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.

Abstract:The upcoming satellite mission EnMAP offers the opportunity to retrieve information on the seasonal development of vegetation parameters on a regional scale based on hyperspectral data. This study aims to investigate whether an analysis method for the retrieval of leaf area index (LAI), developed and validated on the 4 m resolution scale of six airborne datasets covering the 2012 growing period, is transferable to the spaceborne 30 m resolution scale of the future EnMAP mission. The widely used PROSAIL model is applied to generate look-up-table (LUT) libraries, by which the model is inverted to derive LAI information. With the goal of defining the impact of different selection criteria in the inversion process, different techniques for the LUT based inversion are tested, such as several cost functions, type and amount of artificial noise, number of considered solutions and type of averaging method. The optimal inversion procedure (Laplace, median, 4% inverse multiplicative noise, 350 out of 100,000 averages) is identified by validating the results against corresponding in-situ measurements (n = 330) of LAI. Finally, the best performing LUT inversion (R 2 = 0.65, RMSE = 0.64) is adapted to simulated EnMAP data, generated from the airborne acquisitions. The comparison of the retrieval results to upscaled maps of LAI, previously validated on the 4 m scale, shows that the optimized retrieval method can successfully be transferred to spaceborne EnMAP data. OPEN ACCESSRemote Sens. 2015, 7 10322

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The DLR_School_Lab Oberpfaffenhofen, operated by Germany's national research center for aeronautics and space (DLR) is a typical extracurricular science lab, its main objective being to attract secondary school students to Mathematics, Informatics, Natural Sciences, and Technology (MINT). It has been developed and operated since 2003 and offers thirteen hands-on experiments for secondary school classes, as well as advanced teacher trainings in physics and geography. Based on the expertise gained in the past eight years with approx. 18,000 students and 2,000 teachers, the concept behind the DLR_School_Lab is described, with special focus on its remote sensing experiments radar, laser, and infrared technology, optical environmental remote sensing, satellite navigation, and earth observation with satellite data. Furthermore, the issue of effectiveness of extracurricular science labs is addressed, as well as their suitability for talent support.