31 research outputs found
Satellite remote sensing of surface winds, waves, and currents: Where are we now?
This review paper reports on the state-of-the-art concerning observations of surface winds, waves, and currents from space and their use for scientific research and subsequent applications. The development of observations of sea state parameters from space dates back to the 1970s, with a significant increase in the number and diversity of space missions since the 1990s. Sensors used to monitor the sea-state parameters from space are mainly based on microwave techniques. They are either specifically designed to monitor surface parameters or are used for their abilities to provide opportunistic measurements complementary to their primary purpose. The principles on which is based on the estimation of the sea surface parameters are first described, including the performance and limitations of each method. Numerous examples and references on the use of these observations for scientific and operational applications are then given. The richness and diversity of these applications are linked to the importance of knowledge of the sea state in many fields. Firstly, surface wind, waves, and currents are significant factors influencing exchanges at the air/sea interface, impacting oceanic and atmospheric boundary layers, contributing to sea level rise at the coasts, and interacting with the sea-ice formation or destruction in the polar zones. Secondly, ocean surface currents combined with wind- and wave- induced drift contribute to the transport of heat, salt, and pollutants. Waves and surface currents also impact sediment transport and erosion in coastal areas. For operational applications, observations of surface parameters are necessary on the one hand to constrain the numerical solutions of predictive models (numerical wave, oceanic, or atmospheric models), and on the other hand to validate their results. In turn, these predictive models are used to guarantee safe, efficient, and successful offshore operations, including the commercial shipping and energy sector, as well as tourism and coastal activities. Long-time series of global sea-state observations are also becoming increasingly important to analyze the impact of climate change on our environment. All these aspects are recalled in the article, relating to both historical and contemporary activities in these fields
BDS GNSS for Earth Observation
For millennia, human communities have wondered about the possibility of observing
phenomena in their surroundings, and in particular those affecting the Earth on which they live.
More generally, it can be conceptually defined as Earth observation (EO) and is the collection of
information about the biological, chemical and physical systems of planet Earth. It can be undertaken
through sensors in direct contact with the ground or airborne platforms (such as weather balloons and
stations) or remote-sensing technologies. However, the definition of EO has only become significant
in the last 50 years, since it has been possible to send artificial satellites out of Earth’s orbit.
Referring strictly to civil applications, satellites of this type were initially designed to provide
satellite images; later, their purpose expanded to include the study of information on land
characteristics, growing vegetation, crops, and environmental pollution. The data collected are used
for several purposes, including the identification of natural resources and the production of accurate
cartography. Satellite observations can cover the land, the atmosphere, and the oceans.
Remote-sensing satellites may be equipped with passive instrumentation such as infrared or
cameras for imaging the visible or active instrumentation such as radar. Generally, such satellites are
non-geostationary satellites, i.e., they move at a certain speed along orbits inclined with respect to the
Earth’s equatorial plane, often in polar orbit, at low or medium altitude, Low Earth Orbit (LEO) and
Medium Earth Orbit (MEO), thus covering the entire Earth’s surface in a certain scan time (properly
called ’temporal resolution’), i.e., in a certain number of orbits around the Earth.
The first remote-sensing satellites were the American NASA/USGS Landsat Program;
subsequently, the European: ENVISAT (ENVironmental SATellite), ERS (European Remote-Sensing
satellite), RapidEye, the French SPOT (Satellite Pour l’Observation de laTerre), and the Canadian
RADARSAT satellites were launched. The IKONOS, QuickBird, and GeoEye-1 satellites were
dedicated to cartography. The WorldView-1 and WorldView-2 satellites and the COSMO-SkyMed
system are more recent. The latest generation are the low payloads called Small Satellites, e.g., the
Chinese BuFeng-1 and Fengyun-3 series.
Also, Global Navigation Satellite Systems (GNSSs) have captured the attention of researchers
worldwide for a multitude of Earth monitoring and exploration applications. On the other hand,
over the past 40 years, GNSSs have become an essential part of many human activities. As is widely
noted, there are currently four fully operational GNSSs; two of these were developed for military
purposes (American NAVstar GPS and Russian GLONASS), whilst two others were developed for
civil purposes such as the Chinese BeiDou satellite navigation system (BDS) and the European
Galileo. In addition, many other regional GNSSs, such as the South Korean Regional Positioning
System (KPS), the Japanese quasi-zenital satellite system (QZSS), and the Indian Regional Navigation
Satellite System (IRNSS/NavIC), will become available in the next few years, which will have
enormous potential for scientific applications and geomatics professionals.
In addition to their traditional role of providing global positioning, navigation, and timing (PNT)
information, GNSS navigation signals are now being used in new and innovative ways. Across the
globe, new fields of scientific study are opening up to examine how signals can provide information
about the characteristics of the atmosphere and even the surfaces from which they are reflected before
being collected by a receiver.
EO researchers monitor global environmental systems using in situ and remote monitoring tools.
Their findings provide tools to support decision makers in various areas of interest, from security
to the natural environment. GNSS signals are considered an important new source of information
because they are a free, real-time, and globally available resource for the EO community
Statistical and Machine Learning Models for Remote Sensing Data Mining - Recent Advancements
This book is a reprint of the Special Issue entitled "Statistical and Machine Learning Models for Remote Sensing Data Mining - Recent Advancements" that was published in Remote Sensing, MDPI. It provides insights into both core technical challenges and some selected critical applications of satellite remote sensing image analytics
Improving Flood Detection and Monitoring through Remote Sensing
As climate-change- and human-induced floods inflict increasing costs upon the planet, both in terms of lives and environmental damage, flood monitoring tools derived from remote sensing platforms have undergone improvements in their performance and capabilities in terms of spectral, spatial and temporal extents and resolutions. Such improvements raise new challenges connected to data analysis and interpretation, in terms of, e.g., effectively discerning the presence of floodwaters in different land-cover types and environmental conditions or refining the accuracy of detection algorithms. In this sense, high expectations are placed on new methods that integrate information obtained from multiple techniques, platforms, sensors, bands and acquisition times. Moreover, the assessment of such techniques strongly benefits from collaboration with hydrological and/or hydraulic modeling of the evolution of flood events. The aim of this Special Issue is to provide an overview of recent advancements in the state of the art of flood monitoring methods and techniques derived from remotely sensed data
Synergistic optical and microwave remote sensing approaches for soil moisture mapping at high resolution
Aplicat embargament des de la data de defensa fins al dia 1 d'octubre de 2022Soil moisture is an essential climate variable that plays a crucial role linking the Earth’s water, energy, and carbon cycles. It is responsible for the water exchange between the Earth’s surface and the atmosphere, and provides key information about soil evaporation, plant transpiration, and the allocation of precipitation into runoff, surface flow and infiltration. Therefore, an accurate estimation of soil moisture is needed to enhance our current climate and meteorological forecasting skills, and to improve our current understanding of the hydrological cycle and its extremes (e.g., droughts and floods). L-band Microwave passive and active sensors have been used during the last decades to estimate soil moisture, since there is a strong relationship between this variable and the soil dielectric properties.
Currently, there are two operational L-band missions specifically devoted to globally measure soil moisture: the ESA’s Soil Moisture and the Ocean Salinity (SMOS), launched in November 2009; and the NASA’s Soil Moisture Active Passive (SMAP), launched in January 2015. The spatial resolution of the SMOS and SMAP radiometers, in the order of tens of kilometers (~40 km), is adequate for global applications. However, to fulfill the needs of a growing number of applications at local or regional scale, higher spatial detail (< 1 km) is required. To bridge this gap and improve the spatial resolution of the soil moisture maps, a variety of spatial enhancement or spatial (sub-pixel) disaggregation approaches have been proposed.
This Ph.D. Thesis focuses on the study of the Earth’s surface soil moisture from remotely sensed observations. This work includes the implementation of several soil moisture retrieval techniques and the development, implementation, validation and comparison of different spatial enhancement or downscaling techniques, applied at local, regional, and continental scale. To meet these objectives, synergies between several active/passive microwave sensors (SMOS, SMAP and Sentinel-1) and optical/thermal sensors (MODIS) have been explored. The results are presented as follows:
- Spatially consistent downscaling approach for SMOS using an adaptive moving window
A passive microwave/optical downscaling algorithm for SMOS is proposed to obtain fine-scale soil moisture maps (1 km) from the native resolution (~40 km) of the instrument. This algorithm introduces the concept of a shape-adaptive window as a central improvement of the disaggregation technique presented by Piles et al. (2014), allowing its application at continental scales.
- Assessment of multi-scale SMOS and SMAP soil moisture products across the Iberian Peninsula
The temporal and spatial characteristics of SMOS and SMAP soil moisture products at coarse- and fine-scales are assessed in order to learn about their distinct features and the rationale behind them, tracing back to the physical assumptions they are based upon.
- Impact of incidence angle diversity on soil moisture retrievals at coarse and fine scales
An incidence angle (32.5°, 42.5° and 52.5°)-adaptive calibration of radiative transfer effective parameters single scattering albedo and soil roughness has been carried out, highlighting the importance of such parameterization to accurately estimate soil moisture at coarse-resolution. Then, these parameterizations are used to examine the potential application of a physically-based active-passive downscaling approach to upcoming microwave missions, namely CIMR, ROSE-L and Sentinel-1 Next Generation. Soil moisture maps obtained for the Iberian Peninsula at the three different angles, and at coarse and fine scales are inter-compared using in situ measurements and model data as benchmarks.La humedad del suelo es una variable climática esencial que juega un papel crucial en la relación de los ciclos del agua, la energía y el carbono de la Tierra. Es responsable del intercambio de agua entre la superficie de la Tierra y la atmósfera, y proporciona información crucial sobre la evaporación del suelo, la transpiración de las plantas y la distribución de la precipitación en escorrentía, flujo superficial e infiltración. Por lo tanto, es necesaria una estimación precisa de la humedad del suelo para mejorar las predicciones climáticas y meteorológicas, y comprender mejor el ciclo hidrológico y sus extremos (v.g., sequías e inundaciones). Los sensores pasivos y activos en banda L se han usado durante las últimas décadas para estimar la humedad del suelo debido a la relación directa que existe entre esta variable y las propiedades dieléctricas del suelo.
Actualmente, hay dos misiones operativas en banda L específicamente dedicadas a medir la
humedad del suelo a escala global: la misión Soil Moisture and Ocean Salinity (SMOS) de la ESA,
lanzada en noviembre de 2009; y la misión Soil Moisture Active Passive (SMAP) de la NASA,
lanzada en enero de 2015. La resolución espacial de los radiómetros SMOS y SMAP, del orden de unas decenas de kilómetros (~40 km), es adecuada para aplicaciones a escala global. Sin embargo, para satisfacer las necesidades de un número creciente de aplicaciones a escala local o regional, se requiere más detalle espacial (<1 km). Para solventar esta limitación y mejorar la resolución espacial de los mapas de humedad, se han propuesto diferentes técnicas de mejora o desagregación espacial.
Esta Tesis se centra en el estudio de la humedad de la superficie terrestre a partir de datos
obtenidos a través de teledetección. Este trabajo incluye la implementación de distintos
algoritmos de recuperación de la humedad del suelo y el desarrollo, implementación, validación y comparación de distintas técnicas de desagregación, aplicadas a escala local, regional y continental. Para cumplir estos objetivos, se han explorado sinergias entre diferentes sensores de microondas activos/pasivos (SMOS, SMAP y Sentinel-1) y sensores ópticos/térmicos. Los resultados se presentan de la siguiente manera:
- Técnica de desagregación espacialmente consistente, basada en una ventana móvil
adaptativa, aplicada a los datos SMOS
Se propone un algoritmo de desagregación del píxel basado en datos obtenidos de medidas
radiométricas de microondas en banda L y datos ópticos, para mejorar la resolución espacial de
los mapas de humedad del suelo desde la resolución nativa del instrumento (~40 km) hasta
resoluciones de 1 km. El algoritmo introduce el concepto de una ventana de contorno
adaptativo, como mejora principal sobre la técnica de desagregación presentada en Piles et al. (2014), permitiendo su implementación a escala continental.
- Análisis multiescalar de productos de humedad del suelo SMAP y SMOS sobre la
Península Ibérica Se han evaluado las características temporales y espaciales de distintos productos de humedad del suelo SMOS y SMAP, a baja y a alta resolución, para conocer sus características distintivas y comprender las razones de sus diferencias. Para ello, ha sido necesario rastrear los supuestos físicos en los que se basan.
- Impacto del ángulo de incidencia en la recuperación de la humedad del suelo a baja y a
alta resolución
Se ha llevado a cabo una calibración adaptada al ángulo de incidencia (32.5°, 42.5° y 52.5°)
de los parámetros efectivos, albedo de dispersión simple y rugosidad del suelo, descritos en el modelo de transferencia radiativa � − �, incidiendo en la importancia de esta parametrización para estimar la humedad del suelo de forma precisa a baja resolución. El resultado de las mismas se ha utilizado para estudiar la potencial aplicación de un algoritmo activo/pasivo de desagregación basado en la física para las próximas misiones de microondas, llamadas CIMR, ROSE-L y Sentinel-1 Next Generation. Los mapas de humedad recuperados a los tres ángulos de incidencia, tanto a baja como a alta resolución, se han obtenido para la Península Ibérica y se han comparado entre ellos usando como referencia mediciones de humedad in situ.Postprint (published version
Airborne Coherent GNSS Reflectometry and Zenith Total Delay Estimation over Coastal Waters
High-precision GNSS (global navigation satellite e system) measurements can be used for remote sensing and nowadays play a significant role in atmospheric sounding (station data, radio occultation observations) and sea surface altimetry based on reflectometry. A limiting factor of high-precision reflectometry is the loss of coherent phase information due to sea-state-induced surface roughness. This work studies airborne reflectometry observations recorded over coastal waters to examine the sea-state influence on Doppler distribution and the coherent residual phase retrieval. From coherent observations, the possibility of zenith total delay inversion is also investigated, considering the hydrostatic mapping factor from the Vienna mapping function and an exponential vertical decay factor depending on height receiver changes. The experiment consists of multiple flights performed along the coast between the cities of Calais and Boulogne-sur-Mer, France, in July 2019. Reflected signals acquired in a right-handed circular polarization are processed through a model-aided software receiver and passed through a retracking module to obtain the Doppler and phase-corrected signal. Results from grazing angle observations (elevation < 15°) show a high sensitivity of Doppler spread with respect to sea state with correlations of 0.75 and 0.88 with significant wave height and wind speed, respectively. An empirical Doppler spread threshold of 0.5 Hz is established for coherent reflections supported by the residual phase observations obtained. Phase coherence occurs in 15% of the observations; however, the estimated zenith total delay for the best event corresponds to 2.44 m, which differs from the typical zenith total delay (2.3 m) of 5%
The International Soil Moisture Network:Serving Earth system science for over a decade
In 2009, the International Soil Moisture Network (ISMN) was initiated as a community effort, funded by the European Space Agency, to serve as a centralised data hosting facility for globally available in situ soil moisture measurements (Dorigo et al., 2011b, a). The ISMN brings together in situ soil moisture measurements collected and freely shared by a multitude of organisations, harmonises them in terms of units and sampling rates, applies advanced quality control, and stores them in a database. Users can freely retrieve the data from this database through an online web portal (https://ismn.earth/en/, last access: 28 October 2021). Meanwhile, the ISMN has evolved into the primary in situ soil moisture reference database worldwide, as evidenced by more than 3000 active users and over 1000 scientific publications referencing the data sets provided by the network. As of July 2021, the ISMN now contains the data of 71 networks and 2842 stations located all over the globe, with a time period spanning from 1952 to the present. The number of networks and stations covered by the ISMN is still growing, and approximately 70 % of the data sets contained in the database continue to be updated on a regular or irregular basis. The main scope of this paper is to inform readers about the evolution of the ISMN over the past decade, including a description of network and data set updates and quality control procedures. A comprehensive review of the existing literature making use of ISMN data is also provided in order to identify current limitations in functionality and data usage and to shape priorities for the next decade of operations of this unique community-based data repository
Engineering Calibration and Physical Principles of GNSS-Reflectometry for Earth Remote Sensing
The Cyclone Global Navigation Satellite System (CYGNSS) is a NASA mission that uses 32 Global Positioning System (GPS) satellites as active sources and 8 CYGNSS satellites as passive receivers to measure ocean surface roughness and wind speed, as well as soil moisture and flood inundation over land. This dissertation addresses two major aspects of engineering calibration: (1) characterization of the GPS effective isotropic radiated power (EIRP) for calibration of normalized bistatic radar cross section (NBRCS) observables; and (2) development of an end-to-end calibration approach using modeling and measurements of ocean surface mean square slope (MSS). To estimate the GPS transmit power, a ground-based GPS constellation power monitor (GCPM) system has been built to accurately and precisely measure the direct GPS signals. The transmit power of the L1 coarse/acquisition (C/A) code of the full GPS constellation is estimated using an optimal search algorithm. Updated values for transmit power have been successfully applied to CYGNSS L1B calibration and found to significantly reduce the PRN dependence of CYGNSS L1 and L2 data products. The gain pattern of each GPS satellite’s transmit antenna for the L1 C/A signal is determined from measurements of signal strength received by the 8-satellite CYGNSS constellation. Determination of GPS patterns requires knowledge of CYGNSS patterns and vice versa, so a procedure is developed to solve for both of them iteratively. The new GPS and CYGNSS patterns have been incorporated into the science data processing algorithm used by the CYGNSS mission and result in improved calibration performance. Variable transmit power by numerous Block IIF and IIR-M GPS space vehicles has been observed due to their flex power mode. Non-uniformity in the GPS antenna gain patterns further complicates EIRP estimation. A dynamic calibration approach is developed to further address GPS EIRP variability. It uses measurements by the direct received GPS signal to estimate GPS EIRP in the specular reflected direction and then incorporates them into the calibration of NBRCS. Dynamic EIRP calibration instantaneously detects and corrects for power fluctuations in the GPS transmitters and significantly reduces errors due to GPS antenna gain azimuthal asymmetry. It allows observations with the most variable Block IIF transmitters (approximately 37% of the GPS constellation) to be included in the standard data products and further improves the calibration quality of the NBRCS. A physics-based approach is then proposed to examine potential calibration errors and to further improve the Level 1 calibration. The mean square slope (mss) is a key physical parameter that relates the ocean surface properties (wave spectra) to the CYGNSS measurement of NBRCS. An approach to model the mss for validation with CYGNSS mss data is developed by adding the contribution of a high frequency tail to the WAVEWATCH III (WW3) mss. It is demonstrated that the ratio of CYGNSS mss to modified WW3 mss can be used to diagnose potential calibration errors that exist in the Level 1 calibration algorithm. This approach can help to improve CYGNSS data quality, including the Level 1 NBRCS and Level 2 ocean surface wind speed and roughness. The engineering calibration methods presented in this dissertation make significant contributions to the spatial coverage, calibration quality of the measured NBRCS and the geophysical data products produced by the NASA CYGNSS mission. The research is also useful to the system design, science investigation and engineering calibration of future GNSS-reflectometry missions.PHDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/168052/1/wangtl_1.pd
Studies of the MLT/I using Multistatic Meteor Radar
This thesis applies a multistatic meteor radar to an investigation of the dynamics of
the mesosphere lower thermosphere/ionosphere (MLT/I; 60-110 km altitude). The
main radar used in the study operates at 55 MHz and is in the vicinity of Adelaide,
South Australia, consisting of a monostatic radar at the Buckland Park eld site (34.6 S,
138.5 E) and a bistatic receiver located about 55 km south-east at a site in the Adelaide
Hills (35.1 S, 138.8 E). The areas of investigation pertaining to MLT/I dynamics
include assessing the ability of a multistatic meteor radar to measure the vertical
ux
of horizontal momentum and studying the interaction between gravity waves and tidal
e ects. The thesis also presents a novel phase calibration technique for meteor radars,
based on the use of civilian aircraft.
The assessment of this radar's ability to measure MLT/I momentum
uxes demonstrated
that a relative uncertainty of about 75% can be expected for a monostatic con
guration, assuming a
ux magnitude of 20 m2s-2, a single day of integration, and
a gravity wave field synthesized from a realistic spectral model. The multistatic configuration
with a single bistatic receiver is shown to yield a relative uncertainty of about
65% under the same conditions. It is suggested that the increase in precision can be
attributed entirely to the increase in the number of meteor detections associated with
the combined monostatic and bistatic receivers, rather than due to the existence of a
more favourable distribution of Bragg vectors arising from the receiver separation.
A case study of winds around the autumnal equinox of 2018 revealed large modulations
in diurnal tidal amplitudes, with peak component diurnal tide amplitudes of 50
ms-1 and peak zonal wind velocities of 140 ms-1. In the context of the need to verify
the accuracy of momentum
ux estimates from the radar, this motivated an investigation
into the role momentum transport from gravity wave breaking played in modulating the
tidal amplitudes. The investigation showed that while the observed gravity wave forcing
exhibited a complex relationship with the tidal winds, the components of the forcing
were generally seen to be approximately out of phase with the tidal winds above altitudes of 88 km. Additionally, no clear phase relationship between the tides and
gravity wave forcing was observed below 88 km.
Following the case study, the altitude and angle-of-arrival (AOA) errors and reduced
meteor detection rates associated with suspected receiver phase calibration errors motivated
the development of an alternative phase calibration technique. The technique
developed was based on the use of echoes from civilian aircraft with known positions.
Approximately two weeks worth of aircraft detections with the radar and a 1090 MHz
Automatic Dependent Surveillance Broadcast receiver (used to receive aircraft position
information) was acquired during November 2019. By taking into account the implied
phase correction variability with AOA using a beamforming approach, it was shown
that the aircraft-based corrections yielded an equal or smaller meteor height distribution
width than the conventionally used empirical phase calibration technique. Assuming
that a smaller height distribution width equates to smaller average height estimation errors,
this was taken to mean that the aircraft-based approach outperformed the empirical
one.Thesis (Ph.D.) -- University of Adelaide, School of Physical Sciences, 202
Application of GNSS Interferometric Reflectometry for Lake Ice Studies
This thesis examines the use of Global Navigation Satellite System Interferometric Reflectometry (GNSS-IR) for the study of lake ice with a particular focus on the estimation of ice thickness. Experiments were conducted in two lake regions: (1) sub-Arctic lakes located near Yellowknife and Inuvik in the Northwest Territories during March 2017 and 2019, and (2) MacDonald Lake, Haliburton, Ontario, which is known as a mid-latitude lake, during the ice season of 2019-2020. For both regions, GNSS-IR results are compared and validated against in-situ ice and on-ice snow measurements, and also with ice thickness derived from thermodynamic lake ice models. In the first experiment, GNSS antennas were installed directly on the ice surface and the ice thickness at each site was estimated by analyzing the signal-to-noise ratio (SNR) of the reflected GNSS signals. The GNSS-IR capability of ice thickness estimation tested on sub-Arctic lakes results in a root mean square error (RMSE) of 0.07 m, a mean bias error (MBE) of -0.01 m, and a correlation of 0.66. At MacDonald Lake, a GNSS antenna was mounted on a 5-m tower on the shore to collect reflected signals from the lake surface. The Least-Squares Harmonic Estimation (LS-HE) method was applied to retrieve higher SNR frequencies in order to estimate the depths of multiple layers within lake ice and the overlaying snowpack. Promising results were obtained from this experiment; however, ice thickness estimation using GNSS-IR at this mid-latitude lake site was found to be highly dependent on the presence or absence of wet layers such as slush at the snow-ice interface and wet snow above that interface. On colder days, when there was a lower chance for the formation of wet layers, ice thickness could be estimated with a correlation of 0.68, RMSE of 0.07 m, and MBE of -0.02 m. In addition, GNSS-IR showed the potential for determining the freeze-up and break-up timing based on the SNR amplitude of reflected signals. The novel work presented in this thesis points to the potential of using reflected signals acquired by recent (e.g. Cyclone Global Navigation Satellite System (CYGNSS) and TechDemoSat-1 (TDS-1)) and future GNSS-R missions for lake ice investigations