Andreas Müller

Delineation of Urban Footprints From TerraSAR-X Data by Analyzing Speckle Characteristics and Intensity Information

With a spatial resolution of up to 1 m, the German radar satellite TerraSAR-X (TSX) has significantly increased the usability of spaceborne synthetic aperture radar (SAR) imagery in the context of urban applications. This paper presents an approach toward the semiautomated detection of built-up areas (BAs) based on single-polarized TSX images. The proposed methodology includes a specific preprocessing of the SAR data and an automated image analysis procedure. The preprocessing focuses on the analysis of local speckle characteristics in order to provide a texture layer that highlights BAs. In the context of an object-oriented image analysis, this texture layer is used along with the original intensity information to automatically extract settlements. The technique is tested on the basis of 12 TSX scenes covering representative urban agglomerations distributed throughout the world. Overall, accuracies between 76% and 96% for the derived city footprints demonstrate the high potential of both the TSX imagery and the proposed analysis approach in detecting BAs. In order to demonstrate the robustness and transferability of the image analysis concept, we finally transferred the classification strategy from the object-oriented domain to a more general and simplified pixel-based approach.

An automatic atmospheric correction algorithm for visible/NIR imagery

The automatic correction of atmospheric effects currently requires visible to short‐wave spectral bands (400–2500 nm) to derive high accuracy surface reflectance data. Common techniques employ spectral correlations of dark targets in the short‐wave infrared (SWIR, around 2.2 µm), blue (480 nm) and red (660 nm) regions to derive the aerosol optical depth. A large number of current Earth‐observing satellite sensors have only three or four spectral channels in the visible and near‐infrared (VNIR) region (400–1000 nm), making an automatic image‐based atmospheric correction very difficult. This contribution presents a new algorithm and first results with VNIR imagery. The method starts with the assumption of average clear atmospheric conditions (aerosol optical depth AOD = 0.27, corresponding to a visibility of 23 km) and calculates the surface reflectance in the red and near‐infrared (NIR) bands. The second step derives a mask of dark vegetation pixels. It is calculated using multiple thresholds of vegetation index combined with red and NIR surface reflectance values. Then the red band surface reflectance for the dark pixels is estimated from the NIR reflectance as ρred = 0.1 ρnir, from which the aerosol optical depth (or visibility) can be calculated. The core of the VNIR algorithm consists of two subsequent iteration loops (visibility and ρred) to improve the visibility estimate. Results of the VNIR method are presented for Landsat‐5 Thematic Mapper (TM) and Landsat‐7 Enhanced Thematic Mapper Plus (ETM+) imagery using only the first four bands. The performance of the method is compared to the established dark pixel technique where the SWIR bands are included. Results show that the deviation between both methods is usually less than 0.005 reflectance units if measured in terms of the scene‐average reflectance, indicating a useful potential for this approach.

TanDEM-X mission—new perspectives for the inventory and monitoring of global settlement patterns

Abstract. TerraSAR-X add-on for digital elevation measurement (TanDEM-X) is a German Earth observation mission collecting a total of two global coverages of very high resolution (VHR) synthetic aperture radar (SAR) X-band data with a spatial resolution of around three meters in the years 2011 and 2012. With these, the TanDEM-X mission (TDM) will provide a unique data set which is complementary to existing global coverages based on medium (MR) or high resolution (HR) optical imagery. The capabilities of the TDM in terms of supporting the analysis and monitoring of global human settlement patterns are explored and demonstrated. The basic methodology for a fully-operational detection and delineation of built-up areas from VHR SAR data is presented along with a description of the resulting geo-information product—the urban footprint (UF) mask—and the operational processing environment for the UF production. Moreover, potential follow-on analyses based on the intermediate products generated in the context of the UF analysis are introduced and discussed. The results of the study indicate the high potential of the TDM with respect to an analysis of urbanization patterns, peri-urbanization, spatio-temporal dynamics of settlement development as well as population estimation, vulnerability assessment and modeling of global change.

De‐shadowing of satellite/airborne imagery

A de‐shadowing technique is presented for multispectral and hyperspectral imagery over land acquired by satellite/airborne sensors. The method requires a channel in the visible and at least one spectral band in the near‐infrared (0.8–1u2009µm) region, but performs much better if bands in the short‐wave infrared region (around 1.6 and 2.2u2009µm) are available as well. The algorithm consists of these major components: (i) calculation of the covariance matrix and zero‐reflectance matched filter vector, (ii) derivation of the unscaled and scaled shadow function, (iii) histogram thresholding of the unscaled shadow function to define the core shadow areas, (iv) region growing to include the surroundings of the core shadow areas for a smooth shadow/clear transition, and (v) de‐shadowing of the pixels in the final shadow mask. The critical parameters of the method are discussed. Example images from different climates and landscapes are presented to demonstrate the successful performance of the shadow removal process over land surfaces.

Influence of the Adjacency Effect on Ground Reflectance Measurements

It is well known that the adjacency effect has to be taken into account during the retrieval of surface reflectance from high spatial resolution satellite imagery. The effect results from atmospheric scattering, depends on the reflectance contrast between a target pixel and its large-scale neighborhood, and decreases with wavelength. Recently, ground reflectance field measurements were published, claiming a substantial influence of the adjacency effect at short distance measurements (< 2 m), and an increase of the effect with wavelength. The authors repeated similar field measurements and found that the adjacency effect usually has a negligible influence at short distances, decreasing with wavelength in agreement with theory, but can have a small influence in high-reflectance contrast environments. Radiative transfer calculations were performed to quantify the influence at short and long distances for cases of practical interest (vegetation and soil in a low-reflectance background). For situations with large reflectance contrasts, the atmospheric backscatter component of the adjacency effect can influence ground measurements over small-area targets, and should therefore be taken into account. However, it is not possible to draw a general conclusion, since some of the considered surfaces are known for exhibiting strong directional effects

A Comparison of Feature-Based MLR and PLS Regression Techniques for the Prediction of Three Soil Constituents in a Degraded South African Ecosystem

The accurate assessment of selected soil constituents can provide valuable indicators to identify and monitor land changes coupled with degradation which are frequent phenomena in semiarid regions. Two approaches for the quantification of soil organic carbon, iron oxides, and clay content based on field and laboratory spectroscopy of natural surfaces are tested. (1) A physical approach which is based on spectral absorption feature analysis is applied. For every soil constituent, a set of diagnostic spectral features is selected and linked with chemical reference data by multiple linear regression (MLR) techniques. (2) Partial least squares regression (PLS) as an exclusively statistical multivariate method is applied for comparison. Regression models are developed based on extensive ground reference data of 163 sampled sites collected in the Thicket Biome, South Africa, where land changes are observed due to intensive overgrazing. The approaches are assessed upon their prediction performance and significance in regard to a future quantification of soil constituents over large areas using imaging spectroscopy.

Can the Future EnMAP Mission Contribute to Urban Applications? A Literature Survey

With urban populations and their footprints growing globally, the need to assess the dynamics of the urban environment increases. Remote sensing is one approach that can analyze these developments quantitatively with respect to spatially and temporally large scale changes. With the 2015 launch of the spaceborne EnMAP mission, a new hyperspectral sensor with high signal-to-noise ratio at medium spatial resolution, and a 21 day global revisit capability will become available. This paper presents the results of a literature survey on existing applications and image analysis techniques in the context of urban remote sensing in order to identify and outline potential contributions of the future EnMAP mission. Regarding urban applications, four frequently addressed topics have been identified: urban development and planning, urban growth assessment, risk and vulnerability assessment and urban climate. The requirements of four application fields and associated image processing techniques used to retrieve desired parameters and create geo-information products have been reviewed. As a result, we identified promising research directions enabling the use of EnMAP for urban studies. First and foremost, research is required to analyze the spectral information content of an EnMAP pixel used to support material-based land cover mapping approaches. This information can subsequently be used to improve urban indicators, such as imperviousness. Second, we identified the global monitoring of urban areas as a promising field of investigation taking advantage of EnMAP’s spatial coverage and revisit capability. However, owing to the limitations of EnMAPs spatial resolution for urban applications, research should also focus on hyperspectral resolution enhancement to enable retrieving material information on sub-pixel level.

Aspects of operational atmospheric correction of hyperspectral imagery

The large number of spectral bands of hyperspectral instruments and the time required for the calculation of atmospheric look-up tables and the reflectance image cube pose very challenging requirements on an operational processing facility. This contribution presents some aspects and suggestions to reduce the processing time. Essential components are a precalculated database with a reduced number of spectral bands, an interactive phase to determine the appropriate atmospheric parameters, and a choice between medium and high accuracy levels for the atmospheric correction. The medium accuracy levels work with look-up tables for a reduced number of spectral bands employing interpolation for the channels omitted in the look-up tables. The high accuracy level uses tables for all channels and includes the scan angle dependence of the atmospheric radiance and transmittance functions. These ideas were successfully implemented and tested during several airborne hyperspectral campaigns resulting in an estimated time saving of a factor 3-7. The deviations of field measured reflectance spectra and spectra retrieved from airborne HyMap imagery are in the range of 2-3% or better.

Monitoring the Extent of Contamination from Acid Mine Drainage in the Iberian Pyrite Belt (SW Spain) Using Hyperspectral Imagery

Monitoring mine waste from sulfide deposits by hyperspectral remote sensing can be used to predict surface water quality by quantitatively estimating acid drainage and metal contamination on a yearly basis. In addition, analysis of the mineralogy of surface crusts rich in soluble salts can provide a record of annual humidity and temperature. In fact, temporal monitoring of salt efflorescence from mine wastes at a mine site in the Iberian Pyrite Belt (Huelva, Spain) has been achieved using hyperspectral airborne Hymap data. Furthermore, climate variability estimates are possible based on oxidation stages derived from well-known sequences of minerals, by tracing sulfide oxidation intensity using archive spectral libraries. Thus, airborne and spaceborne hyperspectral remote sensing data can be used to provide a short-term record of climate change, and represent a useful set of tools for assessing environmental geoindicators in semi-arid areas. Spectral and geomorphological indicators can be monitored on a regular basis through image processing, supported by field and laboratory spectral data. In fact, hyperspectral image analysis is one of the methods selected by the Joint Research Centre of the European Community (Ispra, Italy) to study abandoned mine sites, in order to assess the enforcement of the European Mine Waste Directive (2006/21/EC of the European Parliament and of the Council 15 March 2006) on the management of waste from extractive industries (Official Journal of the European Union, 11 April 2006). The pyrite belt in Andalucia has been selected as one of the core mission test sites for the PECOMINES II program (Cracow, November 2005), using imaging spectroscopy; and this technique is expected to be implemented as a monitoring tool by the Environmental Net of Andalucia (REDIAM, Junta de Andalucia, Spain).

Spectral and radiometric requirements for the airborne thermal imaging spectrometer ARES

ARES (Airborne Reflective/Emissive Spectrometer) is an airborne imaging spectrometer for remote sensing of land surfaces covering the wavelength regions 0.45–2.45u2009µm and 8–13u2009µm with 160 channels. The instrument is being built by Integrated Spectronics, financed by DLR and GFZ, and will be available to the scientific community from 2005 on. This contribution presents the design of the thermal spectrometer covering the 8–13u2009µm region with 32 channels of 150u2009nm bandwidth while a separate paper treats the instrument specifications in the solar reflective region. The spectro‐radiometric design is based on scientific requirements derived from application scenarios comprising vegetation, soils of different compositions, and mineral exploration. The corresponding emissivity spectra are input for a simulation model that calculates at‐sensor radiance spectra, resamples them with the channel‐specific response functions, adds different amounts of sensor noise to the signal, and performs a retrieval to get the corresponding noisy surface emissivity spectra. The results of the simulation study indicate that a spectral wavelength accuracy of 3u2009nm and a sensor noise equivalent temperature of 0.05–0.1u2009K are required for an accurate retrieval of emissivity spectra.