Development of atmospheric correction algorithms for very high spectral and spatial resolution images: application to SEOSAT and the FLEX/Sentinel-3 missions

Advanced high spectral and spatial resolution imager spectrometers on board new generation of Earth Observation missions bring new exciting opportunities to the remote sensing scientific community. However, this progress goes hand in hand with new challenges. The exploitation of data acquired from these family of advanced instruments requires new processing algorithms able to deal with these particularities. As part of this evolution, atmospheric correction algorithms - a mandatory processing step applied prior to the Earth surface reflectance data exploitation - must be adapted or reformulated, thereby paying special attention to how atmospheric effects disturb the acquired signal in the spectral and spatial domains. For these reasons, this Thesis aims to develop new atmospheric correction strategies to be applied over very high spectral and spatial resolution data. Following this goal, this Thesis was conducted in the framework of two missions during their development phase: (1) the FLEX/Sentinel–3 tandem space mission (for high spectral resolution data) and, (2) the Ingenio/SEOsat space mission (for high spatial resolution data). In the context of these missions, an additional challenge is introduced when acquiring proximal remote sensing data for their validation. This is especially relevant for the FLEX mission, which is dedicated to monitor the weak Solar Induced Chlorophyll Fluorescence (SIF) signal. Following this motivation, the main objectives of this Thesis are threefold: The first objective involved to analyse atmospheric effects on the Ingenio/SEOsat high spatial and low spectral resolution satellite mission and to propose a new atmospheric correction strategy. This strategy was called Hybrid and combines: (1) a per–pixel atmospheric radiative transfer model inversion technique making use of auxiliary data to characterize the atmospheric state, followed by (2) an image deconvolution technique modelling the atmospheric MTF to correct for atmospheric spatial effects. The Hybrid method was applied to Sentinel–2 data, particularly over bands acquired at 10 m resolution due to its similarities with the Ingenio/SEOsat mission. The second objective involved to define a novel atmospheric correction strategy for the FLEX/Sentinel-3 tandem mission. The proposed strategy is a two-steps method where information from Sentinel-3 instruments, OLCI and SLSTR, is first used in synergy to characterize the aerosol and water vapour presence. The high spectral resolution of FLEX data is subsequently exploited to refine the previously aerosol characterization. As part of this objective, the suitability of all the approximations assumed in the formulation proposed for the atmospheric inversion of FLEX data was validated against the FLEX mission requirements. The third objective involved to develop a strategy that deals with the atmospheric correction of very high spectral and spatial resolution data acquired at lower atmospheric scales such as Unmanned Aerial Vehicles or systems mounted on towers. In this Thesis, it was demonstrated that even when acquiring the signal at proximal remote sensing scale, i.e., few meters from the target oxygen absorption must be compensated to properly estimate SIF within these spectral regions. For this reason, a strategy to compensate for the oxygen absorption while properly dealing with the instrumental spectral response function convolution was presented and tested using simulated data. Altogether, this work identified challenges associated to atmospheric correction when applying to high spatial and especially to very high spectral resolution data. In this Thesis, adequate formulations have been developed to resolve these difficulties, and successful methodologies have been designed for the particular cases of SEOsat (high spatial resolution) and FLEX (high spectral resolution); two future remote sensing space missions that will be launched in the forthcoming years

Towards the quantitative and physically-based interpretation of solar-induced vegetation fluorescence retrieved from global imaging

Due to emerging high spectral resolution, remote sensing techniques and ongoing developments to retrieve the spectrally resolved vegetation fluorescence spectrum from several scales, the light reactions of photosynthesis are receiving a boost of attention for the monitoring of the Earth's carbon balance. Sensor-retrieved vegetation fluorescence (from leaf, tower, airborne or satellite scale) originating from the excited antenna chlorophyll a molecule has become a new quantitative biophysical vegetation parameter retrievable from space using global imaging techniques. However, to retrieve the actual quantum efficiencies, and hence a true photosynthetic status of the observed vegetation, all signal distortions must be accounted for, and a high-precision true vegetation reflectance must be resolved. ESA's upcoming Fluorescence Explorer aims to deliver such novel products thanks to technological and instrumental advances, and by sophisticated approaches that will enable a deeper understanding of the mechanics of energy transfer underlying the photosynthetic process in plant canopies and ecosystems

The data concept behind the data: From metadata models and labelling schemes towards a generic spectral library

Spectral libraries play a major role in imaging spectroscopy. They are commonly used to store end-member and spectrally pure material spectra, which are primarily used for mapping or unmixing purposes. However, the development of spectral libraries is time consuming and usually sensor and site dependent. Spectral libraries are therefore often developed, used and tailored only for a specific case study and only for one sensor. Multi-sensor and multi-site use of spectral libraries is difficult and requires technical effort for adaptation, transformation, and data harmonization steps. Especially the huge amount of urban material specifications and its spectral variations hamper the setup of a complete spectral library consisting of all available urban material spectra. By a combined use of different urban spectral libraries, besides the improvement of spectral inter- and intra-class variability, missing material spectra could be considered with respect to a multi-sensor/ -site use. Publicly available spectral libraries mostly lack the metadata information that is essential for describing spectra acquisition and sampling background, and can serve to some extent as a measure of quality and reliability of the spectra and the entire library itself. In the GenLib project, a concept for a generic, multi-site and multi-sensor usable spectral library for image spectra on the urban focus was developed. This presentation will introduce a 1) unified, easy-to-understand hierarchical labeling scheme combined with 2) a comprehensive metadata concept that is 3) implemented in the SPECCHIO spectral information system to promote the setup and usability of a generic urban spectral library (GUSL). The labelling scheme was developed to ensure the translation of individual spectral libraries with their own labelling schemes and their usually varying level of details into the GUSL framework. It is based on a modified version of the EAGLE classification concept by combining land use, land cover, land characteristics and spectral characteristics. The metadata concept consists of 59 mandatory and optional attributes that are intended to specify the spatial context, spectral library information, references, accessibility, calibration, preprocessing steps, and spectra specific information describing library spectra implemented in the GUSL. It was developed on the basis of existing metadata concepts and was subject of an expert survey. The metadata concept and the labelling scheme are implemented in the spectral information system SPECCHIO, which is used for sharing and holding GUSL spectra. It allows easy implementation of spectra as well as their specification with the proposed metadata information to extend the GUSL. Therefore, the proposed data model represents a first fundamental step towards a generic usable and continuously expandable spectral library for urban areas. The metadata concept and the labelling scheme also build the basis for the necessary adaptation and transformation steps of the GUSL in order to use it entirely or in excerpts for further multi-site and multi-sensor applications

Study of the speckle noise effects over the eigen decomposition of polarimetric SAR data: a review

This paper is focused on considering the effects of speckle noise on the eigen decomposition of the co- herency matrix. Based on a perturbation analysis of the matrix, it is possible to obtain an analytical expression for the mean value of the eigenvalues and the eigenvectors, as well as for the Entropy, the Anisotroopy and the dif- ferent a angles. The analytical expressions are compared against simulated polarimetric SAR data, demonstrating the correctness of the different expressions.Peer ReviewedPostprint (published version