PROBA Research Articles

Discrimination of wheat crop stage using CHRIS/PROBA multi-angle narrowband data

Multi-angular narrowband compact high-resolution imaging spectrometer (CHRIS) on-board the project for on-board autonomy (PROBA) data of 18 March 2008 were used in this study to discriminate three different growth stages of wheat crop grown in the Central State Farm of Suratgarh, Rajasthan, India. Results showed that the off-nadir view angles performed better than nadir viewing for crop stage discrimination. Among all the off-nadir viewing angles, −55.37° view angle (in the backward-scattering direction) had the highest normalized distance between the crop stage classes. Based on the analysis, the five best bands were identified as 630, 660, 674, 705 and 712 nm for separating wheat at different stages.

PROBA-2 Attitude and Orbit Control System: In-Flight Results of Innovative GNC Functions

AbstractThe PRoject for On-Board Autonomy (PROBA) is an ESA technology-demonstration program aimed at the in-orbit validation of autonomy-enabling space technologies. Following the success of PROBA-1, the PROBA-2 spacecraft was launched on 2 November 2009 and continues the in-flight demonstration of on-board autonomy by performing a Sun observation mission as well as numerous flight experiments. This paper completes previously published articles by presenting the in-flight results of two innovative autonomous GNC functions: (1) Star Tracker Earth Exclusion Angle Prediction for Earth avoidance and (2) Large-Angle Rotation around Fixed Axis. Finally, flight results of the Attitude and Orbit Control System (AOCS) nominal operation using these innovative GNC functions will be presented.

Spectrodirectional Minnaert-k retrieval using CHRIS-PROBA data

We report on a detailed analysis of hyperspectral and multidirectional remote sensing data acquired using the Compact High Resolution Imaging Spectrometer (CHRIS) mounted onboard the Project for On-Board Autonomy (PROBA) spacecraft. This instrument is capable of sampling reflected radiation over the visible and near-infrared (NIR) region of the solar spectrum at a spatial resolution (approx. 17 m) intermediary between sensors traditionally used in land applications (such as Landsat and Satellite Pour l'Observation de la Terre (SPOT), 30 m–50 m) and the latest instruments delivering a nominal resolution of 1 m or less. The spectral anisotropic signature of an Alpine coniferous forest during winter in relation to canopy cover was investigated using the Minnaert-k parameter obtained by inverting the Rahman–Pinty–Verstraete (RPV) model against CHRIS data. Although earlier studies have demonstrated that Minnaert-k can be used to characterize surface heterogeneity at subpixel scale, its spectral dependency has not yet been fully assessed in an imaging spectrometry context. Minnaert-k parameter retrievals across CHRIS bands revealed that a switch from bell-shaped to bowl-shaped anisotropic reflectance patterns occurs when comparing visible to NIR responses. Specifically, the degree of canopy cover and background brightness determine where in the spectral domain this switch in reflectance anisotropy occurs. For a bright snow cover background Minnaert-k values correlated best with canopy cover at the end of the red edge (e.g., around 735 nm). In this spectral region, pixels with medium canopy cover (40%–70%) typically produced bell-shaped anisotropy patterns, while pixels with sparse (<30%) or dense (>70%) canopy covers typically produced bowl-shaped reflectance anisotropy patterns.

Merging the Minnaert-$k$ Parameter With Spectral Unmixing to Map Forest Heterogeneity With CHRIS/PROBA Data

The Compact High Resolution Imaging Spectrometer (CHRIS) mounted onboard the Project for Onboard Autonomy (PROBA) spacecraft is capable of sampling reflected radiation at five viewing angles over the visible and near-infrared regions of the solar spectrum with high spatial resolution. We combined the spectral domain with the angular domain of CHRIS data in order to map the surface heterogeneity of an Alpine coniferous forest during winter. In the spectral domain, linear spectral unmixing of the nadir image resulted in a canopy cover map. In the angular domain, pixelwise inversion of the Rahman-Pinty-Verstraete (RPV) model at a single wavelength at the red edge (722 nm) yielded a map of the Minnaert-k parameter that provided information on surface heterogeneity at a subpixel scale. However, the interpretation of the Minnaert-k parameter is not always straightforward because fully vegetated targets typically produce the same type of reflectance anisotropy as non-vegetated targets. Merging both maps resulted in a forest cover heterogeneity map, which contains more detailed information on canopy heterogeneity at the CHRIS subpixel scale than is possible to realize from a single-source optical data set.

Improvements in Aerosol Optical Depth Estimation Using Multiangle CHRIS/PROBA Images

A method has been developed to estimate aerosol optical depth (AOD) over land surfaces using high spatial resolution, hyperspectral, and multiangle Compact High Resolution Imaging Spectrometer (CHRIS)/Project for On Board Autonomy (PROBA) images. The CHRIS instrument is mounted aboard the PROBA satellite and provides up to 62 bands. The PROBA satellite allows pointing to obtain imagery from five different view angles within a short time interval. The method uses inversion of a coupled surface/atmosphere radiative transfer model and includes a general physical model of angular surface reflectance. An iterative process is used to determine the optimum value providing the best fit of the corrected reflectance values for a number of view angles and wavelengths with those provided by the physical model. This method has previously been demonstrated on data from the Advanced Along-Track Scanning Radiometer and is extended here to the spectral and angular sampling of CHRIS/PROBA. The values obtained from these observations are validated using ground-based sun-photometer measurements. Results from 22 image sets show an rms error of 0.11 in AOD at 550 nm, which is reduced to 0.06 after an automatic screening procedure.

Measuring soil moisture and ocean salinity

The European Space Agency (ESA) lofted two satellites into orbit atop a single launch vehicle on 2 November: the Soil Moisture and Ocean Salinity (SMOS) mission and the second demonstration satellite under ESA's Project for Onboard Autonomy (Proba‐2). SMOS, the first satellite designed to map sea surface salinity and monitor soil moisture on a global scale, features the Microwave Imaging Radiometer Using Aperture Synthesis (MIRAS), an interferometer that connects 69 receivers to measure the temperature of the reflection of Earth's surface in the microwave frequency range.

In-Flight Attitude Perturbation Estimation for Earth-Orbiting Spacecraft

This paper presents four innovative techniques, three Kalman-based and one observer-based, to estimate environmental perturbation torques acting on an Earth-orbiting spacecraft. The Kalman-based techniques all use simple generic models for the state dependence of the perturbation, and for estimating the unknown coefficients included in these generic mathematical formulations. The observer-based technique is developed with the nonlinear disturbance observer theory. The proposed strategies are validated in numerical simulations and are traded-off in terms of estimation accuracy and computational load requirement. Then, the most suitable estimation technique is combined with a batch least square filter algorithm to yield a perturbation estimation system with low computational load, which can be implemented onboard a spacecraft. Finally, the proposed estimation strategy is applied to a realistic gyroless Earth-orbiting spacecraft mission: the European Space Agency’s Project for Onboard Autonomy (PROBA)-2 mission. Ultimately, the selected estimation strategy will be implemented onboard the PROBA-2 spacecraft for in-flight validation. All strategies proposed in this article are general and are applicable to any Earth-orbiting spacecraft.

On the application of the MODTRAN4 atmospheric radiative transfer code to optical remote sensing

The quantification of atmospheric effects on the solar radiation measured by a spaceborne or airborne optical sensor is required for some key tasks in remote sensing, such as atmospheric correction, simulation of realistic scenarios or retrieval of atmospheric parameters. The MODTRAN4 code is an example of state‐of‐the‐art atmospheric radiative transfer code, as it provides very accurate calculations by means of a rigorous mathematical formulation and a very fine spectral resolution. However, the application of MODTRAN4 to remote sensing is not straightforward for the average user for a number of reasons: the provided output parameters do not exactly correspond to those necessary for the construction of the at‐sensor signal by combination with the surface reflectance, an advanced knowledge of radiative transfer theory and atmospheric physics is needed for the understanding of the input parameters and all their possible combinations, and the computation time may be too high for many practical applications. This work is intended to give explicit solutions to those problems. MODTRAN4 has been modified so that the proper atmospheric parameters are calculated and delivered as output. In addition, the most important execution options are investigated, and the compromise between accuracy and computation time is analysed. The performance of the proposed methodology is demonstrated by generating a look‐up table (LUT) enabling fast but accurate radiative transfer calculations for the atmospheric correction of data acquired by the Compact High Resolution Imaging Spectrometer (CHRIS) on board the Project for On‐Board Autonomy (PROBA).

Comparison Between Fractional Vegetation Cover Retrievals from Vegetation Indices and Spectral Mixture Analysis: Case Study of PROBA/CHRIS Data Over an Agricultural Area

In this paper we compare two different methodologies for Fractional Vegetation Cover (FVC) retrieval from Compact High Resolution Imaging Spectrometer (CHRIS) data onboard the European Space Agency (ESA) Project for On-Board Autonomy (PROBA) platform. The first methodology is based on empirical approaches using Vegetation Indices (VIs), in particular the Normalized Difference Vegetation Index (NDVI) and the Variable Atmospherically Resistant Index (VARI). The second methodology is based on the Spectral Mixture Analysis (SMA) technique, in which a Linear Spectral Unmixing model has been considered in order to retrieve the abundance of the different constituent materials within pixel elements, called Endmembers (EMs). These EMs were extracted from the image using three different methods: i) manual extraction using a land cover map, ii) Pixel Purity Index (PPI) and iii) Automated Morphological Endmember Extraction (AMEE). The different methodologies for FVC retrieval were applied to one PROBA/CHRIS image acquired over an agricultural area in Spain, and they were calibrated and tested against in situ measurements of FVC estimated with hemispherical photographs. The results obtained from VIs show that VARI correlates better with FVC than NDVI does, with standard errors of estimation of less than 8% in the case of VARI and less than 13% in the case of NDVI when calibrated using the in situ measurements. The results obtained from the SMA-LSU technique show Root Mean Square Errors (RMSE) below 12% when EMs are extracted from the AMEE method and around 9% when extracted from the PPI method. A RMSE value below 9% was obtained for manual extraction of EMs using a land cover use map.

Hyperspectral and Multiangle CHRIS–PROBA Images for the Generation of Land Cover Maps

The small hyperspectral imager Compact High-Resolution Imaging Spectrometer (CHRIS) is the most important instrument for Earth observation included in the payload of the European Space Agency Third-Part Mission Project for On-Board Autonomy (PROBA)-1 satellite. This instrument has provided dozens of images in several target areas in the world, and a good number of acquisitions are available for the test site of Frascati and Tor Vergata, Italy. This paper reports several results concerning the generation of thematic maps obtained from CHRIS mode-3 imagery. The potential of the use of different configurations for the input vector exploiting multispectral, multiangular, and multitemporal measurements has been investigated, and the results have been evaluated and compared in terms of accuracy in the classification. The core of the decision task has been developed using the neural network methodology. Indeed, this approach is characterized by a particular ease in performing nonlinear mapping of a multidimensional set of inputs into the output one.

Correction of systematic spatial noise in push-broom hyperspectral sensors: application to CHRIS/PROBA images

Hyperspectral remote sensing images are affected by different types of noise. In addition to typical random noise, nonperiodic partially deterministic disturbance patterns generally appear in the data. These patterns, which are intrinsic to the image formation process, are characterized by a high degree of spatial and spectral coherence. We present a new technique that faces the problem of removing the spatially coherent noise known as vertical striping, usually found in images acquired by push-broom sensors. The developed methodology is tested on data acquired by the Compact High Resolution Imaging Spectrometer (CHRIS) onboard the Project for On-board Autonomy (PROBA) orbital platform, which is a typical example of a push-broom instrument exhibiting a relatively high noise component. The proposed correction method is based on the hypothesis that the vertical disturbance presents higher spatial frequencies than the surface radiance. A technique to exclude the contribution of the spatial high frequencies of the surface from the destriping process is introduced. First, the performance of the proposed algorithm is tested on a set of realistic synthetic images with added modeled noise in order to quantify the noise reduction and the noise estimation accuracy. Then, algorithm robustness is tested on more than 350 real CHRIS images from different sites, several acquisition modes (different spatial and spectral resolutions), and covering the full range of possible sensor temperatures. The proposed algorithm is benchmarked against the CHRIS reference algorithm. Results show excellent rejection of the noise pattern with respect to the original CHRIS images, especially improving the removal in those scenes with a natural high contrast. However, some low-frequency components still remain. In addition, the developed correction model captures and corrects the dependency of the noise patterns on sensor temperature, which confirms the robustness of the presented approach.

WHICH PROBA WROTE THE CENTO?

WHICH PROBA WROTE THE CENTO?

Coupled retrieval of aerosol optical thickness, columnar water vapor and surface reflectance maps from ENVISAT/MERIS data over land

An algorithm for the derivation of atmospheric parameters and surface reflectance data from MEdium Resolution Imaging Specrometer Instrument (MERIS) on board ENVIronmental SATellite (ENVISAT) images has been developed. Geo-rectified aerosol optical thickness (AOT), columnar water vapor (CWV) and spectral surface reflectance maps are generated from MERIS Level-1b data over land. The algorithm has been implemented so that AOT, CWV and reflectance products are provided on an operational manner, making no use of ancillary parameters apart from those attached to MERIS products. For this reason, it has been named Self-Contained Atmospheric Parameters Estimation from MERIS data (SCAPE-M). The fundamental basis of the algorithm and applicable error figures are presented in the first part of this paper. In particular, errors of ± 0.03, ± 4% and ± 8% have been estimated for AOT, CWV and surface reflectance retrievals, respectively, by means of a sensitivity analysis based on a synthetic data set simulated under a usual MERIS scene configuration over land targets. The assumption of a fixed aerosol model, the coarse spatial resolution of the AOT product and the neglection of surface reflectance directional effects were also identified as limitations of SCAPE-M. Validation results are detailed in the second part of the paper. Comparison of SCAPE-M AOT retrievals with data from AErosol RObotic NETwork (AERONET) stations showed an average Root Mean Square Error (RMSE) of 0.05, and an average correlation coefficient R 2 of about 0.7–0.8. R 2 values grew up to more than 0.9 in the case of CWV after comparison with the same stations. A good correlation is also found with the MERIS Level-2 ESA CWV product. Retrieved surface reflectance maps have been successfully compared with reflectance data derived from the Compact High Resolution Imaging Spectrometer (CHRIS) on board the PRoject for On-Board Autonomy (PROBA) in the first place. Reflectance retrievals have also been compared with reflectance data derived from MERIS images by the Bremen AErosol Retrieval (BAER) method. A good correlation in the red and near-infrared bands was found, although a considerably higher proportion of pixels was successfully processed by SCAPE-M.

Review of current and planned civilian space hyperspectral sensors for EO

A brief overview is presented of the unique assets that hyperspectral imagery can provide to Earth observation (EO), followed by a review of civilian and dual-use satellite hyperspectral sensors that have been flown, including the European Space Agency (ESA) compact high-resolution imaging spectrometer (CHRIS) on Project for On-Board Autonomy (PROBA), the National Aeronautics and Space Administration (NASA) Hyperion on EO-1, and sensors currently being developed or under consideration, including Germany’s environmental mapping and analysis program (EnMAP) plus some that were planned or built but for various reasons never got to space, e.g., the Naval EarthMap Observer (NEMO) and Warfighter. Additionally, there is information on selected airborne hyperspectral sensors, including the NASA Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). The paper suggests civilian hyperspectral sensors that will possibly be operating in space in the 2008–2015 time period, based on current information regarding their development status.

Refining a hyperspectral and multiangle measurement concept for vegetation structure assessment

The concept of combining multiangle and hyperspectral remote sensing has been developed and utilized in the compact high-resolution imaging spectrometer (CHRIS) satellite observation system onboard the project for on-board autonomy (PROBA) platform developed by the European Space Agency (ESA). Recent studies show that this technology is useful for extracting crop and soil information, and it is very promising for deriving forest structural and biochemical parameters. However, hyperspectral measurements at multiple angles appear to have much redundancy. Therefore, we attempt to refine this measurement concept by testing a new system that acquires hyperspectral signals only in the nadir direction but measures in two additional directions in two spectral bands, namely red and near-infrared (NIR). According to our recent research, we propose that the best two view angles are (i) the hotspot, where the Sun and view directions coincide; and (ii) the darkspot, where the sensor sees the maximum amount of vegetation structural shadows. Through model experiments, we demonstrate that the combination of the hotspot and darkspot reflectances has the strongest signals about the vegetation structure quantified using the foliage clumping index. The 5-Scale model is used in this study to simulate CHRIS data. Very good agreements are shown between modelled and CHRIS-measured spectra at the nadir and off-nadir view angles, except for the largest view angle (+55°), at which the atmospheric correction is uncertain. Furthermore, we successfully demonstrate that the off-nadir hyperspectral simulations could be brought in very close agreement with the CHRIS data once multispectral measurements at the same off-nadir angles are available. In other words, all hyperspectral bands can be closely reconstructed based on the nadir hyperspectral reflectance and off-nadir multispectral reflectance in the red and NIR bands. This is shown for black spruce and aspen forests using the CHRIS data acquired over the Sudbury region in Canada. The results suggest that the multiangle hyperspectral data exhibit much redundancy, and that the multispectral measurements at off-nadir angles in addition to the nadir hyperspectral data would be sufficient to reconstruct hyperspectral signatures at off-nadir angles. This proposed concept could be regarded as a refinement of the existing sensor. Remote sensing data acquired using this new measurement concept would provide the opportunity to analyze simultaneously vegetation structural and biochemical information.

Mapping shrub abundance in desert grasslands using geometric-optical modeling and multi-angle remote sensing with CHRIS/Proba

This work examines the application of a geometric-optical canopy reflectance model to provide measures of woody shrub abundance in desert grasslands at the landscape scale. The approach is through inversion of the non-linear simple geometric model (SGM) against 631 nm multi-angle reflectance data from the Compact High Resolution Imaging Spectrometer (CHRIS) flown on the European Space Agency's Project for On-Board Autonomy (Proba) satellite. Separation of background and upper canopy contributions was effected by a linear scaling of the parameters of the Walthall bidirectional reflectance distribution function model with the weights of a kernel-driven model. The relationship was calibrated against a small number of sample locations with highly contrasting background/upper canopy configurations, before application over an area of about 25 km 2. The results show that with some assumptions, the multi-angle remote sensing signal from CHRIS/Proba can be explained in terms of a combined soil–understory background response and woody shrub cover and exploited to map this important structural attribute of desert grasslands.

A method for the surface reflectance retrieval from PROBA/CHRIS data over land: application to ESA SPARC campaigns

The Compact High Resolution Imaging Spectrometer (CHRIS) onboard the Project for On-Board Autonomy (PROBA) platform system provides the first high spatial resolution hyperspectral/multiangular remote sensing data from a satellite system, what represents a new source of information for Earth Observation purposes. A fully consistent radiative transfer approach is always preferred when dealing with the retrieval of surface reflectance from hyperspectral/multiangular data. However, due to the reported calibration anomalies for CHRIS data, a direct atmospheric correction based on physical radiative transfer modeling is not possible, and the method must somehow compensate for such calibration problems in specific wavelength ranges. A dedicated atmospheric correction algorithm for PROBA/CHRIS data over land is presented in this work. It consists in the combination of radiative transfer and empirical line approaches to atmospheric correction, in order to retrieve surface reflectance images free from both the atmospheric distortion and artifacts due to miscalibration. The atmospheric optical parameters and the updated set of calibration coefficients are obtained jointly in an autonomous process, without the need for any ancillary data. Results from the application of the algorithm to PROBA/CHRIS data from the two European Space Agency SPectra bARrax Campaign (SPARC) held at the Barrax study site (La Mancha, Spain) in 2003 and 2004 are presented in this work, focusing on the validation of the final surface reflectance using in situ measurements acquired simultaneously to PROBA overpasses.

First Results From the PROBA/CHRIS Hyperspectral/Multiangular Satellite System Over Land and Water Targets

The Project for On-Board Autonomy (PROBA) platform developed by the European Space Agency was launched on October 22, 2001. The instrument payload includes the Compact High Resolution Imaging Spectrometer (CHRIS). The coupled system provides high spatial resolution hyperspectral/multiangular data, which represents a new-generation source of information for Earth observation purposes. The first results obtained from the preprocessing (noise removal and geometric/atmospheric correction) of two different datasets, collected over agricultural crops and inland waters, are presented in this letter. In situ measurements are used to assess the quality of the data and to validate the processing algorithms. The capabilities of this new kind of information for an improved analysis of the surface properties are shown, focusing on the advantages that the coupling between the spectral and the angular domains may have in future Earth observation systems.

The PROBA/CHRIS mission: a low-cost smallsat for hyperspectral multiangle observations of the Earth surface and atmosphere

The European Space Agency's Project for On-Board Autonomy is intended to demonstrate a range of innovations in the design, construction, and operation of small satellites. It carries a number of scientific instruments, the most advanced of which is the Compact High-Resolution Imaging Spectrometer. A typical nadir image is 13 km /spl times/13 km in size and has 18 narrow spectral channels at 17-m spatial resolution. When operated at 34-m spatial resolution, the instrument can capture data in 62, almost contiguous, spectral channels. The platform is highly manoeuvrable: along-track pointing allows a given site to be imaged five times during a single overpass, while across-track pointing ensures that the revisit time for a site of interest is less than a week. This unique combination of spectral and angular sampling provides a rich source of data with which to study environmental processes in the atmosphere and at the Earth's surface.

ESA'S ADVANCED MICROSATELLITE MISSION (AMM) STUDY

The Advanced Microsatellite Mission (AMM) study looks at the technology required for the next generation of microsatellites, following on from current microsatellites such as PROBA (Project for On-Board Autonomy). The study aims specifically to address four important aspects: the fraction of satellite mass that is available to the payload, the power available, the thermal environment, and the services provided by the platform. The AMM spacecraft concept has the following features: deployed solar arrays providing over 200W for the payload, propulsion in the form of FEEP (Field Emission Electric Propulsion) for orbit manoeuvres, Ka-band data downlink for downlink rates up to 100 Mbps and a modular and scaleable avionics architecture suitable for a variety of mission needs.