Review of the CALIMAS Team Contributions to European Space Agency's Soil Moisture and Ocean Salinity Mission Calibration and Validation

Camps, Adriano ... et al.-- 38 pages, 22 figuresThis work summarizes the activities carried out by the SMOS (Soil Moisture and Ocean Salinity) Barcelona Expert Center (SMOS-BEC) team in conjunction with the CIALE/Universidad de Salamanca team, within the framework of the European Space Agency (ESA) CALIMAS project in preparation for the SMOS mission and during its first year of operation. Under these activities several studies were performed, ranging from Level 1 (calibration and image reconstruction) to Level 4 (land pixel disaggregation techniques, by means of data fusion with higher resolution data from optical/infrared sensors). Validation of SMOS salinity products by means of surface drifters developed ad-hoc, and soil moisture products over the REMEDHUS site (Zamora, Spain) are also presented. Results of other preparatory activities carried out to improve the performance of eventual SMOS follow-on missions are presented, including GNSS-R to infer the sea state correction needed for improved ocean salinity retrievals and land surface parameters. Results from CALIMAS show a satisfactory performance of the MIRAS instrument, the accuracy and efficiency of the algorithms implemented in the ground data processors, and explore the limits of spatial resolution of soil moisture products using data fusion, as well as the feasibility of GNSS-R techniques for sea state determination and soil moisture monitoringThis work has been performed under research grants TEC2005-06863-C02-01/TCM, ESP2005-06823-C05, ESP2007-65667-C04, AYA2008-05906-C02-01/ESP and AYA2010-22062-C05 from the Spanish Ministry of Science and Innovation, and a EURYI 2004 award from the European Science FoundationPeer Reviewe

Contribution to advanced sensor development for passive imaging of the Earth

This work has been formally undertaken within the frame of the scholarship number BES-2012-053917 of 1 December 2012, by the "Secretario de Estado de Investigación del Ministerio de Economía y Competitividad" related to the program "Formación de Personal Investigador (FPI)". The scholarship is related to the research project at the Universitat Politècnica de Catalunya (UPC) number TEC2011-25865. In a more general scope, this thesis is related to the Remote Sensing Laboratory (Signal Theory & Communication Department, UPC) on-going activities, within the SMOS (Soil Moisture and Ocean Salinity) mission by the European Space Agency (ESA). These activities have been organized to provide original advances in the following four main topics: 1) SMOS calibration and performance. Since the launch of the instrument in 2009, SMOS imaging has been performing exclusively in co-polar mode. However, SMOS measurements are fully polarimetric. This feature was not operationally exploited due to the large errors yielded by full-pol images. In this context my work was addressed to support better characterization of the antenna. Based on the idea that SMOS polarization mode was recently implemented using Full-pol measurements, the so-called relative phases have been recomputed by using co-polar and cross-polar measurements. SMOS moderate Side Lobe Level (SLL) is caused by the limited coverage of the measured visibility samples in the frequency domain, so another objective of this work has been devoted to assess the impact of calibration errors into SMOS side lobes level (SLL). The main objective on this topic has been to reproduce by simulation SMOS measured side-lobe levels (SLL) by adding errors to a point source response, in order to identify the dominant source of error. During commissioning phase it was detected that SMOS heater system were introducing small and random sporadic PMS offset steps (jumps) in several units. Another work during this thesis has been devoted to mitigate those PMS jumps by trimming calibration date from single LICEF averaged TA jumps over the ocean. 2) SMOS spatial bias assessment. SMOS measurements still have mathematical image reconstruction errors that must be properly assessed. The aim of this work is to focus on the so-called "floor error", defined in an error free end-to-end image reconstruction simulation. In order to reduce this error, different inversion approaches have been implemented and tested, as the so-called Gibbs 2 approach 3) SMOS improved imaging. One of the problems of most concern within the SMOS mission is related to the so-called "land-sea contamination" (LSC), an artificial increase of ocean brightness temperature close to land masses. Therefore, a systematic assessment has been performed in this thesis in order to understand and mitigate this artifact. This subject is related to one of the main original outcomes of the thesis, since it has a relevant impact on the quality of SMOS imaging. The LSC mitigation technique developed during the work of the thesis has been presented and validated by different methods. 4) SMOS follow-on missions advanced configurations. This work is devoted to assess the impact of instrumental errors on the radiometric accuracy (pixel bias) of one of the selected array configurations of the so-called Super-MIRAS instrument. The aim of this work has been focused on the assessment of different array geometries and instrument architectures of future L-band synthetic aperture radiometers to improve spatial resolution while maintaining radiometric sensitivity.Esta tesis se ha llevado a cabo en el marco de la beca FPI BES-2012-053917 del 1 de diciembre de 2012, por el "Secretario de Estado de Investigación del Ministerio de Economía y Competitividad", asociada al proyecto TEC2011-25865 (Universidad Politècnica de Catalunya). En un sentido más amplio, el trabajo se engloba dentro de las actividades del Grupo de Teledetección (RSLab) del Departamento de Teoría de la Señal y Comunicaciones, UPC, en el marco de la misión SMOS (Soil Moisture and Ocean Salinity) de la Agencia Espacial Europea del Espacio (ESA). El trabajo se divide en: 1) Calibración y prestaciones del sensor SMOS Desde el lanzamiento del instrumento en 2009, la imagen de SMOS se ha obtenido utilizando medidas en modo co-polar. Sin embargo, las medidas en SMOS se realizan en full-pol. Esto no se había llevado a cabo debido a los grandes errores que se obtenían con imágenes en full-pol. En este contexto mi trabajo se ha enfocado en la realización de una mejor caracterización de la antena. Basado en la idea de que el modo full-pol ha sido recientemente implementado en SMOS, las fases relativas entre antenas han sido recalculadas utilizando medidas co-polares y cross-polares. Los lóbulos secundarios de SMOS (SLL) son causados por la cobertura limitada de las visibilidades medidas en el dominio frecuencial, así que otro de los objetivos de este trabajo ha sido analizar el impacto de errores de calibración en los lóbulos secundarios de SMOS. Básicamente se han reproducido los lóbulos secundarios de SMOS mediantes simulaciones añadiendo errores a una fuente puntual, identificando las principales fuentes de error. Durante la fase de comisionado se detectó que el sistema de calentamiento de SMOS introducía pequeños saltos aleatorios del offset del PMS en diferentes unidades. Para hacer un seguimiento y corregir estos saltos se realizaron calibraciones de offset semanales justo después de la fase de comisionado, así que otro de los trabajos realizados en esta tesis ha sido dirigido a mitigar estos saltos introduciendo calibraciones adicionales antes de los mismos a partir de medir la temperatura de antena media calculada en el océano. 2) Técnicas de reducción de los errores espaciales SMOS tiene un error matemático de reconstrucción en la imagen que ha sido investigado en este trabajo. Así que este trabajo se ha focalizado en el "floor error" definido como el error de reconstrucción en un instrumento ideal libre de errores. Para reducir este error se han utilizado diferentes aproximaciones como Gibbs 2. 3) Mejoras en la inversión de imagen Uno de los mayores problemas durante los primeros cinco años de misión SMOS ha sido la llamada "land-sea contamination" (contaminación tierra-mar). Así pues, se ha realizado un estudio sistemático para comprender y mitigar este artefacto. Este tema está relacionado con uno de los descubrimientos más importantes de esta tesis ya que este tiene un gran impacto en la calidad de la imagen de SMOS. La técnica encontrada para mitigar este error es presentada y validada mediante diferentes métodos. 4) Misiones futuras Este trabajo está enfocado en la investigación del impacto de errores instrumentales en la precisión radiométrica de errores espaciales de una de las posibles nuevas configuraciones de array propuestas para construir un nuevo instrumento llamado Super-MIRAS. El propósito principal de este trabajo está orientado en el desarrollo de diferentes geometrías de arrays y arquitecturas de instrumentos para una futura misión en banda L, en la que se diseñaría un nuevo radiómetro de apertura sintética para mejorar la resolución espacial manteniendo la sensibilidad radiométrica

Contribution to advanced sensor development for passive imaging of the Earth

This work has been formally undertaken within the frame of the scholarship number BES-2012-053917 of 1 December 2012, by the "Secretario de Estado de Investigación del Ministerio de Economía y Competitividad" related to the program "Formación de Personal Investigador (FPI)". The scholarship is related to the research project at the Universitat Politècnica de Catalunya (UPC) number TEC2011-25865. In a more general scope, this thesis is related to the Remote Sensing Laboratory (Signal Theory & Communication Department, UPC) on-going activities, within the SMOS (Soil Moisture and Ocean Salinity) mission by the European Space Agency (ESA). These activities have been organized to provide original advances in the following four main topics: 1) SMOS calibration and performance. Since the launch of the instrument in 2009, SMOS imaging has been performing exclusively in co-polar mode. However, SMOS measurements are fully polarimetric. This feature was not operationally exploited due to the large errors yielded by full-pol images. In this context my work was addressed to support better characterization of the antenna. Based on the idea that SMOS polarization mode was recently implemented using Full-pol measurements, the so-called relative phases have been recomputed by using co-polar and cross-polar measurements. SMOS moderate Side Lobe Level (SLL) is caused by the limited coverage of the measured visibility samples in the frequency domain, so another objective of this work has been devoted to assess the impact of calibration errors into SMOS side lobes level (SLL). The main objective on this topic has been to reproduce by simulation SMOS measured side-lobe levels (SLL) by adding errors to a point source response, in order to identify the dominant source of error. During commissioning phase it was detected that SMOS heater system were introducing small and random sporadic PMS offset steps (jumps) in several units. Another work during this thesis has been devoted to mitigate those PMS jumps by trimming calibration date from single LICEF averaged TA jumps over the ocean. 2) SMOS spatial bias assessment. SMOS measurements still have mathematical image reconstruction errors that must be properly assessed. The aim of this work is to focus on the so-called "floor error", defined in an error free end-to-end image reconstruction simulation. In order to reduce this error, different inversion approaches have been implemented and tested, as the so-called Gibbs 2 approach 3) SMOS improved imaging. One of the problems of most concern within the SMOS mission is related to the so-called "land-sea contamination" (LSC), an artificial increase of ocean brightness temperature close to land masses. Therefore, a systematic assessment has been performed in this thesis in order to understand and mitigate this artifact. This subject is related to one of the main original outcomes of the thesis, since it has a relevant impact on the quality of SMOS imaging. The LSC mitigation technique developed during the work of the thesis has been presented and validated by different methods. 4) SMOS follow-on missions advanced configurations. This work is devoted to assess the impact of instrumental errors on the radiometric accuracy (pixel bias) of one of the selected array configurations of the so-called Super-MIRAS instrument. The aim of this work has been focused on the assessment of different array geometries and instrument architectures of future L-band synthetic aperture radiometers to improve spatial resolution while maintaining radiometric sensitivity.Esta tesis se ha llevado a cabo en el marco de la beca FPI BES-2012-053917 del 1 de diciembre de 2012, por el "Secretario de Estado de Investigación del Ministerio de Economía y Competitividad", asociada al proyecto TEC2011-25865 (Universidad Politècnica de Catalunya). En un sentido más amplio, el trabajo se engloba dentro de las actividades del Grupo de Teledetección (RSLab) del Departamento de Teoría de la Señal y Comunicaciones, UPC, en el marco de la misión SMOS (Soil Moisture and Ocean Salinity) de la Agencia Espacial Europea del Espacio (ESA). El trabajo se divide en: 1) Calibración y prestaciones del sensor SMOS Desde el lanzamiento del instrumento en 2009, la imagen de SMOS se ha obtenido utilizando medidas en modo co-polar. Sin embargo, las medidas en SMOS se realizan en full-pol. Esto no se había llevado a cabo debido a los grandes errores que se obtenían con imágenes en full-pol. En este contexto mi trabajo se ha enfocado en la realización de una mejor caracterización de la antena. Basado en la idea de que el modo full-pol ha sido recientemente implementado en SMOS, las fases relativas entre antenas han sido recalculadas utilizando medidas co-polares y cross-polares. Los lóbulos secundarios de SMOS (SLL) son causados por la cobertura limitada de las visibilidades medidas en el dominio frecuencial, así que otro de los objetivos de este trabajo ha sido analizar el impacto de errores de calibración en los lóbulos secundarios de SMOS. Básicamente se han reproducido los lóbulos secundarios de SMOS mediantes simulaciones añadiendo errores a una fuente puntual, identificando las principales fuentes de error. Durante la fase de comisionado se detectó que el sistema de calentamiento de SMOS introducía pequeños saltos aleatorios del offset del PMS en diferentes unidades. Para hacer un seguimiento y corregir estos saltos se realizaron calibraciones de offset semanales justo después de la fase de comisionado, así que otro de los trabajos realizados en esta tesis ha sido dirigido a mitigar estos saltos introduciendo calibraciones adicionales antes de los mismos a partir de medir la temperatura de antena media calculada en el océano. 2) Técnicas de reducción de los errores espaciales SMOS tiene un error matemático de reconstrucción en la imagen que ha sido investigado en este trabajo. Así que este trabajo se ha focalizado en el "floor error" definido como el error de reconstrucción en un instrumento ideal libre de errores. Para reducir este error se han utilizado diferentes aproximaciones como Gibbs 2. 3) Mejoras en la inversión de imagen Uno de los mayores problemas durante los primeros cinco años de misión SMOS ha sido la llamada "land-sea contamination" (contaminación tierra-mar). Así pues, se ha realizado un estudio sistemático para comprender y mitigar este artefacto. Este tema está relacionado con uno de los descubrimientos más importantes de esta tesis ya que este tiene un gran impacto en la calidad de la imagen de SMOS. La técnica encontrada para mitigar este error es presentada y validada mediante diferentes métodos. 4) Misiones futuras Este trabajo está enfocado en la investigación del impacto de errores instrumentales en la precisión radiométrica de errores espaciales de una de las posibles nuevas configuraciones de array propuestas para construir un nuevo instrumento llamado Super-MIRAS. El propósito principal de este trabajo está orientado en el desarrollo de diferentes geometrías de arrays y arquitecturas de instrumentos para una futura misión en banda L, en la que se diseñaría un nuevo radiómetro de apertura sintética para mejorar la resolución espacial manteniendo la sensibilidad radiométrica.Postprint (published version

2000 days of SMOS at the Barcelona Expert Centre: a tribute to the work of Jordi Font

Soil Moisture and Ocean Salinity (SMOS) is the first satellite mission capable of measuring sea surface salinity and soil moisture from space. Its novel instrument (the L-band radiometer MIRAS) has required the development of new algorithms to process SMOS data, a challenging task due to many processing issues and the difficulties inherent in a new technology. In the wake of SMOS, a new community of users has grown, requesting new products and applications, and extending the interest in this novel brand of satellite services. This paper reviews the role played by the Barcelona Expert Centre under the direction of Jordi Font, SMOS co-principal investigator. The main scientific activities and achievements and the future directions are discussed, highlighting the importance of the oceanographic applications of the mission.Peer ReviewedPostprint (published version

Nodal sampling: a new image reconstruction algorithm for SMOS

Soil moisture and ocean salinity (SMOS) brightness temperature (TB) images and calibrated visibilities are related by the so-called G -matrix. Due to the incomplete sampling at some spatial frequencies, sharp transitions in the TB scenes generate a Gibbs-like contamination ringing and spread sidelobes. In the current SMOS image reconstruction strategy, a Blackman window is applied to the Fourier components of the TBs to diminish the amplitude of artifacts such as ripples, as well as other Gibbs -like effects. In this paper, a novel image reconstruction algorithm focused on the reduction of Gibbs -like contamination in TB images is proposed. It is based on sampling the TB images at the nodal points, that is, at those points at which the oscillating interference causes the minimum distortion to the geophysical signal. Results show a significant reduction of ripples and sidelobes in strongly radio-frequency interference contaminated images. This technique has been thoroughly validated using snapshots over the ocean, by comparing TBs reconstructed in the standard way or using the nodal sampling (NS) with modeled TBs. Tests have revealed that the standard deviation of the difference between the measurement and the model is reduced around 1 K over clean and stable zones when using NS technique with respect to the SMOS image reconstruction baseline. The reduction is approximately 0.7 K when considering the global ocean. This represents a crucial improvement in TB quality, which will translate in an enhancement of the retrieved geophysical parameters, particularly the sea surface salinity.Peer ReviewedPostprint (author's final draft

Deriving vertical total electron content maps from SMOS full polarimetric data to compensate the Faraday rotation effect

The Faraday rotation is a geophysical effect that causes a rotation of the electromagnetic field components emitted by the Earth when it propagates through the ionosphere. It depends on the vertical total electron content (VTEC) of the ionosphere, the geomagnetic field, and the frequency. For satellite measurements at the L band, this effect is not negligible and must be compensated for. This is the case of the Soil Moisture and Ocean Salinity (SMOS) mission, where the measured polarimetric brightness temperature must be corrected from the Faraday rotation effect before the retrieval of the geophysical parameters. The Faraday rotation angle (FRA) can be estimated using a theoretical formulation that makes use of external sources for the VTEC and the geomagnetic field. Alternatively, it can be continuously retrieved from the SMOS full-polarimetric data. However, this is not straightforward due to the relatively poor radiometric sensitivity (thermal noise) and accuracy (spatial bias) of its payload MIRAS (Microwave Interferometer Radiometer by Aperture Synthesis). In this thesis, a methodology for estimating the total electron content of the ionosphere by using an inversion procedure from the measured rotation angle has been developed. These SMOS VTEC maps are derived from SMOS measurements in the Extended Alias-Free Field of View (EAF-FoV) by applying spatio-temporal filtering techniques to mitigate the radiometric errors present in the full-polarimetric measured brightness temperatures. Systematic error patterns found in the Faraday rotation angle retrieval have been characterized along the mission and corrected. The methodology is independent, not only of external databases and forward models, but also of the target that is being measured. Eventually, these SMOS-derived VTEC maps can then be used in the SMOS level 2 processors to improve the geophysical retrievals. The impact of using these SMOS VTEC maps to correct the FRA in the SMOS mission instead of the commonly used VTEC data from GPS has also been assessed, particularly over ocean, where the ionospheric effect is stronger. This assessment has demonstrated improvements in the spatial biases, in the stability of the brightness temperatures (especially in the third Stokes parameter), and in the reduction of the latitudinal gradient present in the third Stokes parameters. All these quality indicators point to a better quality of the geophysical retrievals.La rotación de Faraday es un efecto geofísico que causa un giro en las componentes del campo electromagnético emitido por la Tierra cuando éste se propaga a través de la ionosfera. Ésta depende del contenido vertical total de electrones (VTEC) en la ionosfera, el campo geomagnético y la frecuencia. En las medidas de los satélites que operan en banda L, este efecto no es despreciable y se debe compensar. Este es el caso de la misión SMOS (Soil Moisture and Ocean Salinity), por lo que el efecto de Faraday se tiene que corregir en las medidas polarimétricas captadas por el instrumento antes de obtener parámetros geofísicos. El ángulo de rotación de Faraday (FRA) se puede estimar con una fórmula teórica que usa bases de datos externas para el VTEC y el campo geomagnético. Alternativamente, se puede obtener de una manera continua a partir de los datos polarimétricos de SMOS. Sin embargo, esto no se logra con un cálculo directo debido a la pobre sensibilidad radiométrica (ruido térmico) y a la baja precisión (sesgos espaciales) que presenta el instrumento MIRAS (Microwave Interferometer Radiometer by apertura Synthesis), que se encuentra a bordo del satélite. En esta tesis, se desarrolla una metodología para estimar el VTEC de la ionosfera usando un proceso inverso a partir del ángulo de rotación medido. Estos mapas de VTEC se derivan de medidas en todo el campo de visión extendido en donde no hay aliasing. Para mitigar los errores radiométricos en las temperaturas de brillo polarimétricas, se aplican técnicas de filtrados temporales y espaciales. En el ángulo de rotación de Faraday recuperado se detectaron errores sistemáticos. Estos se caracterizaron a lo largo de la misión y se corrigieron. La metodología es independiente, no solo de bases de datos externas y modelos de océano, sino también de la superficie medida. Estos mapas de VTEC derivados de los datos SMOS se pueden usar en el procesador de nivel 2 para mejorar las recuperaciones geofísicas. Se ha evaluado el impacto de usar estos mapas para corregir el FRA en la misión, en vez de los datos de VTEC que comúnmente se emplean (mapas provenientes de datos de GPS), particularmente sobre océano, en donde los efectos de la ionosfera son más críticos. Esta verificación ha demostrado mejoras en el sesgo espacial, en la estabilidad de las temperaturas de brillo (especialmente en el tercer parámetro de Stokes) y en la reducción del gradiente latitudinal presente en el tercer parámetro de Stokes. Todos estos indicadores de calidad apuntan a la obtención de parámetros geofísicos de mejor calidad.Postprint (published version

Assessment of Drought in Grasslands: Spatio – Temporal Analyses of Soil Moisture and Extreme Climate Effects in Southwestern Mongolia

Soil moisture plays an essential key role in the assessment of hydrological and meteorological droughts that may affect a wide area of the natural grassland and the groundwater resource. The surface soil moisture distribution as a function of time and space is highly relevant for hydrological, ecological, and agricultural applications, especially in water-limited or drought-prone regions. However, gauging soil moisture is challenging because of its high variability. While point-scale in-situ measurements are scarce, the remote sensing tools remain the only practical means to obtain regional and global-scale soil moisture estimates. A Soil Moisture and Ocean Salinity (SMOS) is the first satellite mission ever designed to gauge the Earth’s surface soil moisture (SM) at the near-daily time scales. This work aims to evaluate the spatial and temporal patterns of SMOS soil moisture, determine the effect of the climate extremes on the vegetation growth cycle, and demonstrate the feasibility of using our drought model (GDI) the Gobi Drought Index. The GDI is based on the combination of SMOS soil moisture and several products from the MODIS satellite. We used this index for hydro-meteorological drought monitoring in Southwestern Mongolia. Firstly, we validated bias-corrected SMOS soil moisture for Mongolia by the in-situ soil moisture observations 2000 to 2015. Validation shows satisfactory results for assessing drought and water-stress conditions in the grasslands of Mongolia. The correlation analysis between SMOS and Normalized Difference Vegetation Index (NDVI) index in the various ecosystems shows a high correlation between the bias-corrected, monthly-averaged SMOS and NDVI data (R2 > 0.81). Further analysis of the SMOS and in situ SM data revealed a good match between spatial SM distribution and the rainfall events over Southwestern Mongolia. For example, during dry 2015, SM was decreased by approximately 30% across the forest-steppe and steppe areas. We also notice that both NDVI and rainfall can be used as indicators for grassland monitoring in Mongolia. The second part of this research, analyzed several dzud (specific type of climate winter disaster) events (2000, 2001, 2002, and 2010) related to drought, to comprehend the spatial and temporal variability of vegetation conditions in the Gobi region of Mongolia. We determined how these extreme climatic events affect vegetation cover and local grazing conditions using the seasonal aridity index (aAIZ), NDVI, and livestock mortality data. The NDVI is used as an indicator of vegetation activity and growth. Its spatial and temporal pattern is expected to reflect the changes in surface vegetation density and status induced by water-deficit conditions. The Gobi steppe areas showed the highest degree of vulnerability to climate, with a drastic decline of grassland in arid areas. We found that under certain dzud conditions, rapid regeneration of vegetation can occur. A thick snow layer acting as a water reservoir combined with high livestock losses can lead to an increase of the maximum August NDVI. The snowy winters can cause a 10 to 20-day early peak in NDVI and the following increase in vegetation growth. However, during a year with dry winter conditions, the vegetation growth phase begins later due to water deficiency and the entire year has a weaker vegetation growth. Generally, livestock loss and the reduction of grazing pressure was played a crucial role in vegetation recovery after extreme climatic events in Mongolia. At the last stage of our study, we develop an integrated Gobi drought index (GDI), derived from SMOS and LST, PET, and NDVI MODIS products. GDI can incorporate both, the meteorological and soil moisture drought patterns and sufficiently well represent overall drought conditions in the arid lands. Specifically, the monthly GDI and 1-month standardized precipitation index SPI showed significant correlations. Both of them are useful for drought monitoring in semi-arid lands. But, the SPI requires in situ data that are sparse, while the GDI is free from the meteorological network restriction. Consequently, we compared the GDI with other drought indices (VSWI, NDDI, NDWI, and in-situ SM). Comparison of these drought indices with the GDI allowed assessing the droughts’ behavior from different angles and quantified better their intensity. The GDI maps at fine-scale (< 1km) permit extending the applicability of our drought model to regional and local studies. These maps were generated from 2000 to 2018 across Southwestern Mongolia. Fine-scale GDI drought maps are currently limited to the whole territory for Mongolia but the algorithm is dynamic and can be transported to any region. The GDI drought index can be served as a useful tool for prevention services to detect extremely dry soil and vegetation conditions posing a risk of drought and groundwater resource depletion. It was able to detect the drought events that were underestimated by the National Drought Watch System in Mongolia. In summary, with the help of satellite, climatological, and geophysical data, the integrated GDI can be beneficial for vegetation drought stress characterization and can be a useful tool to monitor the effectiveness of pasture land restoration management practices for Mongolian livelihoods. The future application of the GDI can be extended to monitor potential impacts on water resources and agriculture in Mongolia, which have been impacted by long periods of drought

Improved MUSIC-based SMOS RFI source detection and geolocation algorithm

©2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.The European Space Agency's Soil Moisture and Ocean Salinity (SMOS) mission has been providing L-band brightness temperature (BT) using its instrument, the Microwave Imaging Radiometer using Aperture Synthesis. In the measurements, the negative effect of radio frequency interference (RFI) is clearly present, deteriorating the quality of geophysical parameter retrieval. Detection and geolocation of RFI sources are essential to remove or at least mitigate the RFI impacts and ultimately improve the performance of parameter retrieval. This paper discusses a new approach to SMOS RFI source detection, based on the MUltiple SIgnal Classification (MUSIC) algorithm. Recently, the feasibility of MUSIC direction-of-arrival estimation has been shown for the RFI source detection of the synthetic aperture interferometric radiometer. This paper refines the MUSIC RFI source detection algorithm and tailors it to the SMOS scenario. To consolidate the RFI source detection procedure, several required steps are devised, including the rank estimation of the covariance matrix, local peak detection and thresholds, andmultiple-snapshot processing. The developed method is tested using a number of SMOS visibility samples. In the test results, the MUSIC method shows an improvement on the accuracy and precision of the RFI source geolocation, compared with a simple detection method based on the local peaks of BT images. The MUSIC results especially outperform the SMOS BT image on the spatial resolution.Peer ReviewedPostprint (author's final draft