Claudia Künzer

Regularizing method for the determination of the backscatter cross section in lidar data

The retrieval of the backscatter cross section in lidar data is of great interest in remote sensing. For the numerical calculation of the backscatter cross section, a deconvolution has to be performed; its determination is therefore an ill-posed problem. Most of the common techniques, such as the well-known method of Gaussian decomposition, make implicit assumptions on both the emitted laser pulse and the scatterers. It is well understood that a land surface is quite complicated, and in many cases it cannot be composed of pure Gaussian function combinations. Therefore the assumption of Gaussian decomposition of waveforms may be invalid sometimes. In such cases an inversion method might be a natural choice. We propose a regularizing method with a posteriori choice of the regularizing parameter for solving the problem. The proposed method can alleviate difficulties in numerical computation and can suppress the propagation of noise. Numerical evidence is given of the success of the approach presented for recovering the backscatter cross section in lidar data.

Experience and Perspective of Providing Satellite Based Crisis Information, Emergency Mapping & Disaster Monitoring Information to Decision Makers and Relief Workers

Recognizing an increasing demand for up-to-date and precise information on disaster and crisis situations the German Remote Sensing Data Center (DFD) of DLR has set up a dedicated interface for linking the available and comprehensive remote sensing and analysis capacities with national and international civil protection, humanitarian relief actors and political decision makers. This so called “Center for Satellite Based Crisis Information” (ZKI) is engaged in the acquisition, analysis and provision of satellite based information products on natural disasters, humanitarian crisis situation, and civil security. Besides response and assessment activities, DFDZKI also focuses on the provision of geoinformation for medium term rehabilitation, reconstruction and prevention activities. DFD-ZKI operates in national, European and international contexts, closely networking with public authorities (civil security), non-governmental organizations (humanitarian relief organizations), satellite operators and other space agencies. ZKI supports the “International Charter on Space and Major Disasters”, which is a major cooperative activity among international space agencies in the context of natural and man-made disasters.

Generation of Up to Date Land Cover Maps for Central Asia

Human activity and climate variability has always changed the Earth’s surface and both will mainly contribute to future alteration in land cover and land use changes. In this chapter we demonstrate a land cover and land use classification approach for Central Asia addressing regional characteristics of the study area. With the aim of regional classification map for Central Asia a specific classification scheme based on the Land Cover Classification System (LCCS) of the Food and Agriculture Organisation of the United Nations Environment Programme (FAO-UNEP) was developed. The classification was performed by using a supervised classification method applied on metrics, which were derived from Moderate Resolution Imaging Spectroradiometer (MODIS) data with 250 m spatial resolution. The metrics were derived from annual time-series of red and near-infrared reflectance as well as from Normalized Difference Vegetation Index (NDVI) and thus reflect the temporal behavior of different land cover types. Reference data required for a supervised classification approach were collected from several high resolution satellite imagery distributed all over the study area. The overall accuracy results for performed classification of the year 2001 and 2009 are 91.2 and 91.3 %. The comparison of both classification maps shows significant alterations for different classes. Water bodies such as Shardara Water Reservoir and Aral Sea have changed in their extent. Whereby, the size of the Shardara Water Reservoir is very dynamic from year to year due to water management and the eastern lobe of southern Aral Sea has decreased because of the lack of inflow from Amu Darja. Furthermore, some large scale changes were detected in sparsely vegetated areas in Turkmenistan, where spring precipitation mainly affects the vegetation density. In the north of Kazakhstan significant forest losses caused by forest fires and logging were detected. The presented classification approach is a suitable tool for monitoring land cover and land use in Central Asia. Such independent information is important for accurate assessment of water and land recourses.

Ten Years of Experience with Scientific TerraSAR-X Data Utilization

This paper presents the first comprehensive review on the scientific utilization of earth observation data provided by the German TerraSAR-X mission. It considers the different application fields and technical capabilities to identify the key applications and the preferred technical capabilities of this high-resolution SAR satellite system from a scientific point of view. The TerraSAR-X mission is conducted in a close cooperation with industry. Over the past decade, scientists have gained access to data through a proposal submission and evaluation process. For this review, we have considered 1636 data utilization proposals and analyzed 2850 publications. In general, TerraSAR-X data is used in a wide range of geoscientific research areas comprising anthroposphere, biosphere, cryosphere, geosphere, and hydrosphere. Methodological and technical research is a cross-cutting issue that supports all geoscientific fields. Most of the proposals address research questions concerning the geosphere, whereas the majority of the publications focused on research regarding “methods and techniques”. All geoscientific fields involve systematic observations for the establishment of time series in support of monitoring activities. High-resolution SAR data are mainly used for the determination and investigation of surface movements, where SAR interferometry in its different variants is the predominant technology. However, feature tracking techniques also benefit from the high spatial resolution. Researchers make use of polarimetric SAR capabilities, although they are not a key feature of the TerraSAR-X system. The StripMap mode with three meter spatial resolution is the preferred SAR imaging mode, accounting for 60 percent of all scientific data acquisitions. The Spotlight modes with the highest spatial resolution of less than one meter are requested by only approximately 30 percent of the newly acquired TerraSAR-X data.

Data standardization and modeling in a web based information system

This paper describes data handling within a web-based information system in terms of data standardization, data modeling and data ingestion. The information system developed under the premise to make all datasets generated within the WISDOM project available for regional decision makers is based on a PostgreSQL object-relational database. Data standardization in this context is implemented by project specific guidelines that follow international standards like IS019115/19139 or OGC compliant Styled Layer Descriptors (SLD). Data modeling on the other hand improves data retrieval and accessibility by adding contextual information to all datasets through the registration to spatial, thematic and temporal reference objects. Ingesting new datasets into the information system is done in an automatic way for spatial datasets using a Java application, while non-spatial datasets have to be ingested by SQL commands. Implementing web-based interfaces to enable registered users to upload new datasets is a future task.