This paper gives a summary of the HydroGNSS mission and status in the preparations up to launch. Some of the advancements in instrument are presented, including on-board gain adjustment, geolocation. Also the ground processing Payload Data Ground Segment is introduced and some of the processing advances, including antenna pattern modelling for EIRP estimation and bounding of measurement areas.

Seasonal snow cover is an important environmental component, as its characteristics affect energy and gas exchange between ground and the atmosphere. The mass of seasonal snow cover, or Snow Water Equivalent (SWE), describes the available freshwater stored in snow. When present, snow cover affects the microwave signature of the scene and should therefore be considered in any microwave based remote sensing model and retrieval algorithm. Microwave remote sensing of snow and its properties has a long history, and in particular SWE has traditionally been retrieved by using passive microwave observations at 19 and 37 GHz [1] , [2] .

Recent applications of passive L-band observations from space are summarized for ocean, land surface and cryosphere applications. The main limitation of the measurements performed by the current generation of sensors is the spatial resolution. The need of a mission ensuring the continuation of L-band measurements from space with high spatial resolution (10-15 km) is discussed.

HydroGNSS is the second mission supported by the European Space Agency (ESA) under the Scout program, which is a new framework (3 years from KO to launch, cost ≤ 30 M€) by which ESA aims to demonstrate disruptive sensing techniques or incremental science, while retaining the potential to be subsequently scaled up in larger missions or implemented in future ESA Earth Observation programmes. HydroGNSS consists of a scientific demonstrator that primarily addresses land bio-geophysical variables. The mission is comprised of one satellite (with an option on the second) flying at a low-Earth orbit to collect Global Navigation Satellite System reflections (i.e., Delay Doppler Maps, DDMs) near continuously over the globe. The DDMs are used to generate Level 2 products related to Essential Climate Variables (ECV s), whose estimation defines the primary scientific goal of the mission. In this contribution we outline a review of the ECVs targeted by HydroGNSS, showing some representative results achieved during preliminary studies about the mission. Special emphasis is given to the monitoring of soil freeze-thaw state and soil moisture. ECVs are of great interest and support the sustainable development agenda adopted by the United Nations members in 2015.

Monitoring freeze/thaw variations of the Earth surfaces is of paramount importance for the study of biogeochemical processes and climate change. At present, the use of passive sensors is well established, but, very recently, some studies demonstrated the potentialities of observations exploiting signals of opportunity. We propose here an advanced study to demonstrate the capability of spaceborne Global Navigation Satellite System Reflectometry (GNSS-R) to provide accurate and systematic information about the Earth-surface freeze/thaw state. Reflectivity values derived from TechDemoSat-1 (TDS-1) data are elaborated and compared against the Soil Moisture and Ocean Salinity (SMOS) freeze/thaw product, while state-of-the-art land cover data are used to select GNSS-R data within an estimated footprint. In spite of the limited data availability due to sparse spatial coverage and calibration issues of TDS-1 observations, the proposed analysis demonstrates the possibility of monitoring the freeze/thaw state by analyzing the calibrated reflectivity, including also the possibility of detecting the transition state between frozen and thawed conditions across seasonal variations. This feature makes the design of next-generation GNSS-R satellite missions a unique opportunity to achieve high-resolution freeze/thaw monitoring with small and low-cost platforms.

A tower-based global navigation satellite system reflectometry (GNSS-R) experiment is set up in an Arctic wetland environment for investigating the possibility of monitoring wetland inundation and freeze/thaw (FT) dynamics which are additionally impacted by snow on the ground. Effects of inundation, snow cover, and soil FT state on observed GNSS-R signal-to-noise ratios (SNRs) are analyzed for horizontal (H) and vertical (V) polarizations. A simple classification approach is suggested to detect the inundated, frozen, or thawed soil state. A simple forward reflectivity model is formulated to evaluate the influence of snow cover, overlying frozen, or thawed soil, on the reflected GNSS signals. Reflectivity time series are simulated in H- and V-polarizations usingin situobservations of the Arctic wetland site. The simulations are used to verify the tower-based observations, which show a significant impact of wet snow on reflectivity during melting conditions in spring. The observed SNR is strongly correlated with the Sentinel-1 backscatter coefficient. Generally, soil states detected by GNSS-R are in high agreement with ground truth soil states, especially for inundated and frozen soils. Wet snow conditions, however, complicate the correct timing estimation of soil thawing by inducing reflectivities of a similar order as thawing soil. It is recommended that GNSS-R land application models and retrieval algorithms consider snow cover effects to reduce false classification, especially in FT detection. Overall, the outcome of this study is relevant to the upcoming ESA HydroGNSS mission.

Monitoring freeze/thaw variations of the Earth surfaces is of great value for the study of biogeochemical processes and climate changes. Over the last decade, the use of passive sensors has been established and, more recently, some researches demonstrated the potential of exploiting observations based on signals of opportunity. We propose an advanced study to assess the capability of spaceborne Global Navigation Satellite System Reflectometry (GNSS-R) to give systematic information about the soil freeze/thaw state of high-latitude regions. To this aim, reflectivity values derived from TechDemoSat-1 (TDS-1) data are elaborated using state-of-art land cover data.

This paper presents a new approach for monitoring soil frost in the northern boreal forest region using co-polarized C-band synthetic aperture radar (SAR) data. Due to the high sensitivity of the C-band signal to vegetation, estimating the soil freeze/thaw (F/T) state directly from the measured backscatter is not feasible over dense vegetation, such as boreal forests. The presented method is based on applying a simple zeroth-order model to estimate the contribution of the ground and the forest canopy on the observed total backscatter. The retrieved ground and canopy backscatter values were compared with in situ information on soil F/T state. By using a linear least sum of square errors classification algorithm, the retrieved ground and canopy backscatter values representing frozen and thawed ground were successfully separated. The method was tested for various soil types and incidence angles. For soil types with higher water holding capacities and lower infiltration rates such as fine Haplic Podzol and Umbric Gleysol, the estimation accuracy of the F/T state was over 97%, whereas for drier, well-drained soil types such as Haplic Arenosol and Coarse Haplic Podzol it was over 94%. Estimation accuracy slightly increased with higher incidence angle. The method is not feasible in rocky terrain due to very low water content, or in wet snow conditions due to lack of penetration of the C-band SAR signal through wet snow. With low ancillary data and computational requirements, the proposed method is applicable for continuous near real-time monitoring of soil F/T state.

The Finnish Meteorological Institute (FMI) operates a suite of ground-based active and passive microwave instruments at a test site representative of the Northern boreal forest zone. The instruments provide hourly to daily multifrequency observations of microwave signatures from the natural landscape throughout the year. Supported by comprehensive in situ observations of soil, vegetation, snow and atmospheric conditions, the data enable testing and formulation of new methods to retrieve geophysical parameters from remote sensing data. Complementing ground-based observations, airborne campaigns have been used to extend the spatial scale of observations to cover different types of terrain. In this paper an overview of the site and instrumentation is given, giving examples of recent campaigns and use of the collected data in the development of new Earth Observation methods. All data, including the raw data observations, are available for research purposes from FMI.

Earth's cold regions are key elements of the planet's climate system: they have strong feedbacks with global change and they have a direct impact on human activities. Despite their importance, at present they are not adequately monitored by state-of-the-art instruments. In order to fill this gap, a dedicated spaceborne mission called Cryorad has been proposed in the framework of the ESA Earth Explorer 10 call. The mission would comprise a 0.4-2 GHz nadir-looking radiometer installed on a polar-orbit satellite. Scientific and technical studies are underway, as well as experimental campaigns in Greenland and Antarctica.

The Finnish Meteorological Institute, together with Gamma Remote Sensing, Switzerland, has developed a global soil freeze/thaw detection algorithm using passive L-band microwave observations from the European Space Agency's Soil Moisture and Ocean Salinity (SMOS) mission. The current product gives the soil state as “frozen”, “partially frozen”, or “thawed”. Estimates for a given season are derived after each winter period. An operational product with a latency of one day is under development. Global information on soil freezing and thawing has many applications; e.g. in evaluation or as an input prior in carbon and climate models, soil carrying capacity analysis, and hydrological models.

A synergistic method for obtaining soil permittivity and soil frost was developed. The method incorporates a semiempir-ical backscattering model for forested land. Soil permittivity is retrieved from active microwave observations using least squares inversion method. Bayesian assimilation scheme can be applied to combine the active retrieval with a permittivity estimate from a passive instrument. Soil frost can be determined from permittivity estimates using a threshold method. The synergistic method was tested on boreal forest site in Northern Finland using ASAR for active and SMOS for passive observations. Satellite retrievals were compared to in situ soil permittivity, temperature and frost measurements. The results show that high resolution SAR data (e.g., ASAR, Sentinel) can be used to downscale coarse resolution SMOS estimates and that synergistic method reduces variability and biases of the ASAR retrieval.

There is a long-stranding need of reliable space-borne observations on snow mass. Current satellite sensors and data products are largely unable to meet requirements presented in particular by numerical prediction and watershed management. Consequently, several concept studies have been initiated to address these specific needs, outlining possibilities for future space sensors focusing on retrieval of snow mass and other characteristics of the terrestrial cryosphere. The results of these of-going mission concept studies are presented and discussed. Several possible sensor options are presented, which would address diverse needs on either hemispheric or regional scales.

Recent theoretical and experimental studies have indicated the feasibility of passive microwave L-band observationsfor observing dry snow cover characteristics, namely snow density in the lower approx.. 10 cm of the snowpack. The sensitivity of L-band emission to snow density is based on the dual influence of refraction and impedance matching on observed brightness temperature with changing effective snow permittivity. The permittivity of pure, dry snow, on the other hand, depends largely on snow density. In this study, we expand the theoretical and experimental results of retrieving dry snow density to passive L-band satellite observations. Such retrievals could be appealing in the context of improving satellite based retrievals of e.g. Snow Water Equivalent (SWE) using other sensors. Retrievals are applied to both multi-angular observations from the ESA SMOS mission, and observations of the NASA SMAP radiometer on a single angle of observation. While in theory the multi-angular approach is preferable, improved RFI mitigation in SMAP provides more spatially and temporally more stable retrievals. The applied dual-parameter retrieval scheme produces also an estimate of ground permittivity; experimental data showed dry snow cover to have a clear influence on ground permittivity retrievals, implicating that even dry snow cover is non-negligible also in retrievals of soil moisture from L-band observations.

Dry snow is conventionally considered as having minimal effect on microwave radiation at long wavelengths (such as L-band). However, dry snow affects observed microwave signatures even at these wavelengths through changes in impedance matching between soil and the overlying media, as well as through changes in the refraction angle at the soil interface. Exploiting these effects, the multi-angular, dual-polarized L-band observations of e.g. the European Space Agency's SMOS (Soil Moisture and Ocean Salinity) mission have the potential to derive snow properties, such as the density of the lowest layers of the snowpack in contact with the ground. This in turn, would have the potential to inform retrieval schemes of snow cover based on EO-data from other sensors. In addition, the theoretical studies demonstrate that the effect of dry snow on retrieval of other geophysical variables, such as soil moisture, is not negligible. In this study, we demonstrate the simultaneous retrieval of snow density and ground permittivity in dry snow conditions, using a multi-year dataset of tower-based L-band observations. We show that following predictions of the theoretical studies, the retrieved snow density matches that of the density measured for the lowest snow layers; dry snow cover is also shown to affect retrievals of ground permittivity by up to 40 %.

The launch of the European Space Agency (ESA)'s Soil Moisture and Ocean Salinity (SMOS) satellite mission in November 2009 opened a new era of global passive monitoring at L-band (1.4-GHz band reserved for radio astronomy). The main objective of the mission is to measure soil moisture and sea surface salinity; the sole payload is the Microwave Imaging Radiometer using Aperture Synthesis. As part of comprehensive calibration and validation activities, several ground-based L-band radiometers, so-called ETH L-Band radiometers for soil moisture research (ELBARA-II), have been deployed. In this paper, we analyze a comprehensive set of measurements from one ELBARA-II deployment site in the northern boreal forest zone. The focus of this paper is in the detection of the evolution of soil frost (a relevant topic, e.g., for the study of carbon and methane cycles at high latitudes). We investigate the effects that soil freeze/thaw processes have on the L-band signature and present a simple modeling approach to analyze the relation between frost depth and the observed brightness temperature. Airborne observations are used to expand the analysis for different land cover types. Finally, the first SMOS observations from the same period are analyzed. Results show that soil freezing and thawing processes have an observable effect on the L-band signature of soil. Furthermore, the presented emission model is able to relate the observed dynamics in brightness temperature to the increase of soil frost.

This paper discusses the development of the airborne synthetic aperture radiometer HUT-2D of Aalto University. We present the life cycle of the project starting from its initiation, highlighting the main milestones and achievements in hardware development, interferometric algorithm validation, and finally in airborne campaigns. We point out the most important lessons learned from especially the hardware development history and discuss the overall performance and usability of the instrument. With these lessons learned we sketch an easy-to-implement, cost-effective redesign of the HUT-2D instrument. This redesign focuses on issues that would produce improvements, which are the most beneficiary in terms of the instrument's ability to make scientific measurements.

The acquisition of Snow Water Equivalent (SWE) at spatial resolutions higher than those of the present methods relying on inversion of coarse-scale passive microwave observations is a possible application for space-borne SAR imagery. The presented experimental campaign NoSREx (Nordic Snow Radar Experiment) was initiated to contribute to the knowledge of snowpack backscattering and emission properties, in particular, to help develop methods to retrieve SWE from high-resolution two-frequency SAR observations (at X and Ku band). Another objective was to provide data for studies exploring the synergistic use of active and passive microwave observations for monitoring of snow properties. The NoSREx campaign began in November 2009, and has recently concluded a second winter period of observations.

Annually large areas of northern hemisphere freeze and are covered with snow. This paper presents results from synthetic aperture radiometer measurements of soils in unfrozen and frozen state and examines changes in their L-band emissivity.

L-band radiometry is widely considered the best technique for Earth observing satellites to measure sea surface salinity (SSS). Interferometric aperture synthesis is a new technology applicable in spaceborne remote sensing at low frequencies. The challenge of the technology comes with decreased radiometric resolution and complexity in calibration compared to conventional radiometer systems. Due to these issues and the overall newness of the concept, validation of the technology for salinity retrieval purposes is desired. In this paper, we describe an intense measurement campaign carried out with the complete interferometric aperture synthesis radiometer system HUT-2-D, designed and operated by the Helsinki University of Technology. The campaign aimed at the detection of a changing salinity level in the Baltic Sea, in the coastal areas of Finland. We describe the campaign comprising details of the ground truth collection, sea surface emission modeling, and radiometric data analysis. We have a special emphasis on the assessment of the impact of the sea state on the radiometric measurements, which is considered one of the major obstacles for SSS retrieval at the L-band. For this purpose, we present a new correlation between sea roughness information collected with the Global Navigation Satellite System reflectometer and radiometric data measured by an L-band radiometer system.

This paper describes the analysis of L-band radiometric measurement data gathered with the synthetic aperture radiometer HUT-2D during several ground-based and airborne measurement campaigns. The radiometric data are analyzed from the instrument's performance point of view, aiming to verify the theoretical performance of an instrument of this kind and to assess the performance of the HUT-2D radiometer system in particular. The data sets considered for the study consist of measurements of well-known natural targets, such as cosmic background radiation, and measurements of pure water scenes, the brightness temperature of which is possible to model based on in situ measurements. We define four figures of merit, which are applicable for synthetic aperture radiometers. These are radiometric resolution, image bias, pixel-to-pixel random error, and temporal stability. Then, we use the selected data sets to assess these in the case of HUT-2D. The experimental results are discussed and compared to the theoretical values, where applicable. Also, we discuss possibilities to improve the presented performance. The main results of this paper are the consolidated performance parameters of the HUT-2D instrument. We study and discuss the properties of the error components related to the technology in a general level, and study the scalability of the errors as a function of the measured targets. In particular, the stability of the direction-dependent error component is pointed out, and a mitigation guideline is proposed.

Potential radio frequency interference (RFI) sources at L-band include L-band radars; mobile, navigation and other satellite services; and various land services. We have collected data using our airborne L-band interferometric HUT-2D radiometer in order to support the ESA SMOS mission. We participated in April-May 2008 in ESA's rehearsal campaign for SMOS satellite validation activities in Germany and Spain. Additional data have been collected in Finland. Two basic categories of RFI have been observed: (1) Point-wise weak sources that do not saturate the HUT-2D instrument, and (2) strong sources that totally saturate the sensor over a large area.

In this paper we present calibration and validation activities of European Space Agency's SMOS mission, which utilize airborne interferomentric L-band radiometer system HUT-2D of the Aalto University. During spring 2010 the instrument was used to measure three SMOS validation target areas, one in Denmark and two in Germany. We present these areas shortly, and describe the airborne activities. We show some exemplary measurements of the radiometer system and demonstrate the studies using the data.

The successful launch of the European Space Agency's (ESA) Soil Moisture and Ocean Salinity (SMOS) satellite mission on November 2nd 2009 opened a new era of global monitoring with L-band passive microwave instruments. The main objective of the mission is to measure soil moisture and sea surface salinity globally. The sole payload of SMOS is the Microwave Imaging Radiometer using Aperture Synthesis (MIRAS). In this paper we compare the first SMOS measurements over a sub-Arctic boreal forest area with tower-based and airborne reference data. Our main interest is the evolution of the boreal soil frost, since it has a large impact on the carbon cycle in the Arctic region.

Interferometnc aperture synthesis is a new technology proposed for space-borne remote sensing of sea surface salinity. In the lack of availability of a complete instrument of this kind, validation of the technology for salinity retrieval purposes is desired. In this paper we describe an intense measurement campaign carried out with a complete interferometnc aperture synthesis radiometer system HUT-2D. The campaign aimed for the detection of a changing salinity level in the Baltic Sea. We have a special emphasis on the assessment of the impact of sea state on the radiometnc measurements, which is considered one of the major obstacles for sea surface salinity retrieval at L-band. For this purpose we study sea roughness information collected with Global Navigation Satellite System Reflectometer.

We have studied usage of our airborne L-band 2-D synthetic aperture radiometer HUT-2D for estimation of soil moisture. Measurements were conducted over three sites in Northern and Southern Finland in August 2007. Good results were achieved for bare soil and low vegetation, whereas soil moisture retrieval for forested areas requires further studies.

During the last two decades, the development of synthetic aperture radiometers for remote sensing has been studied intensively. One of the proposed methods for the calibration of such an instrument is the application of a distributed noise injection network. This paper focuses on the origin and effect of errors arising from this methodology. A generalized analytical method to calculate the accumulation of phase and amplitude errors in a distributed noise injection network is presented. This method is then applied to the Microwave Imaging Radiometer using Aperture Synthesis (MIRAS), the interferometric radiometer aboard the European Soil Moisture and Ocean Salinity satellite. The effect of the resulting errors to MIRAS' brightness temperature is analyzed. The presented method is applicable also to other interferometric radiometers, whose calibration relies on distributed noise injection.

An airborne L-band 2-D interferometric radiometer for Soil Moisture and Ocean Salinity (SMOS) measurements has been developed in the Helsinki University of Technology, Laboratory of Space Technology. The first successful flights were conducted in spring 2006. In this paper, the technical description, calibration, and image reconstruction philosophy and the latest results from the use of the instrument are discussed. One of the key goals of the instrument design has been to acquire L-band interferometric data to support the European Space Agency's SMOS mission that employs the L-band interferometric radiometer Microwave Interferometric Radiometer using Aperture Synthesis. Both instruments use aperture synthesis technology for the target image reconstruction in two dimensions.

Ground calibration of the calibration subsystems of MIRAS (Microwave Imaging Radiometer using Aperture Synthesis) has been performed. The MIRAS instrument is the payload of European Space Agency's (ESA) Soil Moisture and Ocean Salinity (SMOS) mission. The calibration subsystems are Calibration Subsystem (CAS), which is a noise distribution network, and Noise Injection Radiometer (NIR), which measures the noise levels of CAS and the average incident brightness temperature. This paper presents the used measurement approaches, related uncertainties, and the calibration results for the NIR and CAS. The results show that in spite of uncertainties, the characterization methods allow accurate ground calibration of the two subsystems. The performance of both subsystems meet the requirements.

This paper describes a test campaign carried out with synthetic aperture radiometer HUT-2D to establish understanding to the instrument's radiometric performance. The test campaign consists of measurements of the radiation from the sky, which is considered as a well-known target, and measurements of a pure sea water scene, which brightness temperature is possible to model. Results of the tests are used to address instrument's radiometric sensitivity and radiometric resolution. The experimental results are discussed and compared to the theoretical values, where applicable.

In this paper, the thermally stabilized front-end of an L-band total power receiver is presented. Applications on the L-band have become one of the most important focus points in the field of passive microwave remote sensing. Measuring environmental parameters such as ocean salinity and soil moisture remain a challenge, posing strict requirements to instrument performance. For traditional radiometers, especially the stability of front-end components is critical. The principle of the stabilization technique and the actual design are described. The design also features an on-board active cold load for calibration purposes. The presented technique aims to stabilize the front-end section PCB with heaters to sub 0.05 C level.

Helsinki University of Technology (TKK), Laboratory of Space Technology has developed an airborne two dimensional synthetic aperture radiometer for remote sensing purposes. The radiometer - called HUT-2D - measures the ground target using L-band channel reserved for radio astronomy. Main interests are in soil moisture (SM) and sea surface salinity (SSS) monitoring. The instrument is similar with the European Space Agency's (ESA) SMOS (Soil Moisture and Ocean Salinity) mission MIRAS (Microwave Imaging Radiometer by Aperture Synthesis) instrument. The HUT-2D instrument will be used in SMOS mission calibration and validation activities. Already, the development work of the HUT-2D instrument has given valuable information to the SMOS project. This paper describes the instrument and presents example airborne measurements in Finnish coastal zone.

The Helsinki University of Technology has recently finished the construction of a 2-D airborne aperture synthesis radiometer and conducted a successful test flight with the complete instrument. During the test flight, a number of different brightness temperature sources were measured to examine the instrument's stability, electromagnetic compatibility issues, calibration methods, and image reconstruction algorithm. A set of images from this first test flight is presented, and their main features are discussed

Interferometric radiometry is a novel concept in remote sensing that is also presenting particular challenges for calibration methods. In this paper, we describe the calibration subsystem (CAS) developed for the Microwave Imaging Radiometer using Aperture Synthesis (MIRAS) interferometer of the Soil Moisture and Ocean Salinity (SMOS) satellite. CAS is important for the overall performance of the payload as it calibrates out the differences between the multiple receivers of MIRAS. SMOS is in the final phase of development and is due to launch in 2008.

End-to-end calibration of the Microwave Imaging Radiometer by Aperture Synthesis (MIRAS) radiometer refers to processing the measured raw data up to dual-polarization brightness temperature maps over the earth's surface, which is the level 1 product of the Soil Moisture and Ocean Salinity (SMOS) mission. The process starts with a self-correction of comparators offset and quadrature error and is followed by the calibration procedure itself. This one is based on periodically injecting correlated and uncorrelated noise to all receivers in order to measure their relevant parameters, which are then used to correct the raw data. This can deal with most of the errors associated with the receivers but does not correct for antenna errors, which must be included in the image reconstruction algorithm. Relative S-parameters of the noise injection network and of the input switch are needed as additional data, whereas the whole process is independent of the exact value of the noise source power and of the distribution network physical temperature. On the other hand, the approach relies on having at least one very well-calibrated reference receiver, which is implemented as a noise injection radiometer. The result is the calibrated visibility function, which is inverted by the image reconstruction algorithm to get the brightness temperature as a function of the director cosines at the antenna reference plane. The final step is a coordinate rotation to obtain the horizontal and vertical brightness temperature maps over the earth. The procedures presented are validated using a complete SMOS simulator previously developed by the authors.

A complete and systematic noise analysis of radiometer front-ends, including both total power and correlation measurements, is presented. The procedure uses the concepts of noise waves and S-parameters, widely used in microwave systems design and takes into account full noise characterization of receivers including mismatch effects. The general formulation is compatible with known total power radiometer analysis and is specially appropriate in correlation radiometers for which the effect of nonideal components, such as input isolators, is analyzed. Along with numerical simulations, simple formulas are given to compute the measured visibility in nonideal conditions. The analysis is validated using experimental results consisting of correlation measurements of four receivers placed inside an anechoic chamber. Good agreement between theoretical predictions and experimental data is observed.

A complete systematic analysis of correlation radiometer front-ends is presented. It takes into account full noise characterisation of the individual receivers and mismatch effects between different subsystems. The results are applied to the case where the front-ends include input isolator both ideal and imperfect. Along with numerical simulations, simple formulas are given to compute the visibility in these conditions, which is here defined as system visibility. The analysis is validated using experimental results consisting of correlation measurements of four receivers placed inside an anechoic chamber. Good agreement between theoretical predictions and experimental data is observed

An L-band airborne radiometer using two-dimensional aperture synthesis (HUT-2D) is under development in Helsinki University of Technology (HUT) for remote sensing. The low measurement frequency is suitable for soil moisture and sea surface salinity measurements. The instrument's technical characteristics are similar to those of the European Space Agency's (ESA) SMOS) (Soil Moisture and Ocean Salinity) satellite instrument in order to support ESA in satellite mission instrument development work. The HUT-2D instrument overview and recent test results are presented in this paper.