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Polarimetric Synthetic Aperture Radar Interferometry (Pol-InSAR) based forest height estimation for ecosystem monitoring and management has been developing rapidly in recent years. Spaceborne Pol-InSAR systems with long temporal baselines of several days always lead to severe temporal decorrelation, which can cause a forest height overestimation error. However, most forest height estimation studies have not considered the change in dielectric property as a factor that may cause temporal decorrelation with a long temporal baseline. Therefore, it is necessary to propose a new method that considers dielectric fluctuations and random motions of scattering elements to compensate for the temporal decorrelation effect. The lack of ground truth for forest canopy also needs a solution. Unsupervised methods could be a solution because they do not require the use of true values of tree heights as the ground truth to calculate their estimation accuracies. This paper aims to present an unsupervised forest height estimation method called Dielectric Fluctuation and Random Motion over Ground (DF-RMoG) to improve accuracy by considering the dielectric fluctuations and random motions. Its performance is investigated using Advanced Land Observing Satellite (ALOS)-1 Pol-InSAR data acquired over a German forest site with temporal intervals of 46 and 92 days. The authors analyze the relationship between forest height and different parameters with DF-RMoG and conventional models. Compared with conventional models, the proposed DF-RMoG model significantly reduces the overestimation error due to temporal decorrelation in forest height estimation according to its lowest average forest height.

The Environmental Mapping and Analysis Program (EnMAP) is a spaceborne German hyperspectral satellite mission that aims at monitoring and characterizing the Earth's environment on a global scale. The mission is now ready to start with the sensor being by end of 2021 in Flight Acceptance Review, ready to be shipped to the launch pad in early 2022. This paper presents first an update of the mission status with recent activities and developments from the space and the ground segment. Then, an update of selected highlights of the science segment activities at launch phase are presented including preparation and if possible early results for the validation of EnMAP products, updates on EnMAP science algorithms (EnMAP-Box) developed at GFZ, online education initiative (HYPERedu), and further mission support activities such as background mission.

This paper proposes a C/X/Ku/K band 6-bit digital step attenuator (DSA) which employs a variety of improved attenuation cells to achieve a wide bandwidth, stable amplitude variation, stable phase variation, and small area. In this paper, the improved T-type, π-type, and switched-path type topologies are analyzed theoretically and applied to different attenuation values to achieve the optimal attenuator performance. In addition, in order to reduce the complexity and to improve the stability of the overall radar system, the logic control circuit is integrated in the DSA chip in this paper. Finally, the proposed attenuator is implemented in 0.15μm GaAs technology, which has a maximum attenuation range of 31.5 dB with 0.5 dB steps. The proposed DSA exhibits a root-mean-square (RMS) attenuation error of less than 0.15 dB and an RMS phase error of less than 3°, at 4–24 GHz. The insertion loss (IL) and the area of the DSA are 4.3–4.5 dB and 1.5 mm × 0.4 mm, respectively. Benefiting from the improvements of the attenuation cells and the characteristic of GaAs technology with strong resistance to radiation and power processing capability, the proposed DSA is suitable for spaceborne radar systems.

Seagrass meadows are a key ecosystem of the Great Barrier Reef World Heritage Area, providing one of the natural heritage attributes underpinning the reef’s outstanding universal value. We reviewed approaches employed to date to create maps of seagrass meadows in the optically complex waters of the Great Barrier Reef and explored enhanced mapping approaches with a focus on emerging technologies, and key considerations for future mapping. Our review showed that field-based mapping of seagrass has traditionally been the most common approach in the GBRWHA, with few attempts to adopt remote sensing approaches and emerging technologies. Using a series of case studies to harness the power of machine- and deep-learning, we mapped seagrass cover with PlanetScope and UAV-captured imagery in a variety of settings. Using a machine-learning pixel-based classification coupled with a bootstrapping process, we were able to significantly improve maps of seagrass, particularly in low cover, fragmented and complex habitats. We also used deep-learning models to derive enhanced maps from UAV imagery. Combined, these lessons and emerging technologies show that more accurate and efficient seagrass mapping approaches are possible, producing maps of higher confidence for users and enabling the upscaling of seagrass mapping into the future.

In preparation of the German spaceborne imaging spectroscopy mission EnMAP (The Environmental Mapping and Analysis Program) and its upcoming launch in early 2022, the data product validation activities have been intensified. As part of the science preparation and mission support project led by the German Research Center (GFZ) Potsdam, the overall quality of the official EnMAP products has to be accessed and evaluated independently from the data quality control activities performed by the Ground Segment at DLR EOC. Therefore, the radiometric, spectral, reflective, geometric and general quality of the three official EnMAP products (L1B, L1C and L2A) has to be validated during the commissioning and nominal phase.This paper presents an update of the data product validation activities, an in-depth insight into the overall approach and into specifically designed methods described in the EnMAP Product Validation Plan.

RainCube (Radar in a CubeSat) is a technology demonstration mission to enable Ka-band precipitation radar technologies on a low-cost, quick-turnaround platform. The RainCube instrument concept was conceived at the Jet Propulsion Laboratory. Initial technology development and demonstration paved the way to a mission concept to validate two key technologies in the space environment – a miniaturized Ka-band precipitation profiling radar that occupies ~3U and a 0.5m Ka-band deployable parabolic antenna stowed within 1.5U. RainCube was selected within NASA Science Mission Directorate’s Research Opportunities in Space and Earth Science 2015 In-Space Validation of Earth Science Technologies solicitation. The spacecraft bus is developed by Tyvak Nanosatellite Systems, who is responsible for integration and test of the flight system and mission operations. The radar and spacecraft were delivered on time for their scheduled ISS deployment on the ELaNa-23 launch in May 2018 from Wallops Flight Facility. The ultra-lightweight compact deployable Ka-band antenna was successfully deployed on July 28, 2018 and the radar made its first observation of precipitation on August 27, 2018. The mission continues to operate and has met all its Level 1 requirements through repeated observations of precipitation in the atmosphere. At the time of writing, the RainCube mission has been extended through August of 2019 with the spacecraft expecting to stay in orbit until summer 2020, and the potential for the mission to be extended through the end of the spacecraft’s life. This paper discusses the developments and results achieved by this novel technical approach, and its impact on mission concepts that may address the Clouds, Convection and Precipitation Designated Targeted Observable as defined in the 2017 Earth Science Decadal Survey.

NASA's Global Ecosystem Dynamics Investigation (GEDI) is a spaceborne lidar mission which will produce near global (51.6°S to 51.6°N) maps of forest structure and above‐ground biomass density during its 2‐year mission. GEDI uses a waveform simulator for calibration of algorithms and assessing mission accuracy. This paper implements a waveform simulator, using the method proposed in Blair and Hofton (1999; https://doi.org/10.1029/1999GL010484), and builds upon that work by adding instrument noise and by validating simulated waveforms across a range of forest types, airborne laser scanning (ALS) instruments, and survey configurations. The simulator was validated by comparing waveform metrics derived from simulated waveforms against those derived from observed large‐footprint, full‐waveform lidar data from NASA's airborne Land, Vegetation, and Ice Sensor (LVIS). The simulator was found to produce waveform metrics with a mean bias of less than 0.22 m and a root‐mean‐square error of less than 5.7 m, as long as the ALS data had sufficient pulse density. The minimum pulse density required depended upon the instrument. Measurement errors due to instrument noise predicted by the simulator were within 1.5 m of those from observed waveforms and 70–85% of variance in measurement error was explained. Changing the ALS survey configuration had no significant impact on simulated metrics, suggesting that the ALS pulse density is a sufficient metric of simulator accuracy across the range of conditions and instruments tested. These results give confidence in the use of the simulator for the pre‐launch calibration and performance assessment of the GEDI mission., Key Points GEDI's simulator has been validated and found accurate enough for pre‐launch calibration activitiesThe uncertainties of the simulator have been quantified and ALS beam density identified as a sufficient measure of accuracyInteresting quirks of full‐waveform metrics have been highlighted and investigated

This paper presents an approach that automatically (but parametrically) reconstructs 2-D/3-D building footprints using 3-D synthetic aperture radar (SAR) tomography (TomoSAR) point clouds. These point clouds are generated by processing SAR image stacks via SAR tomographic inversion. The proposed approach reconstructs the building outline by exploiting both the roof and façade points. Initial building footprints are derived by applying the alpha shapes method on pre-segmented point clusters of individual buildings. A recursive angular deviation based refinement is then carried out to obtain refined/smoothed 2-D polygonal boundaries. A robust fusion framework then fuses the information pertaining to building façades to the smoothed polygons. Afterwards, a rectilinear building identification procedure is adopted and constraints are added to yield geometrically correct and visually aesthetic building shapes. The proposed approach is illustrated and validated using TomoSAR point clouds generated from a stack of TerraSAR-X high-resolution spotlight images from ascending orbit covering approximately 1.5 km2 area in the city of Berlin, Germany.

Aiming to acquire ultrahigh resolution images, algorithms for spaceborne spotlight synthetic aperture radar (SAR) imaging typically confront challenges of curved orbit and azimuth spectral aliasing. In order to conquer these difficulties, a method is proposed in this paper to obtain ultrahigh resolution spaceborne SAR images on a curved orbit, which is composed of the modified RMA (Range Migration Algorithm) and the modified deramping-based approach. The modified RMA is developed to deal with the effect introduced by a curved orbit and the modified deramping-based approach is utilized to handle the problem of azimuth spectral aliasing. In the modified RMA, the polynomial expression of SAR two-dimensional spectrum on a curved orbit is derived with fourth-order azimuth phase history model and series reversion. Then, the singular value decomposition (SVD) is applied to decompose the expression of SAR two-dimensional spectrum numerically in order to acquire coordinates for Stolt interpolation in the scenario of curved orbit. In addition, the modified deramping-based approach is derived by introducing orbital state vectors in order to accommodate the situation of curved orbit in the proposed method. Experiments are implemented on point target simulation in order to verify the effectiveness of the presented method. In experiments, the range and azimuth resolution can achieve 0.15 m and 0.14 m, with focused scene size of 3 km by 3 km.

Space agencies, international and national organisations and institutions recognize the importance of regularly updated and homogenized land cover information, in the context of both nomenclature and spatial resolution. Moreover, ensuring credibility to the users through validated products with transparent procedures is similarly of great importance. To this end, this study contributes with a systematic accuracy performance evaluation of continental and global land cover layers. Confidence levels during validation and a weighted accuracy assessment were designed and applied. Google Earth imagery were employed to assess the accuracy of three land cover products for the years 2010 and 2012. Results indicate high weighted overall accuracy rates of 89, 90, and 86% for CORINE Land Cover 2012, GIO High Resolution Layers, and Globeland30 datasets, respectively. Moreover, their inter-comparison highlights notable differences especially for classes Artificial Surfaces and Water. The deviation of specific classes from the general producer’s and user’s accuracy trends were identified. It is concluded that the different aspects of the employed land cover products can be highlighted more transparently and objectively by integrating confidence levels during the reference data annotation, by employing a stratified sampling based on the several Corine Level-3 subclasses and by applying a weighted overall accuracy procedure.

13 years after the introduction of the first digital airborne mapping camera in the ISPRS conference 2000 in Amsterdam, several digital cameras with more than 100 MPixels per image have been made available. They are now well established in the market and have replaced the analogue mapping cameras. A general improvement in image quality accompanied the digital camera development. The signal-to-noise ratio and the dynamic range are significantly better than with the analogue cameras. In addition, digital cameras can be spectrally and radiometrically calibrated. The use of these cameras required a rethinking in many places. In the recent years, some activities took place that will lead to a better understanding of the cameras and the data produced by these cameras. Several projects, like the projects of the German Society for Photogrammetry, Remote Sensing and Geoinformation (DGPF) or EuroSDR (European Spatial Data Research), were conducted to test and compare the performance of different cameras. This paper will give an overview of standards and alternative approaches in image quality criteria's, and the derivation and use of these parameters.

Soil properties are neither static nor homogenous with space and time. Capturing the spatial variation of soil properties through conventional methods is a difficult task. Hyperspectral remote sensing data provide rich source of information produced in the form of spectrum at each pixel which can be used to identify surface materials. Airborne and spaceborne narrowband hyperspectral sensors have come to the fore which provides spectral information across large area. Thus, it is a promising tool for studying soil properties and can be used as an alternative to conventional method. But atmospheric attenuation and low signal to noise ratio are major problems with this type of data. Preprocessing of hyperspectral airborne/spaceborne data is required to extract soil properties. This paper reviews previous studies on prediction of soil properties from hyperspectral airborne and satellite data during the past years and the preprocessing techniques used in these predictions.

Le Soleil est une étoile variable dont l’éclairement présente un large spectre de périodicités (de quelques minutes à plusieurs décennies). L’amplitude de ces variabilités présente une forte dépendance en longueur d’onde. La mesure précise de l’éclairement spectral hors atmosphère et de cette variabilité selon une échelle radiométrique absolue constituent une entrée fondamentale pour les domaines de recherche suivants :- En physique solaire, ces mesures permettent de valider les modèles étudiant la composition de l’atmosphère solaire, les processus physiques internes et leur variabilité.- La photochimie atmosphérique terrestre et les modèles climatiques. La composition, la structure thermique et la dynamique de l’atmosphère terrestre sont dépendantes du flux solaire incident, de sa distribution en longueur d’onde et de sa variabilité. Les mesures sont requises pour une validation des modèles de transfert radiatif et climatiques.La nécessité d’une mesure continue dans le temps et hors atmosphère s’impose car chaque cycle solaire possède ses propres caractéristiques. Ces mesures sont réalisées depuis plus de 30 ans par des spectroradiomètres adaptés à l’environnement spatial. L’instrument SOLSPEC (SOLar SPECtrum) a apporté une contribution majeure à ces mesures.Le travail présenté dans ce manuscrit est associé à la sélection de SOLSPEC pour une mission à bord de la Station Spatiale Internationale (ISS). Les objectifs ont consisté à adapter l’instrument pour une mission à long terme (2008-2016), à étendre la plage spectrale couverte par SOLSPEC et à réduire l’incertitude de mesures. Il est structuré en deux parties :- La remise à niveau de l’instrumentation et son étalonnage radiométrique.- Le traitement des données pour les premières mesures en orbite.L’instrument a été modifié pour satisfaire de nouvelles exigences de dimensions et de masse. De nouveaux sous-systèmes optiques (unité interne d’étalonnage, pointeur solaire) ont été développés pour permettre la détection et la correction de toute dérive angulaire ou de réponse absolue de manière autonome. La plage spectrale de fonctionnement a été étendue entre 166 et 3088 nm. Une caractérisation radiométrique approfondie de SOLSPEC a été effectuée. L’étalonnage absolu a été réalisé à partir de l’étalon primaire en éclairement spectral (rayonnement du corps noir) du PTB (Physikalisch-Technische Bundesanstalt). Une estimation des incertitudes standard utilisant le formalisme mathématique appliqué en métrologie a été développée. Les résultats donnent une incertitude réduite entre 2 % à 4 % pour la plage 166-370 nm, inférieure à 2 % entre 370 et 2350 nm, comprise entre 2 et 5 % pour l’intervalle 2350-2580 nm et de 5 à 10 % entre 2580 et 2920 nm. Une valeur inférieure à 1 % est atteinte entre 500 et 1900 nm. Les mesures consécutives à la mise en orbite de SOLSPEC ont confirmé le maintien des performances radiométriques. Le spectre solaire hors atmosphère a été déterminé et comparé aux résultats antérieurs et actuels des missions respectives SOLSPEC ATLAS et SORCE. Il correspond à l’activité solaire du début de la mission SOLAR (mi-2008).The Sun is a variable star. Its irradiance presents a wide range of periodicity varying from minutes to decades. The amplitude of this variability is strongly wavelength dependent. The accurate determination of the solar spectral irradiance above the atmosphere in absolute radiometric scale and the study of its variability are main issues for the following researches:- In solar physics, these measurements are required for the validation of the models studying the composition of the solar atmosphere, the internal physical processes and their variability.- For the photochemistry of the Earth’s atmosphere and the climate modeling. The composition, the thermal structure and the dynamics of the atmosphere are dependant on the incoming solar flux, its spectral distribution and variability. The measurements are required for the validation of radiative transfer and climate models.As each solar cycle presents a different behavior, there was a need for continuous measurements above the atmosphere. Such measurements were performed since more than 30 years by means of space qualified spectroradiometers. The SOLSPEC (SOLar SPECtrum) instrument brought a major contribution in this respect. The present work is devoted to the SOLSPEC instrument that was selected for a new mission on board the International Space Station (ISS). The objectives were to refurbish the instrument and to adapt it for a long term mission (2008-2016), to extend the wavelength coverage and to reduce the uncertainties on the measurements. This work is developed in two parts:- The refurbishment and the radiometric characterization of the instrument.- The data processing of the first results after the launch.The instrument was modified in order to fulfill new requirements of dimensions and mass. Different optical sub-systems (internal lamp unit, passive solar sensor) were developed in order to obtain on board capabilities for the detection and the correction of any trend in the absolute response. The spectral range was extended to 166 - 3088 nm. A full radiometric characterization of SOLSPEC has been carried out and is presented in this work. The absolute calibration was performed using the primary standard of spectral irradiance (black-body radiation) of the PTB (Physikalisch-Technische Bundesanstalt). The evaluation of the standard uncertainties is presented using the mathematical methodology applied in metrology. The results provide an uncertainty limited to 2 % - 4 % between 166 and 370 nm, below 2 % from 370 to 2350 nm, between 2 and 5 % for the spectral range 2350 - 2580 nm and 5 % to 10 % between 2580 and 2900 nm. The uncertainty is below 1 % between 500 and 1900 nm. The stability of the radiometric performances was demonstrated from the analysis of the first measurements after the launch, at the beginning of the mission. The solar spectrum above the atmosphere was determined and compared to results obtained from the previous SOLSPEC ATLAS and ongoing SORCE missions. This spectrum corresponds to the solar activity at mid-2008., Doctorat en Sciences de l'ingénieur, info:eu-repo/semantics/nonPublished

Spaceborne SAR system concepts and mission design is often based on algorithms developed and the experience gathered from airborne SAR experiments and associated dedicated campaigns. However, airborne SAR systems have better performance parameters than their future space-borne counterparts as their design is not impacted by mass, power, and storage constraints. This paper describes a methodology to extrapolate spaceborne quality SAR image products from long wavelength airborne polarimetric SAR data which were acquired especially for the development and validation of bio/geo-retrieval algorithms in forested regions. For this purpose not only system (sensor) related parameters are altered, but also those relating to the propagation path (ionosphere) and to temporal decorrelation.

The purpose of this paper is to present an end-to-end simulator for spaceborne high-resolution SAR systems that is capable of simulating realistic raw data and focused images of extended three-dimensional scenes. The simulator is based on precise mathematical modeling of an overall SAR system chain and generates information on the quality of the image data and its suitability to interpret target and background signatures. The principal components of the simulator are: - the generation of an extended scene, including the fully polarimetric scattering behavior of the three-dimensional surfaces, man made objects, and the typical SAR effects like overlay, speckle noise, shadowing;-an accurate SAR sensor simulation (antenna, transmit and receive path);-the generation of the raw data depending on the desired SAR mode (stripmap, spotlight mode);-the image processing and evaluation. The flexible and modular structure allows for adjustment and extension to fulfill different tasks. The most important modules reflecting the basic physical models will be described and simulation results will be demonstrated.