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High resolution synthetic aperture imaging using rotating fan-beam scatterometers is studied. First, the working mode is presented. Then, the relationships among pulse repetition frequency, the number of coherent pulses and the unambiguous swath are discussed. Considering the sparsity of the imaging region and the limited number of pulses, we adopt the sparse recovery method to obtain the target images...
High accuracy of impact height is important to get reliable Radio Occultation (RO) measurements of the atmosphere refractivity. We have made an investigation on how accurately we can measure the impact height at ground level using wave optics simulations, realistic refractivity profiles, a realistic simulator for an advanced RO instrument including noise, and using phase matching for the inversion...
The vertical electron density distribution can have a significant impact on ionospheric measurements of Total Electron Content (TEC) derived from estimates of Faraday rotation (FR) with spaceborne low-frequency SAR data. Using vertical electron density data and the IGRF-12 magnetic field model, simulations of FR under different vertical electron density distributions for an L-band SAR have been performed...
Monitoring of agricultural used soils at frequent intervals is needed to get a better understanding of processes like soil erosion or harvest forecast. This is crucial to support decision making and refining soil policies especially in the context of climate change. Parcel-specific soil coverage information can be derived by satellite imagery with high temporal and geometric resolution. However, their...
We present model and measurement results for time-series C-band normalized radar cross-sections (NRCS) over first-year snow-covered sea ice during a winter-spring transition period. Experimental scatterometer and physical data were collected near Cambridge Bay, Nunavut, Canada between May 20 and May 28, 2014 covering a severe storm event on May 25. We observed good agreement between model and experimental...
In this paper we investigate the use of discriminative model learning through Convolutional Neural Networks (CNNs) for SAR image despeckling. The network uses a residual learning strategy, hence it does not recover the filtered image, but the speckle component, which is then subtracted from the noisy one. Training is carried out by considering a large multitemporal SAR image and its multilook version,...
PALSAR-2 on ALOS-2 developed by JAXA, is a follow-on L-band SAR sensor from PALSAR on ALOS. The mission objectives defined by JAXA include contribution to disaster monitoring. To establish the methodology to acquire the damaged area for disaster monitoring, we need to improve our understanding of the relationships between the sensor parameters (e.g., coherence and errors of the interferogram) and...
Prediction of sea ice motion is important for ocean-atmosphere interaction modeling and safe naval operations in polar regions. In this study, we investigate the potential of Recurrent Neural Networks (RNNs) in predictions of motion for several days in the future based only on previously observed satellite image data. We collect a large dataset of daily Advanced Microwave Scanning Radiometer — Earth...
Leaf area index inversion using remote sensing is crucial for obtain vegetation information and monitoring global climate change. For the invalid uniform continuous canopy hypothesis of SAIL model, fractional canopy cover (FCC) is introduced and a simultaneous retrieval method of LAI and FCC is developed. SAIL model, PSO algorithm, and linear spectral mixture theory are combined in the novel method...
Circularly polarized (CP) synthetic aperture radar (SAR) is a recent state of art SAR that adopts CP-antennas on both a transmitter and a receiver (end-to-end circular polarization). For use of this SAR configuration practically and precisely, in this paper, we propose two types of point target-based polarimetric calibration methods modified by existing calibration for the linearly polarized (LP)...
Due to the launch of a number of dedicated GNSS-R satellite missions during the last years, there is a potential raise of research interest in this field. This paper presents an analysis and simulation tool for the GNSS-R community: wavpy. More than just a simple waveform simulator, this library provides a set of object-oriented classes dedicated to each of the different elements that characterize...
The NASA Soil Moisture Active Passive (SMAP) mission aims to disaggregate L-band microwave brightness temperatures (∼40 km2) with finer resolution radar backscatter (1–3 km2) to obtain an intermediate resolution soil moisture product. The disaggregation is based on a linear functional relationship between backscatter and emissivity microwave observations that is captured by a covariation parameter...
Non-Gaussian statistical models fit SAR data better than Gaussian-based statistics, in most cases, but are complicated and time-consuming to use for unsupervised image segmentation via probabilistic clustering. The more advanced the model, the more complicated and slow the clustering. The U-distribution has been demonstrated to be one of the most flexible models, capturing the Gaussian/Wishart, the...
Polarimetric Synthetic Aperture Radar (PolSAR) images are an important source of information. Speckle noise gives SAR images a granular appearance that makes interpretation and analysis hard tasks. A major issue is the assessment of information content in these kind of images, and how it is affected by usual processing techniques. We study this problem from the classification accuracy viewpoint. Our...
After over two decade of efforts, many land products are now being produced systematically from a variety of satellite data, and these products have been widely used. However, estimating a set of atmospheric and surface variables from one sensor data is often an ill-posed inversion problem, because the number of unknowns is often larger than the available bands[1]. Thus, one has to make assumptions...
In recent years, CubeSats have emerged as a platform of intense interest for a wide range of applications, including remote sensing. Of specific interest in this paper are data processing challenges associated with the MIT's Microwave Atmospheric Satellite (MicroMAS). Due to the motion of MicroMAS and the geometry of the data acquisition process, measurements are not collected on a regular grid of...
Over the last decade, the number of missions including hyperspectral cameras of increasing resolution has grown considerably. Traditional compression techniques have been proposed as an efficient way to store and transmit the ever increasing amount of hyperspectral data and to cope with the limited transmission bandwidth between the onboard systems and the ground stations. On the other hand, compressive...
This paper addressed the retrieval of land surface temperature (LST) from combined mid-infrared and thermal infrared data of the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-Orbiting Partnership (S-NPP). To efficiently remove the effect of the direct solar radiance, a relationship between direct solar radiance and water vapor content, view zenith angle and solar...
To facilitate understanding of the relationship between the most significant greenhouse gas carbon dioxide and human activities, we have developed a differential absorption lidar (DIAL) detection system at 1.57 μm. The goal of this lidar system is to detect the temporal and spatial distribution of atmospheric carbon dioxide gas from 0.3 km to 3 km in the atmosphere. Beginning in 2009, the system was...
In this paper we investigate the double bounce enhancement due to standing water in flooded agricultural fields to assess the capability of an X-band radar to recognize the presence of floodwater under vegetation. The investigation was carried out by analyzing a polarimetric and multifrequency SAR dataset (COSMO-SkyMed, Alos-2, Radarsat-2) collected over the Vercelli district in North Italy, characterized...
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