Hermann Kaufmann

Fusion of spectral and shape features for identification of urban surface cover types using reflective and thermal hyperspectral data

Abstract The urban environment is characterized by an intense multifunctional use of available spaces, where the preservation of open green spaces is of special importance. For this purpose, area-wide urban biotope mapping based on CIR aerial photographs has been carried out for the large cities in Germany during the last 10 years. Because of dynamic urban development and high mapping costs, the municipal authorities are interested in effective methods for mapping urban surface cover types, which can be used for evaluation of ecological conditions in urban structures and supporting updates of biotope maps. Against this background, airborne hyperspectral remote sensing data of the DAIS 7915 instrument have been analyzed for a test site in the city of Dresden (Germany) with regard to their potential for automated material-oriented identification of urban surface cover types. Previous investigations have shown that the high spectral and spatial variabilities of these data require the development of special methods, which are capable of dealing with the resulting mixed-pixel problem in its specific characteristics in urban areas. Earlier, methodological developments led to an approach based on a combination of spectral classification and pixel-oriented unmixing techniques to facilitate sensible endmember selection based on the reflective bands of the DAIS instrument. This approach is now extended by a shape-based classification technique including the thermal bands of the DAIS instrument to improve the detection of buildings during the process of identifying seedling pixels, which represent the starting points for linear spectral unmixing. This new approach increases the reliability of differentiation between buildings and open spaces, leading to more accurate results for the spatial distribution of surface cover types. Thus, the new approach significantly enhances the exploitation of the information potential of the hyperspectral DAIS 7915 data for an area-wide identification of urban surface cover types.

Reduction of Radiometric Miscalibration—Applications to Pushbroom Sensors

The analysis of hyperspectral images is an important task in Remote Sensing. Foregoing radiometric calibration results in the assignment of incident electromagnetic radiation to digital numbers and reduces the striping caused by slightly different responses of the pixel detectors. However, due to uncertainties in the calibration some striping remains. This publication presents a new reduction framework that efficiently reduces linear and nonlinear miscalibrations by an image-driven, radiometric recalibration and rescaling. The proposed framework—Reduction Of Miscalibration Effects (ROME)—considering spectral and spatial probability distributions, is constrained by specific minimisation and maximisation principles and incorporates image processing techniques such as Minkowski metrics and convolution. To objectively evaluate the performance of the new approach, the technique was applied to a variety of commonly used image examples and to one simulated and miscalibrated EnMAP (Environmental Mapping and Analysis Program) scene. Other examples consist of miscalibrated AISA/Eagle VNIR (Visible and Near Infrared) and Hawk SWIR (Short Wave Infrared) scenes of rural areas of the region Fichtwald in Germany and Hyperion scenes of the Jalal-Abad district in Southern Kyrgyzstan. Recovery rates of approximately 97% for linear and approximately 94% for nonlinear miscalibrated data were achieved, clearly demonstrating the benefits of the new approach and its potential for broad applicability to miscalibrated pushbroom sensor data.

The processing chain and Cal/Val operations of the future hyperspectral satellite mission EnMAP

The German Aerospace Center DLR - namely the Applied Remote Sensing Cluster CAF and the German Space Operations Center GSOC - is responsible for the establishment of the ground segment of the future German hyperspectral satellite mission EnMAP (Environmental Mapping and Analysis Program). The Applied Remote Sensing Cluster has long lasting experiences with air- and spaceborne acquisition, processing, and analysis of hyperspectral image data. This paper mainly addresses the concept of the operational and automatic processing chain and the calibration/data quality to generate high quality data products.

GIS-Based Integration of Heterogeneous Data for a Multi-temporal Landslide Inventory

Southern Kyrgyzstan is a region of high landslide activity that frequently endangers human lives and infrastructure. So far, precise spatio-temporal information on landslide activity has been limited, although landslide occurrence in this area has been investigated for the last 60 years by local authorities. The establishment of a comprehensive landslide inventory is a prerequisite for carrying out objective landslide hazard assessment. For this purpose, multiple sources of information about slope failures are analyzed with the goal of establishing a spatially and temporally consistent multi-temporal landslide inventory at a regional scale. In this context, the potential of satellite remote sensing and GIS based analysis is investigated. The paper describes the developed approach for multi-source landslide mapping and demonstrates its application to the Budalyk valley test site.

Research opportunities for studying land degradation with spectroscopic techniques

Desertification is a land degradation problem of major importance in the arid regions of the world. Deterioration in soil and plant cover have adversely affected nearly 70 percent of the drylands as mainly the result of human mismanagement of cultivated and range lands. Overgrazing, woodcutting, cultivation practices inducing accelerated water and wind erosion, improper water management leading to salinisation, are all causes of land degradation. In addition to vegetation deterioration, erosion, and salinisation, desertification effects can be seen in loss of soil fertility, soil compaction, and soil crusting. Combating desertification involves having an accurate knowledge on a current land degradation status and the magnitude of the potential hazard. We present here a new project that aims at deriving a global simplified Land Degradation Index (LDI) from hyperspectral remote sensing data. Indeed, specific soil properties directly linked to soil degradation status, such as chemical properties, organic matter content, mineralogical content, soil crusting, and runoff, as well as vegetation content and degradation status, could be derived from high-spectral resolution imagery. Then, global maps assessing drylands desertification status could be routinely developed. This paper, after a brief review of land degradation processes and assessment, discusses the capabilities of hyperspectral imagery for land degradation assessment.

A contribution to the reduction of radiometric miscalibration of pushbroom sensors

Imaging spectroscopy is used for a variety of applications such as the identification of surface cover materials and its spatiotemporal monitoring. Contrary to multispectral instruments more spectral information can be incorporated in the differentiation of materials. New generations of sensors are based on the pushbroom technology, where a linear array of sensors perpendicular to the flight direction scans the full width of the collected data in parallel as the platform moves. Contrary to whiskbroom scanners that collect data one pixel at a time pushbroom systems can simply gather more light as they sense a particular area for a longer time. This leads to a better Signal-to-Noise Ratio (SNR). In addition, the two dimensional photo detector array in pushbroom systems may enable different readout configuration settings, such as spatial and/or spectral binning, allowing a better control of the SNR. It follows from this that low reflective materials can be potentially sensed as well as high reflective materials without saturating the detector elements. However, the use of detector arrays requires a precise radiometric calibration as different detectors might have different physical characteristics. Any miscalibration results in visually perceptible striping and uncertainties increase in preceding analyses such as classification and segmentation (Datt et al., 2003). There are various reasons for miscalibration, for instance temporal fluctuations of the sensor temperature, deprecated calibration coefficients or uncertainties in the modelling of the calibration coefficients. In addition, ageing and environmental stresses highly affect the mechanical and optical components of a sensor system; its reliability is thus not such to grant unchanged calibration accuracies for the entire mission life span.

Automated Remote Sensing Based Landslide Detection for Dynamic Landslide Inventories

Dynamic landslide inventories are important for objective landslide hazard and risk assessment. Multi-temporal satellite remote sensing has the potential for automated landslide detection at a regional scale. For this purpose a new automated approach has been developed based on analysing temporal trajectories of NDVI values derived from a co-registered multi-temporal RapidEye data stack. Specific temporal footprints of vegetation changes enable identification of landslide events. Applying this approach to a 12,000 sqkm study area in Southern Kyrgyzstan, about 250 landslide events could be automatically detected between 2009 and 2012. Subsequent field checks have revealed that the vast majority of these events have been correctly identified. Thus, the developed approach is capable of automatically detecting different kinds of mass movements under diverse natural conditions.

Geodäsie und Fernerkundung am Helmholtz-Zentrum Potsdam – Deutsches GeoForschungsZentrum (GFZ)

302 zfv 5/2014 139. Jg. DOI 10.12902/zfv-0040-2014 Zusammenfassung Um das System Erde und seine Dynamik zu verstehen, müssen die darin ablaufenden Prozesse bekannt sein. Basis dafür sind globale, lange Zeiträume überdeckende Beobachtungsdaten der komplexen Vorgänge auf und innerhalb der Erde. Das GFZ hat eine integrierte bodenund satellitengestützte Geomonitoring-Infrastruktur geschaffen, mit der geodynamische Vorgänge der festen Erde, der Ozeane, der kontinentalen Hydrosphäre und großer Eisflächen erfasst werden können. Diese wird im Verbund mit nationalen und internationalen Partnern operationell betrieben und die damit gewonnenen Beobachtungsdaten werden zum besseren Verständnis des Erdsystems in numerische Modelle eingeführt. Neben der Modellbildung dynamischer vom Erdkern über die Erdoberfläche bis in die obere Atmosphäre reichender Prozesse ist mit dieser globalen Beobachtungsinfrastruktur eine Vielzahl geophysikalischer Untersuchungen möglich.

Isograde mapping and mineral identification on the island of Naxos, Greece, using DAIS 7915 hyperspectral data

The ESF-LSF 1997 flight campaign conducted by the German Aerospace Center (DLR) recorded several transects across the island of Naxos using the airborne hyperspectral scanner DAIS. The geological targets cover all major litho-tectonic units of a metamorphic dome with the transition of metamorphic zonations from the outer meta-sedimentary greenschist envelope to the gneissic amphibolite facies and migmatitic core. Mineral identification of alternating marble-dolomite sequences and interlayered schists bearing muscovite and biotite has been accomplished using the airborne hyperspectral DAIS 7915 sensor. Data have been noise filtered based on maximum noise fraction (MNF) and fast Fourier transform (FFT) and converted from radiance to reflectance. For mineral identification, constrained linear spectral unmixing and spectral angle mapper (SAM) algorithms were tested. Due to their unsatisfying results a new approach was developed which consists of a linear mixture modeling and spectral feature fitting. This approach provides more detailed and accurate information. Results are discussed in comparison with detailed geological mapping and additional information. Calcites are clearly separated from dolomites as well as the mica-schist sequences by a good resolution of the mineral muscovite. Thereon an outstanding result represents the very good resolution of the chlorite/mica (muscovite, biotite)-transition defining a metamorphic isograde.