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Passive microwave remote sensing is a vital tool for acquiring valuable information regarding the Earth's surface, with significant applications in agriculture, water management, forestry, and various environmental disciplines. Precision agricultural (PA) practices necessitate the availability of field-scale, high-resolution remote sensing data products. This study focuses on the design and development of a cost-effective, portable L-band microwave radiometer capable of operating from an unmanned aircraft system platform to measure high-resolution surface brightness temperature ($T_{B}$). This radiometer consists of a dual-polarized (Horizontal polarized, H-pol and Vertical polarized, V-pol) antenna and a software-defined radio-based receiver system with a 30 MHz sampling rate. The post-processing methodology encompasses the conversion of raw in-phase and quadratic (I&Q) surface emissions to radiation $T_{B}$ through internal and external calibrations. Radiometric measurements were conducted over an experimental site covering both bare soil within an agricultural field and a large water body. The results yielded a high-resolution $T_{B}$ map that effectively delineated the boundaries between land and water, and identified land surface features. The radiometric temperature measurements of the sky and blackbody demonstrated a standard deviation of 0.95 K for H-pol and 0.57 K for V-pol in the case of the sky and 0.39 K for both H-pol and V-pol in the case of the blackbody observations. The utilization of I&Q samples acquired via the radiometer digital back-end facilitates the generation of different time–frequency (TF) analyses through short-time Fourier transform and power spectral density (PSD). The transformation of radiometer samples into TF representations aids in the identification and mitigation of radio frequency interference originating from the instrument itself and external sources.

In this paper, an operational retrieval algorithm is described to infer sea surface temperature (SST) using measurements from the Advanced Microwave Scanning Radiometer-2 (AMSR-2) aboard the Global Change Observation Mission-Water. The algorithm exploits AMSR-2 observations from 12 channels (6–36 GHz, horizontally and vertically polarized), after being corrected for residual calibration biases, to retrieve SST using a statistical based scheme. The Algorithm performance is assessed and results are compared to models and other independent data products. [ABSTRACT FROM PUBLISHER]

We present a new high-fidelity method of calibrating a cross-track scanning microwave radiometer using Global Positioning System (GPS) radio occultation (GPSRO) measurements. The radiometer and GPSRO receiver periodically observe the same volume of atmosphere near the Earth's limb, and these overlapping measurements are used to calibrate the radiometer. Performance analyses show that absolute calibration accuracy better than 0.25 K is achievable for temperature sounding channels in the 50-60-GHz band for a total-power radiometer using a weakly coupled noise diode for frequent calibration and proximal GPSRO measurements for infrequent (approximately daily) calibration. The method requires GPSRO penetration depth only down to the stratosphere, thus permitting the use of a relatively small GPS antenna. Furthermore, only coarse spacecraft angular knowledge (approximately one degree rms) is required for the technique, as more precise angular knowledge can be retrieved directly from the combined radiometer and GPSRO data, assuming that the radiometer angular sampling is uniform. These features make the technique particularly well suited for implementation on a low-cost CubeSat hosting both radiometer and GPSRO receiver systems on the same spacecraft. We describe a validation platform for this calibration method, the Microwave Radiometer Technology Acceleration (MiRaTA) CubeSat, currently in development for the National Aeronautics and Space Administration (NASA) Earth Science Technology Office. MiRaTA will fly a multiband radiometer and the Compact TEC/Atmosphere GPS Sensor in 2015. [ABSTRACT FROM PUBLISHER]

A prerequisite for the successful retrieval of geophysical parameters from remote sensing measurements is the development of an accurate forward model. The European Space Agency Soil Moisture and Ocean Salinity (SMOS), carrying onboard an L-band interferometric radiometer (Microwave Interferometric Radiometer using Aperture Synthesis), was launched on November 2009. Due to the lack of L-band passive ocean measurements from space, several prelaunch forward models were developed and initially used in the SMOS ocean salinity operational processor. In this paper, an update of the prelaunch semi-empirical forward model is presented, using for the first time, real SMOS data. In particular, the ocean surface emissivity modulation at L-band due to rough sea surface is reviewed and reanalyzed. A new model definition is provided with the help of a simple neural network. The improvement is quantified in terms of retrieved salinity accuracy compared with the climatology and concerns essentially the range of wind speeds higher than 12 m·s-1. [ABSTRACT FROM AUTHOR]

Ten underflights of the Special Sensor Microwave Imager/Sounder (SSMIS) with Conical Scanning Millimeter-wave Imaging Radiometer (CoSMIR) onboard the NASA ER-2 aircraft were conducted over the coastal region of California between March 2004 and March 2005. The measured brightness temperature (Tb) values from both sensors are collocated and compared at frequencies of 50.3, 52.8, 53.6, 91.655, 150, 183.3 ± 1,183.3 ± 3, and 183.3 ± 6.6 GHz. The more transparent channels at 50.3, 91.655, and 150 GHz are strongly affected by the changes in surface emission and low-level liquid clouds. Thus, the average differences in Tb values (δTb), measured by the two sensors, and their changes from flight to flight are difficult to assess. For the remaining opaque channels, using the CoSMIR measurements as reference, the lowest SSMIS Tb values occur when the SSMIS is completely under the Earth's shadow. As the satellite moves out of the Earth's shadow in the ascending passes, the SSMIS Tb values are found to gradually increase with more exposure to the sun. The magnitudes of these Tb changes are about 4-5 K for the three 183.3-GHz channels and about 2 K for the 52.8- and 53.6-GHz channels. [ABSTRACT FROM AUTHOR]