Martin Habermeyer

The EnMAP Spaceborne Imaging Spectroscopy Mission for Earth Observation

Imaging spectroscopy, also known as hyperspectral remote sensing, is based on the characterization of Earth surface materials and processes through spectrally-resolved measurements of the light interacting with matter. The potential of imaging spectroscopy for Earth remote sensing has been demonstrated since the 1980s. However, most of the developments and applications in imaging spectroscopy have largely relied on airborne spectrometers, as the amount and quality of space-based imaging spectroscopy data remain relatively low to date. The upcoming Environmental Mapping and Analysis Program (EnMAP) German imaging spectroscopy mission is intended to fill this gap. An overview of the main characteristics and current status of the mission is provided in this contribution. The core payload of EnMAP consists of a dual-spectrometer instrument measuring in the optical spectral range between 420 and 2450 nm with a spectral sampling distance varying between 5 and 12 nm and a reference signal-to-noise ratio of 400:1 in the visible and near-infrared and 180:1 in the shortwave-infrared parts of the spectrum. EnMAP images will cover a 30 km-wide area in the across-track direction with a ground sampling distance of 30 m. An across-track tilted observation capability will enable a target revisit time of up to four days at the Equator and better at high latitudes. EnMAP will contribute to the development and exploitation of spaceborne imaging spectroscopy applications by making high-quality data freely available to scientific users worldwide.

Ensuring globally the TanDEM-X height accuracy: Analysis of the reference data sets ICESat, SRTM and KGPS-tracks

The TanDEM-X mission will derive a global digital elevation model (DEM) with satellite SAR interferometry. Height references play an important role to ensure the required height accuracy of 10m absolute and 2m relative for 90% of the data. In this paper the main height reference data sets ICESat (for DEM calibration), SRTM (for phase unwrapping) and kinematic GPS-Tracks (KGPS — for DEM verification) are analyzed regarding to their accuracy. For the ICESat data a reliable quality measure is developed. For SRTM an improved version adjusted to reliable ICESat data is presented and a concept for collecting and evaluating decimeter-precise kinematic GPS tracks is proposed.

Automated Allocation of Highly Structured Urban Areas in Homogeneous Zones From Remote Sensing Data by Savitzky–Golay Filtering and Curve Sketching

City morphology not only reveals spatial distribution of diverse physical parameters but also of diverse socio-economic characteristics. Because of this, spatial structure or zoning in urban spaces is a key variable for inferring information valuable for assessment, planning, and management purposes. The presented methodology shows a mathematical approach to derive homogeneous zones from a solely remote sensing land-cover classification result. By Savitzky-Golay filtering and a subsequent curve-sketching approach, an interpreter-independent differentiation within a city is computed. The classification shows the result of the arrangement of urban zoning without any ancillary data

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 0.45–2.45 µm and 8–13 µm 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 8–13 µm region with 32 channels of 150 nm 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 3 nm and a sensor noise equivalent temperature of 0.05–0.1 K are required for an accurate retrieval of emissivity spectra.

ARES: A new reflective / emissive Imaging Spectrometer for Terrestrial Applications

A new airborne imaging spectrometer introduced: the ARES (Airborne Reflective Emissive Spectrometer) to be built by Integrated Spectronics, Sydney, Australia, financed by DLR German Aerospace Center and the GFZ GeoResearch Center Potsdam, Germany, and will be available to the scientific community from 2003/2004 on. The ARES sensor will provide 160 channels in the solar reflective region (0.45-2.45 μm) and the thermal region (8-13 μm). It will consists of two separate coregistered optical systems for the reflective and thermal part of the spectrum. The spectral resolution is intended to be between 12 and 15 nm in the solar wavelength range and should reach 150nm in the thermal. ARES will be used mainly for environmental applications in terrestrial ecosystems. The thematic focus is thought to be on soil sciences, geology, agriculture and forestry. Limnologic applications should be possible but will not play a key role in the thematic applications. For all above mentioned key application scenarios the spectral response of soils, rocks, and vegetation as well as their mixtures contain the valuable information to be extracted and quantified. The radiometric requirements for the instrument have been modelled based on realistic application scenarios and account for the most demanding requirements of the three application fields: a spectral bandwidth of 15 nm in the 0.45-1.8 μm region, and 12 nm in the 2 - 2.45 μm region. The required noise equivalent radiance is 0.005, 0.003, and 0.003 mWcm-2sr-1μm-1 for the spectral regions 0.45-1 μm, 1 - 1.8 μm, and 2 - 2.45 μm, respectively.

EnMAP Ground Segment Design: An Overview and Its Hyperspectral Image Processing Chain

EnMAP (Environmental Mapping and Analysis Program; www.enmap.org) is the first German hyperspectral remote sensing satellite mission. This chapter focuses on the challenges on the design of the ground segment as a whole and in particular of its image processing chain. In the context of the system response time we investigate the ability of tilting the satellite which allows for frequent revisits and enables meaningful downstream change detection activities on a global scale. In the context of comparable and high-quality controlled products we investigate in detail the processing steps to radiometrically calibrate, spectrally characterize, geometrically and atmospherically correct the data. The status corresponds to the baseline for the production activities of the ground segment, namely only minor changes are expected. The launch is planned for 2016. The establishment and operation of the ground segment is under responsibility of the Earth Observation Center (EOC) and the German Space Operations Center (GSOC) at the German Aerospace Center (DLR).

Spectroradiometric requirements for the reflective module of the airborne spectrometer ARES

The Airborne Reflective/Emissive Spectrometer is specified as a whisk-broom imaging spectrometer for remote sensing of land surfaces covering the wavelength regions 0.47-2.45 /spl mu/m and 8-12 /spl mu/m with 160 spectral bands. The instrument is being built by Integrated Spectronics, financed by the German Aerospace Agency (DLR) and the GeoResearch Centre Potsdam (GFZ) and will be available to the scientific community from end 2005 on. The spectroradiometric design is based on scientific requirements derived from three main application scenarios comprising vegetation, soil, and mineral sciences. Two of these are described in this letter. Measured or modeled reflectance spectra are input to a simulation model that calculates at-sensor radiance spectra, resamples them with the channel-specific response functions, adds different amounts of noise in the radiance domain, and performs a retrieval to get the corresponding noisy surface reflectance spectra. The retrieval results as a function of the sensor noise level are compared with the accuracy requirements imposed by the different application fields taking into account the technical boundary conditions. The final specifications account for the most demanding requirements of the three application fields: a spectral sampling distance of 13-14 nm in the 470-1800 nm region, and 12 nm in the 2000-2450-nm region. The required noise-equivalent radiances are 5, 3, and 2 nW/spl middot/cm/sup -2//spl middot/sr/sup -1//spl middot/nm/sup -1/ for the spectral regions 470-1000, 1000-1800, and 2000-2450 nm, respectively.

An iterative unmixing approach in support of fractional cover estimation in semi-arid environments

During the last decades, human activities endanger the biological and economic productivity of drylands, observable by processes like soil erosion and long-term loss of vegetation. To identify these changes and underlying driving processes, it is essential to monitor the current state of the environment and to include this information in land degradation models. A frequently used input parameter is the degree of vegetation surface cover, thus there is a demand for quantitative cover estimation of large areas. Multispectral remote sensing has a limited ability to discriminate between dry vegetation components and bare soils. Therefore hyperspectral remote sensing is thought to be a possible source of information when applying adequate preprocessing and specific spectroscopic methodologies. The proposed approach is based on multiple endmember spectral unmixing, where the mixture model is iteratively improved using residual analysis and knowledge-based feature identification. It is believed that this automated methodology can provide quantitative fractional cover estimates for major ground cover classes as well as qualitative estimates of scene components. This apporach is currently tested using HyMap imaging spectrometer data of Cabo de Gata, Southern Spain, and will be adapted to larger areas based on hyperspectral data of future satellite instruments.

Towards a critical design of an operational ground segment for an Earth observation mission

Abstract The ground segment for the future remote sensing mission Environmental Mapping and Analysis Program (EnMAP; www.enmap.org) is developed by the Earth Observation Center and the German Space Operations Center at the German Aerospace Center. The launch is scheduled for 2017. An operational satellite ground segment is a highly complex heterogeneous system which has to cope with different levels of criticality, novelty, specificity, and to be operated for many years. It consists of equipment, hard- and software as well as operators with their procedures. The strengths of the global coherence of the segment-wide approach bringing these aspects together is examined and not on the local details of segment-specific issues. However, the effects on two software-based elements of the ground segment are considered in more detail, namely the product library and the level 2geo processor. The development methodology and how the critical design of the complete ground segment finished its detailed design phase successfully was achieved is analyzed. As a measure of the maturity of the design, its stability across the project phases is proposed.

Identifying pure urban image spectra using a learning urban image spectral archive (LUISA)

In this study a learning urban image spectral archive (LUISA) has been developed, that overcomes the issue of an incomplete spectral library and can be used to derive scene-specific pure material spectra. It consists of a well described starting spectral library (LUISA-A) and a tool to derive scene-based pure surface material spectra (LUISA-T). The concept is based on a three-stage approach: (1) Comparing hyperspectral image spectra with LUISA-A spectra to identify scene-specific pure materials, (2) extracting unknown pure spectra based on spatial and spectral metrics and (3) provides the framework to implement new surface material spectra into LUISA-A. The spectral comparison is based on several similarity measures, followed by an object- and spectral-based ruleset to optimize and categorize potentially new pure spectra. The results show that the majority of pure surface materials could be identified using LUISA-A. Unknown spectra are composed of mixed pixels and real pure surface materials which could be distinguished by LUISA-T.