The Spaceborne Imaging Spectrometer DESIS: Data Access and Scientific Applications

The DLR Earth Sensing Imaging Spectrometer (DESIS) is a space-based instrument installed and operated on the International Space Station (ISS). This space mission is the achievement of the collaboration between the German Aerospace Center (DLR) and the US company Teledyne Brown Engineering (TBE). DLR has developed the instrument and the software for data processing, while TBE provides the Multi-User System for Earth Sensing (MUSES) platform, where DESIS is installed, and the infrastructure for operation and data tasking

Uncertainties for Pre- and Post-Launch Radiometric Calibration of Imaging Spectrometers for Multi-Sensor Applications

An important aspect to using imaging spectrometer data is the radiometric characterization and calibration of the sensors and validation of their data products and doing so with error budgets with known traceability. The radiometric accuracy of a given sensor is important for demonstrating the expected quality of data from the sensor. Known traceability allows data from multiple sensors to be directly comparable as will become more important in the near future with the expected launches of multiple imaging spectrometers from multiple countries, agencies, and commercial entities. The current work describes the state of pre- and post-launch radiometric absolute and relative uncertainties and their role in harmonising on-orbit data. Examples of prelaunch uncertainties based on the calibration of EnMAP and the calibration planned for the CLARREO Pathfinder Mission are presented highlighting recent work in the area of detector-based approaches using tunable laser sources. Post-launch calibration approaches for Pathfinder, EnMAP, CHIME, and DESIS including traditional vicarious calibration methods and the challenges of working with commercial data are presented. The vicarious calibration discussion relies on the example of the recently-available RadCalNet data to describe typical methods and challenges that will be faced when harmonising data between imaging spectrometers as well as with multispectral sensors

Evalutating the potential of desis to infer plant taxonomical and functional diversities in europwean forests

Abstract. Tackling the accelerated human-induced biodiversity loss requires tools able to map biodiversity and its changes globally. Remote sensing (RS) offers unique capabilities of characterizing Earth surfaces; therefore, it could map plant biodiversity continuously and globally. This approach is supported by the Spectral Variation Hypothesis (SVH), which states that spectra and species (taxonomic and trait) diversities are linked through environmental heterogeneity. In this work, we evaluate the capability of the DESIS hyperspectral imager to capture plant diversity patterns as measured in dedicated plots of the network FunDivEUROPE. We computed functional and taxonomical diversity metrics from field taxonomic, structural, and foliar measurements in vegetation plots sampled in Spain and Romania. In addition, we also computed functional diversity metrics both from the DESIS reflectance factors and from vegetation parameters estimated via inversion of a radiative transfer model. Results showed that only metrics computed from spectral reflectance were able to capture taxonomic variability in the area. However, the lack of sensitivity was related to the insufficient plot size and the lack of spatial match between remote sensing and field data, but also the differences between the information contained in the field traits and remote sensing data, and the potential uncertainties in the remote estimates of vegetation parameters. Thus, while DESIS showed some sensitivity to plant diversity, further efforts are needed to deploy suitable biodiversity evaluation and validation plots and networks that support the development of biodiversity remote sensing products

Validation of DESIS Surface Reflectance Product with Measurements on Ground

The hyperspectral instrument "DLR Earth Sensing Imaging Spectrometer" (DESIS) was developed within a collaboration between the US company Teledyne Brown Engineering (TBE) and the German Aerospace Center (DLR). DESIS is operating onboard of the International Space Station (ISS) since August 2018 and is in operational phase since October 2019. The validation of the L2A products in remote sensing is performed by different approaches. One of them is the comparison of the ground surface reflectance as delivered by the L2A-remote sensing products with in-situ measurements. Those in-situ measurements are performed with spectroradiometers at the same wavelength of the remote sensor and at the time of a satellite overpass. The presentation provides recent validation results for the DESIS BOA reflectance product on basis of ground-based reference measurements. Accuracy represents the mean difference of BOA-reflectance retrieval to a reference value and uncertainty gives the rms around the reference. Accuracy and uncertainty of surface reflectance retrieval from DESIS data is benchmarked by comparison with surface reflectance retrieval from Sentinel-2 data

Temperate forest soil pH accurately Quantified with image spectroscopy

Forest canopies to some extent obscure passive reflectance of soil traits such as pH, as well as below-canopy vegetation, in the optical to middle infrared portions of the electromagnetic spectrum (approximately 400–2500 nm) which are typically used in airborne and spaceborne image spectrometers. In this study, we present, for the first time, an accurate estimation of soil pH across extensive areas using hyperspectral imaging data obtained from the DLR Earth Sensing Imaging Spectrometer (DESIS) satellite. Furthermore, we investigate the impact of predicted soil pH variation on the concentrations of micronutrients in both leaves and soil. Our modelling is based on a comprehensive in-situ field campaign conducted during the summers of 2020 and 2021. This campaign collected soil pH data for model calibration and validation from 197 plots located across three distinct temperate forest sites: Veluwezoom and Hoge Veluwe National Parks in the Netherlands, as well as the Bavarian Forest National Park in Germany. The soil pH for each test site was accurately predicted by means of a partial least squares regression (PLSR) model, root mean square error (RMSEcv) of 0.22 and the cross-validated coefficient of determination (R2CV) of 0.66. Our findings demonstrate that there are patches of extremely low soil pH possibly due to ongoing soil acidification processes. We saw a particularly significant decrease in soil pH (p ≤ 0.05) in the coniferous forests when compared to the deciduous forest. The acidification of forest soils had a profound impact on the variation of soil and leaf micronutrient content, particularly iron concentration. These results highlight the potential of image spectroscopy data from the DESIS satellite to monitor and estimate soil pH in forested areas over extensive areas given sufficient data. Our findings hold significant implications for soil pH monitoring programs, enabling forest managers to assess the impact of their management practices and gauge their effectiveness in maintaining soil and forest vitality

The Spaceborne Imaging Spectrometer DESIS: Mission summary and potential for scientific developments

The DLR Earth Sensing Imaging Spectrometer (DESIS) is a spaceborne instrument installed and operated on the International Space Station (ISS). The German Aerospace Center (DLR) has developed the instrument and the full pre-processing chain up to L2A, while the US company Teledyne Brown Engineering (TBE) provided the Multi-User System for Earth Sensing (MUSES) platform and the infrastructure for operations and data tasking. DESIS is equipped with an on-board calibration unit and a rotating pointing mirror (POI). The POI can change the line of sight in the forward/backward direction (independently of the MUSES orientation), allowing the observation of the same area with different pointing angles within an overflight. About four years after the mission’s kick-off, the DESIS spectrometer was integrated into MUSES in August 2018, marking the start of the commissioning phase. The DESIS on-orbit functional tests were successful, and the DLR-built processing chain installed at DLR for scientific users and at Amazon Web Service for commercial users started to generate operational L1B, L1C and L2A DESIS products. In October 2019 the operational phase started the distribution of the data to scientific and commercial users. Since then, the instrument performance has been constantly evaluated. In a continuous monitoring process, the data quality is controlled and, if necessary, the calibration algorithms and tables are adjusted. This is essential for the later data application by scientists. In particular, the monitoring approaches emphasize the need for high and consistent data quality over long time periods. In autumn 2021, the first DESIS user workshop demonstrated the widespread use of DESIS data for topics like water and terrestrial resource monitoring, biodiversity and forest management. This presentation will give an overview of the DESIS mission, data quality, data access, and provides examples and perspectives on the scientific exploitation of the mission. The contribution for the CHIME mission is presented exemplarily for the CHIME test sites that are constantly observed by DESIS since 2020. DESIS data acquisition opportunities rely on the non-sun-synchronous ISS orbit, resulting in observation and illumination conditions difficult to reproduce. On the other hand, DESIS time series contain images of different day times, sensor incident angles as well as sun zenith angles and thus, can open up new opportunities for the monitoring of Earth system processes that have a daily variability such as photosynthesis. Finally, DESIS multitemporal data stacks can be an essential data base for algorithm and operational processor developments that shall be able to handle massive data amounts. The DESIS data archive is open for such research and developments and thus, is a valuable imaging spectroscopy data source

The DESIS L2A processor and validation of L2A products using AERONET and RadCalNet data

The hyperspectral instrument "DLR Earth Sensing Imaging Spectrometer" (DESIS) is a VNIR sensor on-board of the International Space Station (ISS) and operational since October 2019. DESIS acquires images of Earth on user request with a swath of about 30 km width and 235 bands with a Full Width at Half Maximum (FWHM) of 3.5 nm in the spectral range 400 to 1000 nm. In this contribution we will present the basis of the atmospheric correction by PACO software, implemented inside the DESIS Ground Segment as L2A processor. The resulting L2A products will be validated against independent in-situ measurements. The aerosol optical thickness and water vapor will be compared with the Aerosol Robotic Network (AERONET) measurements and the surface reflectance will be validated with the Radiometric Calibration Network (RadCalNet) data