Surface topography and mixed-pixel effects on the simulated L-band brightness temperatures.

The impact of topography and mixed pixels on L-band radiometric observations over land needs to be quantified to improve the accuracy of soil moisture retrievals. For this purpose, a series of simulations has been performed with an improved version of the Soil Moisture and Ocean Salinity (SMOS) End-to-End Performance Simulator (SEPS). The brightness temperature (TB) generator of SEPS has been modified to include a 100-m-resolution land cover map and a 30-m-resolution digital elevation map of Catalonia (northeast of Spain). This highresolution TB generator allows the assessment of the errors in soil moisture retrieval algorithms due to limited spatial resolution and provides a basis for the development of pixel disaggregation techniques. Variation of the local incidence angle, shadowing, and atmospheric effects (up- and downwelling radiation) due to surface topography has been analyzed. THE AVAILABILITY of high-resolution brightness temperature (TB) maps at L-band is crucial to analyze important issues dealing with bare and vegetation-covered land emission and to develop inversion algorithms in preparation for real Soil Moisture and Ocean Salinity (SMOS) mission data. Mixed-pixel, coastlines, shadowing, and topography effects on the measured brightness temperatures need further study, but the lack of global geophysical data at sufficient temporal and spatial resolution and the large amount of data involved in the generation of high-resolution TB maps on a global basis complicate the issue. In fact, in spite of the existence of global digital elevation models with sufficient spatial resolution, accurate land cover data do not exist for most parts of the world. To address these issues, a series of simulations has been performed with an improved version of the SMOS End-to-End Performance Simulator (SEPS) [1], [2], in which, to date, all points on Earth have been assumed to be at sea level. The study has been done over the region of Catalonia, on the northeastern coast of Spain, because of its many different land cover types, topography, and the presence of a coastline. A 30-m-resolution digital elevation map [3] and a 100-m-resolution land coverage map of Catalonia [4] have been used as inputs, and SEPS has been conveniently modified to generate high-resolution TB maps of this area. A variety of soil and land cover types (crops, bushes, marshes, etc.) have been parameterized using the values obtained from field experiments and literature [5]–[10], [12].The impact of topography and mixed pixels on L-band radiometric observations over land needs to be quantified to improve the accuracy of soil moisture retrievals. For this purpose, a series of simulations has been performed with an improved version of the soil moisture and ocean salinity (SMOS) end-to-end performance simulator (SEPS). The brightness temperature generator of SEPS has been modified to include a 100-m-resolution land cover map and a 30-m-resolution digital elevation map of Catalonia (northeast of Spain). This high-resolution generator allows the assessment of the errors in soil moisture retrieval algorithms due to limited spatial resolution and provides a basis for the development of pixel disaggregation techniques. Variation of the local incidence angle, shadowing, and atmospheric effects (up- and downwelling radiation) due to surface topography has been analyzed. Results are compared to brightness temperatures that are computed under the assumption of an ellipsoidal Earth

Simulation of SMAP and AMSR2 observations and estimation of multi-frequency vegetation optical depth using a discrete scattering model in the Tibetan grassland

Passive microwave observation at multiple frequencies has received increasing research interests due to its capability to provide comprehensive information of land surface properties. This paper contributes to the simulation of land surface emission and estimation of vegetation optical depth (VOD) at multiple frequencies using a discrete scattering model with a single set of model parameter values. Validity of the Tor Vergata (TVG) discrete scattering model in simultaneously reproducing the Soil Moisture Active Passive (SMAP) L-band (1.4 GHz) and Advanced Microwave Scanning Radiometer 2 (AMSR2) C- (6.925 GHz) and X-band (10.7 GHz) observations over the Tibetan grassland ecosystem is evaluated. Frequency-specific and multi-frequency calibration strategies are implemented to find the suitable set of model parameter values and to isolate the impact of frequency on parameter values. On this basis, the calibrated TVG model is further used to estimate the VOD, and to investigate the impact of microwave frequency and observation angle on the emission simulations and VOD parameterization. The results show that both frequency-specific and multi-frequency calibration strategies achieve comparable and reasonable simulations of SMAP and AMSR2 observations, confirming the feasibility of using an identical physically-based model (i.e. the calibrated TVG model) to simulate multi-frequency land emission driven by a single set of model parameter values. As such, the dependence of emission components and VOD on frequency can be elaborated after isolating the impact of frequency on parameter values. The VOD values derived from the TVG simulations generally increase with increasing frequency and can be linearly correlated to the LAI variations, while current satellite-based retrievals have almost the same magnitude at the L-, C-, and X-band. The explanation for this can be that the retrieved VOD is different from the theoretical definition. Sensitivity test performed using the calibrated TVG model further shows that polarization-dependence of VOD becomes more apparent with the increasing observation angle and frequency. New parameterization has thus been developed to characterize the dependence of VOD on the frequency, observation angle, and polarization for grassland based on the results of sensitivity test. This study may provide new insights in improving model of land emission and retrievals of SM and VOD with physical interpretability based on multi-frequency satellite observations.</p

Characterizing the dependence of vegetation model parameters on crop structure, incidence angle, and polarization at L-band

International audienceTo retrieve soil moisture over vegetation-covered areas from microwave radiometry, it is necessary to account for vegetation effects. At L-band, many retrieval approaches are based on a simple model that relies on two vegetation parameters: the optical depth (τ) and the single-scattering albedo (ω). When the retrievals are based on multiconfiguration measurements, it is necessary to take into account the dependence of τ and ω on the system configuration, in terms of incidence angle and polarization. In this paper, this dependence was investigated for several crop types (corn, soybean, wheat, grass, and alfalfa) based on L-band experimental datasets. The results should be useful for developing more accurate forward modeling and retrieval methods over mixed pixels including a variety of vegetation types

Modeling L-Band Microwave Emission From Soil-Vegetation System

During a field campaign covering the 2002 corn growing season, a dual polarized tower mounted L-band (1.4 GHz) radiometer (LRAD) provided brightness temperature (T¬B) measurements at preset intervals, incidence and azimuth angles. These radiometer measurements were supported by an extensive characterization of land surface variables including soil moisture, soil temperature, vegetation biomass, and surface roughness. During the period from May 22, 2002 to August 30, 2002 a range of vegetation water content (W) of 0.0 to 4.3 kg m-2, ten days of radiometer and ground measurements were available. Using this data set, the effects of corn vegetation on surface emissions are investigated by means of a semi-empirical radiative transfer model. Additionally, the impact of roughness on the surface emission is quantified using T¬B measurements over bare soil conditions. Subsequently, the estimated roughness parameters, ground measurements and horizontally (H)-polarized TB are employed to invert the H-polarized transmissivity (γh) for the monitored corn growing season

Estimation de l’humidité du sol en milieu agricole par combinaison des données polarimétriques radar en bande C et des micro-ondes passives en bande L

L’humidité du sol a un rôle majeur dans la régulation des éléments du climat (précipitations, température, H2O atmosphérique) et du cycle de l’eau. Pour étudier l’humidité du sol à l’échelle globale, la télédétection spatiale micro-onde présente un fort potentiel. Dans le cas du satellite Soil Moisture Active Passive (SMAP), les méthodes initialement développées permettaient d’obtenir trois produits d’humidité du sol : actif, passif et actif-passif avec une résolution spatiale fine de 3 km, grossière de 40 km et moyenne de 9 km, respectivement. Cependant, six mois après le lancement du satellite, son radar s’est détérioré, empêchant SMAP de générer des produits d’humidité du sol à fine et moyenne résolution spatiale. Dès lors, des équipes de recherche ont étudié la possibilité de combiner des mesures micro-ondes actives et passives avec des capteurs installés sur des plateformes différentes et opérant à des fréquences différentes. Ce projet propose une approche de combinaison des mesures micro-ondes actives et passives de satellites différents pour estimer l’humidité du sol à 1 km de résolution spatiale sur le site de la campagne terrain SMAPVEX16-MB, situé dans une zone agricole du Manitoba. La méthode est basée sur une désagrégation de la température de brillance (TB) de SMAP, de 40 km à 1 km de résolution spatiale, en utilisant les données polarimétriques en bande C de Radarsat-2 corrigées de l’effet de la végétation (la contribution de surface : Ps), plus sensible à l’humidité du sol. La contribution de surface (Ps) est obtenue en appliquant la décomposition polarimétrique de Freeman-Durden. Le résultat de la désagrégation est une température de brillance à 1 km de résolution spatiale, qui est ensuite utilisée dans l’algorithme du Single Chanel Algorithm pour estimer l’humidité du sol à 1 km de résolution spatiale. En ce qui concerne l’estimation de l’humidité du sol, pour tous les dix champs considérés, nous avons obtenu les meilleurs résultats en utilisant les TBV : coefficients de corrélation de Pearson (R) compris entre 0,42 et 0,86, p-values comprises entre 0,003 et 0,27 et erreurs quadratiques moyennes (RMSE) comprises entre 0,02 m3.m -3 et 0,05 m3.m -3. Lorsque nous utilisons les TBH pour estimer l’humidité du sol, nous obtenons : R compris entre 0,39 et 0,75, p-values comprises entre 0,02 et 0,30 et RMSE comprises entre 0,02 m3.m -3 et 0,15 m3.m -3. Ce projet nous a permis d’implémenter une méthode innovatrice de combinaison de données micro-ondes actives et passives pour l’étude de l’humidité du sol. L’approche proposée utilise les Ps au lieu de σ^0 contrairement à la plupart des méthodes que l’on trouve dans la littérature depuis la détérioration du radar de SMAP.Abstract : Soil moisture plays a major role in the regulation of climate elements (precipitation, temperature, atmospheric H2O) and water balance. To study the soil moisture at a global scale, spaceborne microwave remote sensing has a great potential. In the case of the Soil Moisture Active Passive (SMAP) satellite, the initially developed methods provided three soil moisture products : active, passive and active-passive with a fine spatial resolution of 3 km, coarse 40 km and medium 9 km, respectively. However, six months after the launch of the satellite, its radar failed, preventing SMAP from generating soil moisture products at fine (3 km) and medium (9 km) spatial resolutions. Since then, research teams have studied the possibility of combining active and passive measurements with sensors installed on different platforms and operating at different frequencies. This project proposes a combined approach of active and passive microwave measurements of different satellites to estimate soil moisture at 1 km spatial resolution at the SMAPVEX16-MB field campaign site, located in an agricultural area of Manitoba. The method is based on a disaggregation of the brightness temperature (TB) of SMAP, from 40 km to 1 km spatial resolution, using Radarsat-2 polarimetric C-band data corrected for vegetation effects. These are represented by the surface contribution (Ps), which is more sensitive to soil moisture and extracted by applying the polarimetric decomposition of Freeman-Durden (Freeman and Durden, 1998) to Radarsat-2 data. Regarding the estimation of the soil moisture, for all the ten fields considered, we obtained the best results by using TBV: (Pearson correlation R between 0.42 and 0.86, p-values between 0.003 and 0.27, and root mean square errors (RMSE) between 0.02 m3.m -3 and 0.05 m3.m -3). When TBH was used to estimate soil moisture, the results were less accurate (R between 0.39 and 0.75 p-values between 0.02 and 0.30; and RMSE between 0.02 m3.m -3 and 0.15 m3.m -3). This project allowed us to implement an innovative methodology using Ps instead of 0 in contrast to most of the approaches combining active and passive microwave data for soil moisture estimation, since the failure of the radar onboard SMAP

Climate Change Impacts on Agriculture in Europe

COST Action 734 was launched thanks to the coordinated activity of 29 EU countries. The main objective of the Action was the evaluation of impacts from climate change and variability on agriculture for various European areas. Secondary objectives were: collection and review of existing agroclimatic indices and simulation models, to assess hazard impacts on European agricultural areas; to apply climate scenarios for the next few decades; the definition of harmonised criteria to evaluate the impacts of climate change and variability on agriculture; the definition of warning systems guidelines. Based on the result, possible actions (specific recommendations, suggestions, warning systems) were elaborated and proposed to the end-users, depending on their needs

Assimilation des données SMOS dans un modèle des surfaces continentales : mise en œuvre et évaluation sur la France

Assimiler l'humidité superficielle du sol (SSM) dans un modèle de surface améliore la modélisation du contenu en eau du sol. La télédétection est un outils indispensable pour suivre l'évolution de cette variable. SMOS, lancé en Novembre 2009, est le premier satellite dédié à l'étude de l'humidité du sol. Les premières données SMOS ont été comparées aux données ASCAT sur la France. Les données ASCAT se corrèlent mieux aux observations in situ et aux SSM simulées que les données SMOS pendant l'année 2010. Sur le sol nu du site de SMOSREX (2003-2005), les SSM mesurés ont été assimilées dans une nouvelle version multi-couches du modèle Interaction entre le Sol, la Biosphère et l'Atmosphère (ISBA). Un Filtre de Kalman Etendu Simplifié (SEKF) a été utilisé pour analyser le profil d'eau du sol dans les 11 couches de la version multi-couches du modèle de surface (ISBA-DF). Pendant les périodes sèches, les corrections impactent les 15 premiers centimètres du sol alors que pendant les périodes humides, des corrections moins intenses affectent l'ensemble de la colonne de sol. Afin de préparer l'assimilation des températures de brillance (TB), des TB ont été simulées par couplage entre ISBA-DF et un modèle d'émission micro-ondes (CMEM). Avec ISBA-DF, il est préférable de modéliser les TB en utilisant l'approche de Wilheit pour le calcul de l'émissivité de surface lisse et de prendre en compte l'impact des variations de SSM dans le calcul de la rugosité. Finalement, les TB de SMOSREX ont été assimilées dans ISBA-DF. Considérer CMEM comme opérateur d'observations dans le SEKF permet d'obtenir un état analysé proche de celui obtenu lors de l'assimilation des SSM dans ISBA-DF.Assimilating surface soil moisture (SSM) in a land surface model permits a better monitoring of the soil water content. Remote sensing is an indispensable tool for monitoring the evolution of SSM, both spatially and temporally. SMOS was launched in November 2009 and it is the first satellite specifically dedicated to SSM mapping over continents. A comparison of the first SMOS data with ASCAT over France showed that the ASCAT product was better correlated with in situ SSM observations and with SSM simulations for the year 2010. Over bare soil plot of SMOSREX (2003-2005), in situ SSM were assimilated into a new multi-layer version of the soil module of the Interaction between the Soil, Biosphere, Atmosphere (ISBA) land surface model. A simplified Extended Kalman Filter was used to analyze 11 soil layers of the ISBA multi-layer version (ISBA-DF). For dry periods, corrections affected a shallow 0-15 cm top soil layer. For wet period, weaker corrections were applied for the entire column. To prepare the assimilation of the TB, the TB were produced by coupling ISBA-DF with a microwave emission model (CMEM). With ISBA-DF, computing TB using the Wilheit smooth surface emissivity and taking into account an impact of SSM on soil roughness is recommended. Finally, the SMOSREX TB observations were assimilated by ISBA-DF. Considering CMEM as an observation operator provided a SSM and total soil water content analysis similar to the analysis obtained by assimilating direct SSM observations in ISBA-DF

Contributions to land, sea, and sea ice remote sensing using GNSS-reflectometry

This PhD thesis researches the use of passive remote sensing techniques using signals transmitted from the navigation satellites (GNSS) in order to retrieve different geophysical parameters. The thesis consists of two different parts without taking into account the introduction, the state of the art and the conclusions. The first part analyzes the Interference Pattern Technique (IPT), which was previously used in another PhD thesis, and proposes some key improvements. First, the addition of horizontal polarization to the existing vertical polarization is proposed. Then, the retrieval of soil moisture is studied using the horizontal polarization only and combining both polarizations to correct for the surface roughness effects. It is also demonstrated that the phase difference between the two interference patterns is directly related to soil moisture content. A field campaign was conducted in Australia to test empirically all the theoretical developments and algorithms. Secondly, the possibility of measuring Significant Wave Height (SWH) and Mean Sea Surface Level (MSSL) using the IPT is studied. A three month field campaign over coastal sea is devoted to that study. The SWH retrieval is a new estimation algorithm based on measuring the point where the interference pattern loses coherence. The MSSL retrieval is based on the estimation of the IPT oscillation frequency, testing different spectral estimators to improve the accuracy. Since the IPT is limited in coverage due to its static requirements, the research conducted in this thesis migrated to scatterometric GNSS-R techniques. The main goal that migration was to increase coverage of the different GNSS-R instruments. Therefore, the second part of this thesis analyzes the applicability of a scatterometric technique from different platforms: ground-based (mobile and fixed), airborne, and spaceborne. The ground-based still platforms have allowed to develop a soil moisture retrieval algorithm. The ground-based moving platforms have extended the validity of that algorithm. Airborne platforms have been used to study the reflected electric field statistics when the surface reflecting surface is varying (smooth or rough land, and sea). They have also been used to develop different algorithms to measure the coherent and incoherent scattered components depending on the data structure (real-data or complex data). Coherent reflectivity measured from airborne platforms has been compared to other techniques such microwave radiometry, which is highly used in the soil moisture retrieval from spaceborne sensors, and other sensors using optical, multispectral and thermal frequency bands. These relationships between microwave radiometry and GNSS-R measurements suggests the potential synergy of both techniques. A sea ice detection algorithm is also developed using scatterometric GNSS-R data from the UK TDS-1 mission. This algorithm is based on measuring the degree of coherence of the reflected waveform. Finally, a field campaign was conducted to study the effect of vegetation on the GNSS signals that pass through it in order to take into account and correct the effect of vegetation in the GNSS-R data and in the soil moisture retrieval algorithms.Aquesta tesi doctoral aprofundeix en el coneixement de les tècniques de teledetecció passives utilitzant senyals emesos pels satèl·lits de navegació (GNSS) amb l'objectiu de recuperar diferents paràmetres geofísics del terreny. La tesi conté dues parts ben diferenciades a banda de la introducció, estat de l'art i conclusions. La primera part analitza la tècnica coneguda com a patró d'interferències, utilitzada prèviament en una altra tesi doctoral, i proposa certes millores per la seva aplicabilitat. En primer lloc es decideix afegir polarització horitzontal a la ja existent polarització vertical, i s'estudia la recuperació d'humitat del sòl utilitzant només polarització horitzontal i combinant les dues polaritzacions per corregir els efectes de la rugositat del terreny. A continuació es demostra que la mesura de desfasament entre els dos patrons d'interferència està directament relacionada amb la humitat del terreny. Es va realitzar una campanya de mesures a Austràlia per provar empíricament tots els desenvolupaments teòrics i algorismes proposats. En segon lloc s'analitza l'aplicabilitat del patró d'interferències en la mesura de l'altura de les onades (SWH) i del nivell del mar (MSSL), tots dos de forma precisa. L'estimació de l'alçada de les onades és un procés totalment nou basat en mesurar el punt on el patró d'interferències perd la coherència. L'estimació del nivell del mar es basa en l'anàlisi espectral del patró d'interferències provant diferents estimadors espectrals. Atès que la tècnica del patró d'interferència està limitada en cobertura per les seves característiques estàtiques, la investigació duta a terme en aquesta tesi doctoral va migrar cap a tècniques GNSS-R escateromètriques. El principal objectiu a assolir va ser el d'augmentar la cobertura dels diferents instruments GNSS-R de mesura. En conseqüència, la segona part d'aquesta tesi analitza l'aplicabilitat d'aquestes tècniques des de diferents plataformes terrestres (mòbils i fixes), aerotransportades i satèl·lit. Les plataformes terrestres fixes han permès derivar algoritmes de recuperació d'humitat i les mòbils estendre la validació d'aquests. Les plataformes aerotransportades s'han utilitzat per mirar l'estadística del camp elèctric reflectit quan la superfície on es reflecteixen els senyals GNSS va variant (terra plana o terra rugosa, i mar). També han servit per desenvolupar diferents algorismes amb l'objectiu de determinar les components coherent i incoherent del senyal reflectit. De la mateixa manera, dades de reflectivitat coherent mesurades des d'aquestes plataformes han estat comparades amb altres tècniques de teledetecció passiva com la radiometria de microones, altament utilitzada en la mesura d'humitat de terreny, i altres sensors òptics, multi-espectrals, i tèrmics. Aquests resultats han permès suggerir la possible sinergia de dades d'ambdues tecnologies. Un algorisme per detectar la presència de gel sobre el mar també ha estat desenvolupat mitjançant l'ús de dades GNSS-R escateromètriques satel·litals de la missió UK TDS-1. Aquest algorisme es basa en mesurar el grau de coherència de la forma d'ona reflectida. Finalment, s'ha realitzat un estudi de l'efecte de la vegetació en els senyals GNSS que la travessen, per tal de poder corregir aquest efecte en els algoritmes de recuperació d'humitat del terreny