doing so, compiled the list of National Prioritären Lebensräumen for the first time. Until the publication of the habitat map in 2021, quantitative information on the geographical distribution of habitats in Switzerland was lacking. The map categorises habitats throughout Switzerland according to TypoCH. Since the publication of the habitat map, there is still no overview for the canton of Schaffhausen showing the platform on which National Priority Habitats are most accurately deposited. The aim of this doucment is to investigate the availability of data on the spatial distribution of habitats in the canton of Schaffhausen. In doing so, an overview is created of the geoportals on which National Prioritäre Lebensräume are stored most precisely. Using the quantitative procedure of a document analysis, typifying habitat information is to be searched for, synthesised and evaluated in tabular form. The research showed that for four out of eight habitat areas the data situation is satisfactory. However, for the other four areas, only limited or unsatisfactory data are available. Reasons for the different quality of data are discussed in 5 points. Advantages of the life cycle map are also presented. Because the method used rounds up the results on the data situation, the results could be presented better than they are in reality. Thus, more research is needed in the canton of Schaffhausen to verify the data situation on habitat typing. A second version of the habitat map could answer some of the unanswered questions

Monitoring of Oil Exploitation Infrastructure by Combining Unsupervised Pixel-Based Classification of Polarimetric SAR and Object-Based Image Analysis

In developing countries, there is a high correlation between the dependence of oil exports and violent conflicts. Furthermore, even in countries which experienced a peaceful development of their oil industry, land use and environmental issues occur. Therefore, an independent monitoring of oil field infrastructure may support problem solving. Earth observation data enables a fast monitoring of large areas which allows comparing the real amount of land used by the oil exploitation and the companies’ contractual obligations. The target feature of this monitoring is the infrastructure of the oil exploitation, oil well pads – rectangular features of bare land covering an area of approximately 50–60 m x 100 m. This article presents an automated feature extraction procedure based on the combination of a pixel-based unsupervised classification of polarimetric synthetic aperture radar data (PolSAR) and an object-based post-classification. The method is developed and tested using dual-polarimetric TerraSAR-X imagery acquired over the Doba basin in south Chad. The advantages of PolSAR are independence of the cloud coverage (vs. optical imagery) and the possibility of detailed land use classification (vs. single-pol SAR). The PolSAR classification uses the polarimetric Wishart probability density function based on the anisotropy/entropy/alpha decomposition. The object-based post-classification refinement, based on properties of the feature targets such as shape and area, increases the user’s accuracy of the methodology by an order of a magnitude. The final achieved user’s and producer’s accuracy is 59–71% in each case (area based accuracy assessment). Considering only the numbers of correctly/falsely detected oil well pads, the user’s and producer’s accuracies increase to even 74–89%. In an iterative training procedure the best suited polarimetric speckle filter and processing parameters of the developed feature extraction procedure are determined. The high transferability of the methodology is proved by an application to a second SAR acquisition

Automated feature extraction by combining polarimetric SAR and object-based image analysis for monitoring of natural resource exploitation

An automated feature extraction procedure based on the combination of a pixel-based unsupervised classification of polarimetric synthetic aperture radar data (PolSAR) and an object-based post-classification is presented. High resolution SpotLight dual-polarimetric (HH/VV) TerraSAR-X imagery acquired over the Doba basin, Chad, is used for method development and validation. In an iterative training procedure the best suited polarimetric speckle filter, processing parameters for the following entropy/anisotropy/alpha (H/A/α) decomposition and the heron based unsupervised Wishart classification are determined. By considering feature properties such as shape and area, the subsequent object-based post-classification increases the user’s and producer’s accuracy of the feature extraction procedure by an order of a magnitude to finally 59% to 71% in each case (valid for an area based accuracy assessment), or to even 74% to 89%, taking only the numbers of correctly/falsely detected features into account. In addition, the high transferability of the methodology is verified by an application to a second TerraSAR-X acquisition. The feature extraction procedure is developed for monitoring oil field infrastructure. For developing countries, several studies reported a high correlation between the dependence of oil exports and violent conflicts. Moreover, land use and environmental issues also occur in countries characterized by a peaceful development of their oil industry. Consequently, to support problem solving, an independent monitoring of the oil field infrastructure by Earth observation is proposed, enabling monitoring of large areas within a short time to compare the real amount of land used by the oil exploitation and the companies’ contractual obligations. The developed method focuses on the monitoring of the oil well pads, characterized by rectangular, approximately 50 m x 100 m large patches of bare land

Multi‐sensor OBIA methods for conflict research and humanitarian relief applications

Two case studies are presented showing the potential of remote sensing focusing on advanced semi-automated Object-Based Image Analysis (OBIA) methods to support the monitoring of conflict affected areas where traditional field assessments are hampered by security concerns or other hindering factors making field access very difficult. First, the exploitation of natural resources is examined by Synthetic Aperture Radar (SAR) polarimetry. Decomposition of polarimetric SAR data is applied to extract polarimetric parameters which have strong relation to the physical scattering mechanisms of the ground target. Then, a hereon based unsupervised land cover classification is conducted. Next, the result of the aforementioned pixel-based classification is improved by OBIA post-processing procedures. The second method described in this article concentrates on the application of state of the art machine learning techniques in order to provide a generic OBIA approach for the extraction of very small scaled features such as dwellings in Internally Displaced Persons (IDP) or refugee camps. Based on current Very High Resolution (VHR) optical data, a comprehensive set of descriptive attributes is derived comprising spectral, geometrical and relational information in order to characterize the features of interest. In the next step, the target features are identified and specified applying the non-parametric classification algorithm Support Vector Machines (SVM)

Monitoring of the 2015 Villarrica Volcano Eruption by Means of DLR's Experimental TET-1 Satellite

Villarrica Volcano is one of the most active volcanoes in the South Andes Volcanic Zone. This article presents the results of a monitoring of the time before and after the 3 March 2015 eruption by analyzing nine satellite images acquired by the Technology Experiment Carrier-1 (TET-1), a small experimental German Aerospace Center (DLR) satellite. An atmospheric correction of the TET-1 data is presented, based on the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Emissivity Database (GDEM) and Moderate Resolution Imaging Spectroradiometer (MODIS) water vapor data with the shortest temporal baseline to the TET-1 acquisitions. Next, the temperature, area coverage, and radiant power of the detected thermal hotspots were derived at subpixel level and compared with observations derived from MODIS and Visible Infrared Imaging Radiometer Suite (VIIRS) data. Thermal anomalies were detected nine days before the eruption. After the decrease of the radiant power following the 3 March 2015 eruption, a stronger increase of the radiant power was observed on 25 April 2015. In addition, we show that the eruption-related ash coverage of the glacier at Villarrica Volcano could clearly be detected in TET-1 imagery. Landsat-8 imagery was analyzed for comparison. The information extracted from the TET-1 thermal data is thought be used in future to support and complement ground-based observations of active volcanoes

Simulating extreme multi-hazard events with decentralized Web-processing services: Towards a better understanding of cascading impact

The RIESGOS Project (Multi-Risk Analysis And Information System Components for the Andes Region) funded by the German Ministry of Science and education (BMBF) has, as one of its main goals, the design and development of distributed software components for multi-hazard and risk analysis in particular by simulating hypothetical future high-impact events and their consequences. Implemented as an open library of interacting Web-services, these components will cover a full range of multi-hazard and risk related data acquisition and simulation services. These services include, for example: query of a seismic catalog, simulation of a shake map, simulation of a tsunami inundation scenario and assessment of expected damage and loss under consideration of cascading effects to critical infrastructure. Individual Web-services can be flexibly combined to produce multi-hazard scenarios with the ultimate goal to assist local authorities and decision makers to explore factors influencing the risk in their specific multi-hazard environments, thus improving disaster risk reduction and disaster management activities. To facilitate the development of a project which encompasses diverse hazard and risk components of various nature, our research is organized along a set of pre-described ‘event stories’ representing realistic, complex multi-hazard events with cascading effects in selected pilot regions of Chile, Peru and Ecuador. For each story, a storyboard is developed, which provides a narrative description of a hypothetical crisis evolution, defines the specific hazards involved, the related exposed assets and the expected consequences. In particular, these event stories target the following topics: - earthquake and tsunami (Chile and Peru); - heavy rain and river flooding (Peru); - volcano instability, lahar event and subsequent flooding via temporary river blockage (Ecuador). Each story can then be analysed in a more quantitative way by estimating different scenarios through numerical analysis and simulation of the different risk components. Remarkably, the consideration of vulnerability in a multi-hazard risk assessment framework is significantly more challenging with respect to the single hazard case, especially when interaction may occur at the vulnerability level due to physical damage accumulation. Furthermore, the project also aims at considering cascading effects to critical infrastructure such as power grids, roads and bridges. In order to ease up the visual exploration of such a complex multi-risk framework, a Web-based demonstrator platform integrating decentralized OGC Web Processing Service instances into multi-hazard and risk scenarios is being developed. To better meet the requirements of end-users, a thorough analysis of users’ needs and continued user participation during the whole development process is assured