Günter Strunz

Influence of image fusion approaches on classification accuracy: a case study

While many studies in the field of image fusion of remotely sensed data aim towards deriving new algorithms for visual enhancement, there is little research on the influence of image fusion on other applications. One major application in earth science is land cover mapping. The concept of sensors with multiple spatial resolutions provides a potential for image fusion. It minimises errors of geometric alignment and atmospheric or temporal changes. This study focuses on the influence of image fusion on spectral classification algorithms and their accuracy. A Landsat 7 ETM+ image was used, where six multispectral bands (30 m) were fused with the corresponding 15 m panchromatic channel. The fusion methods comprise rather common techniques like Brovey, hue‐saturation‐value transform, and principal component analysis, and more complex approaches, including adaptive image fusion, multisensor multiresolution image fusion technique, and wavelet transformation. Image classification was performed with supervised methods, e.g. maximum likelihood classifier, object‐based classification, and support vector machines. The classification was assessed with test samples, a clump analysis, and techniques accounting for classification errors along land cover boundaries. It was found that the adaptive image fusion approach shows best results with low noise content. It resulted in a major improvement when compared with the reference, especially along object edges. Acceptable results were achieved by wavelet, multisensor multiresolution image fusion, and principal component analysis. Brovey and hue‐saturation‐value image fusion performed poorly and cannot be recommended for classification of fused imagery.

Emergency Preparedness in the Case of a Tsunami—Evacuation Analysis and Traffic Optimization for the Indonesian City of Padang

The “Last-Mile Evacuation” research project develops a numerical last mile tsunami early warning and evacuation information system on the basis of detailed earth observation data and techniques as well as unsteady, hydraulic numerical modeling of small-scale flooding and inundation dynamics of the tsunami including evacuation simulations in the urban coastal hinterland for the city of Padang, West Sumatra, Indonesia. It is well documented that Sumatra’s third largest city with almost one million inhabitants is located directly on the coast and partially sited beneath the sea level, and thus, is located in a zone of extreme risk due to severe earthquakes and potential triggered tsunamis. “Last-Mile” takes the inundation dynamics into account and additionally assesses the physical-technical susceptibility and the socio-economic vulnerability of the population with the objective to mitigate human and material losses due to possible tsunamis. By means of discrete multi-agent techniques risk-based, time- and site-dependent forecasts of the evacuation behavior of the population and the flow of traffic in large parts of the road system in the urban coastal strip are simulated and concurrently linked with the other components.

Risk reduction at the “ Last - Mile ”: an attempt to turn science into action by the example of Padang, Indonesia

More than ever before, the last decade revealed the immense vulnerability of the world’s cities to natural hazards. Neither the tsunami in the Indian Ocean in 2004, the hurricane Katrina in 2005, the cyclone Nargis in 2008 nor the earthquakes in Sichuan in 2008 or in Haiti 2010 found the people, the city administrations or the national or international organizations well prepared in the advent of anticipated but to a large extent disregarded natural disasters. It is evident that the lack of tailor-made disaster management plans and standard operational procedures are often the crucial point in proper risk reduction approaches. This study presents an approach to transfer knowledge of an extensive multidisciplinary scientific study on risk identification into recommendations for risk reduction strategies. The study has been conducted by means of a combination of experts from different scientific communities coming from civil and coastal engineering, remote sensing, social sciences, evacuation modelling and capacity development. The paper presents the results of this research approach and interweaves key findings with recent experiences from an eyewitness on a previous hazard event. Thus, necessary tsunami hazard and vulnerability information as well as valuable insights into preparedness activities have been derived for initiating updated infrastructural designs and practical recommendations for emergency management as well as strategic spatial planning activities at the local scale. The approach was applied in the context of tsunami early warning and evacuation planning in the coastal city of Padang, Western Sumatra, Republic of Indonesia.

Assessing building vulnerability to earthquake and tsunami hazard using remotely sensed data

Quantification of building vulnerability to earthquake and tsunami hazards is a key component for the implementation of structural mitigation strategies fostering the essential shift from post-disaster crisis reaction to preventive measures. Facing accelerating urban sprawl and rapid structural change in modern urban agglomerations in areas of high seismic and tsunami risk, the synergetic use of remote sensing and civil engineering methods offers a great potential to assess building structures up-to-date and area-wide. This paper provides a new methodology contextualizing key components in quantifying building vulnerability with regard to sequenced effects of seismic and tsunami impact. The study was carried out in Cilacap, a coastal City in Central Java, Indonesia. Central is the identification of significant correlations between building characteristics, easily detectable by remote sensing techniques, and detailed in situ measurements stating precise building vulnerability information. As a result, potential vertical evacuation shelters in the study area are detected and a realistic vulnerability assessment of the exposed building stock is given. These findings obtained allow for prioritization of intervention measures such as awareness and preparedness strategies and can be implemented in local disaster management.

Rapid mapping in support of emergency response after earthquake events

Earthquakes and other sudden onset natural disasters require quick and efficient emergency response. Earth observation (EO) data can make a valuable contribution to emergency response efforts if provided within hours and at the most days after the event. Mechanisms like the International Charter Space and Major Disasters and the European GMES Emergency Response Service provide the necessary basis for an efficient and rapid provision of EO data and damage mapping. This paper provides an overview of earthquake damage assessment methodologies, their potential and their limitations in a rapid mapping context and outlines a methodology for casualty estimation. Two case studies—the 2010 Haiti earthquake and the 2011 Van (Turkey) earthquake—are presented, where DLR’s Center for satellite-based crisis information (ZKI) provided rapid damage maps using a team-based visual interpretation approach. Additionally, the application of a casualty estimation method in the immediate aftermath of an earthquake is outlined.

Widening a narrow road: remote sensing contributing to the multifaceted problem of earthquake risk reduction

If we could reliably predict place and time of earthquakes with a sufficient time to handle, the number of fatal casualties and injuries could be immensely reduced. However, earthquake prediction in a deterministic sense has not been solved yet. And it is unclear whether mankind will ever find solutions to exactly predict place and time of earthquakes. Thus, we need to seek new, innovative ideas to reduce the impact of earthquakes hitting vulnerable areas across the globe.

Integrating remote sensing and social science

The alignment, small-scale transitions and characteristics of buildings, streets and open spaces constitute a heterogeneous urban morphology. The urban morphology is the physical reflection of a society that created it, influenced by historical, social, cultural, economic, political, demographic and natural conditions as well as their developments. Within the complex urban environment homogeneous physical patterns and sectors of similar building types, structural alignments or similar built-up densities can be localized and classified. Accordingly, it is assumed that urban societies also feature a distinctive socio-economic urban morphology that is strongly correlated with the characteristics of a citys physical morphology: Social groups settle spatially with ones peer more or less segregated from other social groups according to, amongst other things, their economic status. This study focuses on the analysis, whether the static physical urban morphology correlates with socioeconomic parameters of its inhabitants here with the example indicators income and value of property. Therefore, the study explores on the capabilities of high resolution optical satellite data (Ikonos) to classify patterns of urban morphology based on physical parameters. In addition a household questionnaire was developed to investigate on the cities socioeconomic morphology.

Hazard analysis and estimation of people exposure as contribution to tsunami risk assessment in the West Coast of Sumatra, the South Coast of Java and Bali

Summary. Th e Indian Ocean Tsunami 2004 dramatically showed the catastrophic consequences when destructive tsunami waves are striking coastal areas. Moreover, it became clear that there is an urgent need for tsunami early warning systems to be set up together with appropriate awareness raising and preparedness activities. In response to this catastrophic event and under the coordination by the UNESCO Intergovernmental Oceanographic Commission the Indian Ocean countries are jointly working on the development, implementation and operation of a tsunami early warning system and the realization of disaster risk assessment and preparedness activities. A crucial component in disaster risk management is the availability of reliable information on the population distribution in the tsunami hazard zones in order to mitigate the impact of natural disasters. Th e mapping of tsunami hazard zones and the estimation of people exposure will help the government to improve the evacuation planning and to decrease the amount of people at risk. Th is paper presents research results developed in the framework of the German-Indonesian Tsunami Early Warning System project focussing on the west coast of Sumatra, the south coast of Java, and Bali. Th e methodology for the determination of the hazard zones is based on a multiscenario approach. For the estimation of the population distribution a method is applied that combines statistical data with land use information in order to disaggregate the census data proportionally. Th is approach provides estimates for day- and night-time population in the hazard zones. Th e hazard and exposure maps are provided for the whole coastal regions and, in more detail, for the study areas Padang, Cilacap and Kuta. Moreover, essential key parameters of this analysis are integrated in the Decision Support System of the Indonesian Tsunami Early Warning Centre.

Towards automated forest-type mapping – a service within GSE Forest Monitoring based on SPOT-5 and IKONOS data

Object-based semi-automated segmentation and classification approaches have gained importance in the analysis of remote sensing data over the last few years. Particularly when it comes to operational processing of multi-seasonal input data, independent and robust algorithms are needed. At the German Aerospace Center (DLR) a new method for forest type classification has been developed, covering all processing steps for object-based classification. An automatic adaptation of scene-specific feature values for the classification is implemented, based on automated extraction of feasible ground data. Therefore, no manual sampling of training data is necessary. For classification of mixed forests on the basis of IKONOS data, a special algorithm was developed that can be adapted to any kind of mixed forest definition. Forest age classes are derived based on a digital surface model. The developed method can be used for area-wide forest-type classification on the basis of high and very high-resolution satellite data.

The International Charter ‘Space and Major Disasters’: DLR’s Contributions to Emergency Response Worldwide

This article reports on the application of satellite-based Earth observation in the management of major natural or man-made disasters, such as earthquakes, floods, forest fires, landslides, or oil spills. Activities of the International Charter ‘Space and Major Disasters’, an international consortium of space agencies and satellite operators are introduced, and related contributions in terms of rapidly delivered satellite imagery and supporting services are illustrated. In particular, the role of the German Aerospace Center (DLR) is outlined, which became a member of the International Charter ‘Space and Major Disasters’ in October 2010.ZusammenfassungDie Internationale Charta ‘Space and Major Disasters’: Die Beiträge des DLR zur weltweiten Krisenreaktion. Dieser Artikel berichtet vom Einsatz der satellitengestützten Erdbeobachtung bei der Bewältigung von großen Naturkatastrophen und technischen Unfällen wie z.B. Erdbeben, Hochwasser, Waldbränden, Hangrutschungen oder Ölverschmutzungen. Es werden Aktivitäten der Internationalen Charta ‘Space and Major Disasters’, einem internationalen Zusammenschluss von Raumfahrtagenturen und Satellitenbetreibern, vorgestellt und deren Beiträge in Form von aktuellen Satellitendaten und unterstützenden Diensten aufgezeigt. Insbesondere wird die Rolle des Deutschen Zentrums für Luft- und Raumfahrt (DLR) aufgezeigt, welches im Oktober 2010 Mitglied der Internationalen Charta ‘Space and Major Disasters’ wurde.