Assessing satellite-derived land product quality for earth system science applications: results from the ceos lpv sub-group

The value of satellite derived land products for science applications and research is dependent upon the known accuracy of the data. CEOS (Committee on Earth Observation Satellites), the space arm of the Group on Earth Observations (GEO), plays a key role in coordinating the land product validation process. The Land Product Validation (LPV) sub-group of the CEOS Working Group on Calibration and Validation (WGCV) aims to address the challenges associated with the validation of global land products. This paper provides an overview of LPV sub-group focus area activities, which cover seven terrestrial Essential Climate Variables (ECVs). The contribution will enhance coordination of the scientific needs of the Earth system communities with global LPV activities

Harmonization of Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) from Sea-Viewing Wide Field-of-View Sensor SeaWiFS) and Medium Resolution Imaging Spectrometer Instrument (MERIS)

This paper describes the combination of terrestrial vegetation observations from two sensors, providing a historical dataset used for an in-depth analysis of the corresponding spatio-temporal patterns. The Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) is an important variable suitable for regional to large-scale monitoring of climate impacts on vegetation. In this work, we create an extensive dataset of FAPAR using a 10-day product at $\sim$1 km resolution from September, 1997, to April, 2012, combining information from two sensors: the NASA/Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and the European Space Agency (ESA)/Medium Resolution Imaging Spectrometer Instrument (MERIS). The proposed methodology reduces the noise, fills the gaps and corrects for the spurious trends in the data, providing a time-consistent coverage of FAPAR. We develop a fast merging method and evaluate its performance over Europe and the Horn of Africa.JRC.H.7-Climate Risk Managemen

Consistent assimilation of MERIS FAPAR and atmospheric CO2 into a terrestrial vegetation model and interactive mission benefit analysis

The terrestrial biosphere is currently a strong sink for anthropogenic CO2 emissions. Through the radiative properties of CO2, the strength of this sink has a direct influence on the radiative budget of the global climate system. The accurate assessment of this sink and its evolution under a changing climate is, hence, paramount for any efficient management strategies of the terrestrial carbon sink to avoid dangerous climate change. Unfortunately, simulations of carbon and water fluxes with terrestrial biosphere models exhibit large uncertainties. A considerable fraction of this uncertainty reflects uncertainty in the parameter values of the process formulations within the models. This paper describes the systematic calibration of the process parameters of a terrestrial biosphere model against two observational data streams: remotely sensed FAPAR (fraction of absorbed photosynthetically active radiation) provided by the MERIS (ESA’s Medium Resolution Imaging Spectrometer) sensor and in situ measurements of atmospheric CO2 provided by the GLOBALVIEW flask sampling network. We use the Carbon Cycle Data Assimilation System (CCDAS) to systematically calibrate some 70 parameters of the terrestrial BETHY (Biosphere Energy Transfer Hydrology) model. The simultaneous assimilation of all observations provides parameter estimates and uncertainty ranges that are consistent with the observational information. In a subsequent step these parameter uncertainties are propagated through the model to uncertainty ranges for predicted carbon fluxes. We demonstrate the consistent assimilation at global scale, where the global MERIS FAPAR product and atmospheric CO2 are used simultaneously. The assimilation improves the match to independent observations. We quantify how MERIS data improve the accuracy of the current and future (net and gross) carbon flux estimates (within and beyond the assimilation period). We further demonstrate the use of an interactive mission benefit analysis tool built around CCDAS to support the design of future space missions. We find that, for long-term averages, the benefit of FAPAR data is most pronounced for hydrological quantities, and moderate for quantities related to carbon fluxes from ecosystems. The benefit for hydrological quantities is highest for semi-arid tropical or sub-tropical regions. Length of mission or sensor resolution is of minor importance.JRC.H.7-Climate Risk Managemen

Envisat's Medium Resolution Imaging Spectrometer (MERIS) Algorithm Theoretical Basis Document: FAPAR and Rectied Channels over Terrestrial Surfaces

This Algorithm Theoretical Basis document (ATBd) describes the Joint Research Center (JRC) procedure used to retrieve information of absorbed photosynthetical radiation by the vegetated terrestrial surfaces from an analysis of the Top Of Atmosphere (TOA) data acquired by MERIS. The code of the proposed algorithm takes the form of a set of several formulae which transform calibrated spectral directional reflectances into a single numerical value. These formulae are designed to extract the green Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) in the plant canopy from the measurements and the rectified channels in the red and near-infrared bands. The methodology described in this document has been optimized to assess the presence on the ground of healthy live green vegetation. The main optimization procedure has been constrained to provide an estimate of FAPAR in the plant canopy, although the outputs are expected to be used in a wide range of applications. This algorithm delivers, in addition to the FAPAR product, the so-called rectified reflectance values in the red and near-infrared spectral bands. These are virtual reflectances largely decontaminated from atmospheric and angular effects. It also provides a categorization of pixel types thanks to a pre-processing identification based on multi-spectral properties. These two virtual reflectances are also computed over bare soils using specific coefficients. This document identifies the sources of input data, outlines the physical principles and mathematical background justifying this approach, describes the proposed algorithm, and lists the assumptions and limitations of this technique.JRC.DDG.H.3-Global environement monitorin

Chemometric Modelling and Remote Sensing of Arable Land Soil Organic Carbon as Mediterranean Land Degradation Indicator - A Case Study in Southern Italy

The application of chemometric models for the quantitative estimation of soil organic matter (SOM) from laboratory reflectance data from samples taken on the regional/national level from Italian sites is explored in Part 1 of this report. In addition, the possibility to transfer the developed models from the spectral resolution of lab/field instrumentation to the one of operational satellite systems has been evaluated, by using the laboratory spectra to simulate the respective soil reflectance signatures of Landsat-TM, MODIS and MERIS. Soil physical and chemical laboratory analyses results were provided by the JRC-IES SOIL action (formerly JRC FP6 MOSES action). The 376 soil samples, used in this study, were collected for previous projects of the IES SOIL action and its partners within a wide range of environmental settings in Italy. Reflectance measurements were obtained on disturbed soil samples using an ASD Field Spec Pro spectro-radiometer. Data transformation methods (standardisation, vector-normalisation and first and second order derivatives) have been applied on the spectral data. The transformed spectral data have been used for the prediction of SOM and carbonate content using the partial least squares regression (PLSR). The results (R2 between 0.57 and 0.8) demonstrate the successful application of reflectance spectroscopy combined with chemometric modelling for the estimation of SOM and carbonate content. The calibration models demonstrated a tolerable stability over a variety of different soil types, which is a positive factor for opening the opportunity to use this methodology for monitoring larger areas. Furthermore it could be shown, that the spectral resolution of the MERIS sensor is sufficient for approximation of the SOC/SOM content from pure soil spectra. Consequently the second part of the study focused on the use of MERIS satellite data for the estimation of soil organic carbon content of bare soils at regional scale. The study concentrated on the Apulia region, where we had high density of available field sampling sites, and on parts of the coastal areas of the Abruzzi region South of Pescara, which are known to be amongst the more critical areas in Italy suffering from land degradation problems and desertification risk. For specific morphological-lithological units simple spectral models, based on soil colour and spectral shape attributes, were built to derive soil organic carbon content. In order to apply these models to MERIS satellite data, a time series of images covering the years 2003 and 2004 were acquired for Southern Italy. Pre-processing of image data aimed at extracting those pixels with negligible vegetation abundance at least at one date of observation per year, i.e. practically showing pure bare soil signatures only, and consisted of: ¿ geometrical co-registration and superposition of images from different acquisition dates ¿ the derivation of minimum vegetation composites for each year applying simple minimum value criteria for MERIS vegetation indices ¿ the determination of soil and vegetation abundance at sub-pixel level based on spectral mixture modelling. ¿ the removal of residual vegetation influence from image spectra Soil colour attributes (soil lightness, R coordinate of R-G-B model) and coefficients of a second order polynomial fitted through the pixel reflectance signatures were derived from the minimum vegetation composites of both years. The spatial distribution of soil organic carbon was estimated for each year within specific morphological-lithological units in the Apulia region. In addition models could be applied to other regions in Southern Italy. Estimation results showed good agreement with independent field data and the pedo-transfer rules based estimations of Jones et. al. (2004, 2005).JRC.H.7-Land management and natural hazard

JRC Experience on the Development of Drought Information Systems

From the definition of drought to its monitoring and assessment, this report summarizes the main steps towards an integrated drought information system. Europe, Africa and Latin America are examples, based on the experience of the JRC, that illustrate the challenges for establishing continental drought observatory initiatives. The document is structured in the following way: first an introduction explains what drought is and gives some examples of its impact in society; secondly the framework for establishing a drought monitoring system is described giving examples on the European Drought Observatory and on on-going activities in Africa and Latin America; thirdly the fundamental data and information for measuring drought is described; finally the setting up of an Integrated Drought Information System is discussed and two recent case studies, on Europe and on the Horn of Africa, are presented to illustrate the concept.JRC.H.7-Climate Risk Managemen

Potential of using remote sensing techniques for global assessment of water footprint of crops

Remote sensing has long been a useful tool in global applications, since it provides physically-based, worldwide, and consistent spatial information. This paper discusses the potential of using these techniques in the research field of water management, particularly for ‘Water Footprint’ (WF) studies. The WF of a crop is defined as the volume of water consumed for its production, where green and blue WF stand for rain and irrigation water usage, respectively. In this paper evapotranspiration, precipitation, water storage, runoff and land use are identified as key variables to potentially be estimated by remote sensing and used for WF assessment. A mass water balance is proposed to calculate the volume of irrigation applied, and green and blue WF are obtained from the green and blue evapotranspiration components. The source of remote sensing data is described and a simplified example is included, which uses evapotranspiration estimates from the geostationary satellite Meteosat 9 and precipitation estimates obtained with the Climatic Prediction Center Morphing Technique (CMORPH). The combination of data in this approach brings several limitations with respect to discrepancies in spatial and temporal resolution and data availability, which are discussed in detail. This work provides new tools for global WF assessment and represents an innovative approach to global irrigation mapping, enabling the estimation of green and blue water use

Scientific and technical challenges in remote sensing of plant canopy reflectance and fluorescence

State-of-the-art optical remote sensing of vegetation canopies is reviewed here to stimulate support from laboratory and field plant research. This overview of recent satellite spectral sensors and the methods used to retrieve remotely quantitative biophysical and biochemical characteristics of vegetation canopies shows that there have been substantial advances in optical remote sensing over the past few decades. Nevertheless, adaptation and transfer of currently available fluorometric methods aboard air- and space-borne platforms can help to eliminate errors and uncertainties in recent remote sensing data interpretation. With this perspective, red and blue-green fluorescence emission as measured in the laboratory and field is reviewed. Remotely sensed plant fluorescence signals have the potential to facilitate a better understanding of vegetation photosynthetic dynamics and primary production on a large scale. The review summarizes several scientific challenges that still need to be resolved to achieve operational fluorescence based remote sensing approache

Measuring and modelling fAPAR for satellite product validation

This thesis presents a comprehensive approach to satellite Fraction of Absorbed Photosynthetically Active Radiation (fAPAR) product validation. This draws on 3D radiative transfer modelling and metrology to characterise the biases associated with a satellite fAPAR algorithm and the uncertainty associated with fAPAR estimates. This extends existing approaches which tend to assume that the in situ measurement technique produces the same fAPAR quantity as the satellite product. The validation procedure involves creating a closure experiment where every aspect of the satellite product definition and its associated assumptions can be tested from the perspective of the in situ and satellite sensors. The intrinsic differences created by the satellite product assumptions are also assessed, where a new reference is created. This is known as the “true” fAPAR since it is perfectly knowable within the context of the radiative transfer model used. Correction factors between the in situ and satellite-derived fAPAR are created to correct data collected over Wytham Woods. The results indicate that the corrections reduce differences of >10% to near zero. However, the uncertainty estimates for the satellite-derived fAPAR show that it does not meet the requirements given by Global Climate Observing System (GCOS) (≤(10% or 0.05)). The wider implications of the retrieved uncertainties are also presented showing that it is unlikely that the GCOS requirements associated with downstream applications that use satellite fAPAR can be met currently. This work represents an important step forward in the validation of satellitederived fAPAR because it is the first time that the absence of satellite and in situ data uncertainty and traceability, and satellite product definition differences have been addressed. This paves the way for the improvement of satellite fAPAR products because their uncertainties can now be quantified effectively and their validation conducted fairly, meaning there is now a benchmark to base improvements on

Evaluation of Sentinel-3A and Sentinel-3B ocean land colour instrument green instantaneous fraction of absorbed photosynthetically active radiation

This article presents the evaluation of the Copernicus Sentinel-3 Ocean Land Colour Instrument (OLCI) operational terrestrial products corresponding to the green instantaneous Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) and its associated rectified channels. These products are estimated using OLCI spectral measurements acquired at the top of the atmosphere by a physically-based approach and are available operationally at full (300 m) and reduced (1.2 km) spatial resolution daily. The evaluation of the quality of the FAPAR OLCI values was based on the availability of data acquired over several years by Sentinel-3A (S3A) and Sentinel-3B (S3B). The evaluation exercise consisted of several stages: first, an overall comparison of the two S3 platform products was carried out during the tandem phase; second, comparison with an FAPAR climatology derived from the Medium Resolution Imaging Spectrometer (MERIS) provided information on the seasonality of various types of land cover. Then, direct comparisons were made with the same type of FAPAR products retrieved from two sensors, the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Sentinel-2 (S2) Multispectral Instrument (MSI), and with several ground-based estimates. In addition, an analysis of the efficiency of the retrieval algorithm with 3D radiative transfer simulations was performed. The results indicated that the consistency between daily and monthly S3A and S3B on a global scale was very good during the tandem phase (RMSD = 0.01 and a correlation R2 of 0.99 with a bias of 0.003); we found an agreement with a correlation of 0.95 and 0.93 (RMSD = 0.07 and 0.09) with JRC FAPAR S2 and JRC FAPAR MODIS, respectively. Compatibility with the ground-based data was between 0.056 and 0.24 in term of RMSD depending on the type of vegetation with an overall R2 of 0.89. Immler diagrams demonstrate that their variances were lower than the total uncertainties. The quality assurance using 3D radiative transfer model has shown that the apparent performance of the algorithm depends strongly on the type of in-situ measurement and canopy type