Synthetic Aperture Radar (SAR) images can be extensively informative owing to their resolution and availability. However, the removal of speckle-noise from these requires several pre-processing steps. In recent years, deep learning-based techniques have brought significant improvement in the domain of denoising and image restoration. However, further research has been hampered by the lack of availability of data suitable for training deep neural network-based systems. With this paper, we propose a standard synthetic data set for the training of speckle reduction algorithms.


In Virtual SAR we have infused images with varying level of noise, which helps in improving the accuray fo blind denoising task. The holdout set can be created using images from USC SIPI Aerials database and the the provided matlab script (preprocess_holdout.m) tested on Matlab R2019b.


The usage for research purposes is for free. If you use this dataset, please cite the following paper along with the dataset: Virtual SAR: A Synthetic Dataset for Deep Learning based Speckle Noise Reduction Algorithms


This dataset includes binary files of radiometric measurement sessions 2018-2019. Measurements of microwave descending radiation in the band of resonance absorption of water vapor 18 - 27.2 GHz were performed. The observations were carried out by means of special microwave multichannel (47 channels) radiometer-spectrometer developed in Kotel'nikov Institute of Radioengineering and Electronic of RAS Special Design Bureau. Radiometer was located in Fryazino, Moscow Region, Russian Federation.


This dataset accompanies a paper titled "Detection of Metallic Objects in Mineralised Soil Using Magnetic Induction Spectroscopy". 


Every sweep of the detector over an object is contained in a different file, with the following file naming convention being used: ___.h5, where is globally unique identifier for the file. Each file is a HDF5 file generated using Pandas, containing a single DataFrame. The DataFrame contains 8 columns. The first three correspond to the x-, y- and z-position (in cm) relative to an arbitrary datum. The arbitrary datum stays constant for all sweeps over all objects in a given combination of soil and depth. The other 5 columns contain the complex transimpedance values as measured by the MIS system, after calibration against the ferrite piece. Due to experimental constraints, there is no data for one of the rocks buried at 10 cm depth in "Rocky" soil.


We collected experimental field data with a prototype open-ended waveguide sensor (WR975) operating between 600 MHz - 1300 MHz. With our prototype sensor we collected reflection coefficient measurements at a total of 50 unique 1-ft^2 sites across two separate established cranberry beds in central Wisconsin. The sensor was placed directly on top of cranberry-crop bed canopies, and we obtained 12 independent reflection coefficient measurements (each defined as one S11 sweep across frequency) at each 1-ft^2 site by randomly rotating and/or translating the sensor aperture above each site. After


PS_DISP is a trial bundled script written on bash shell and Matlab code. The script requires Generic Mapping Tools (GMT) and Matlab Software and runs under Linux operating system. The purpose of PS DISP is to generate 2D or 3D vectors displacement from InSAR both ascending and descending orbit either from the mean velocity or time-series data. The 1.5 beta version includes the computation of the 3D field using an optimized approach with variance component estimation (VCE).


The downloadable files contain all data and associated scripts that generate results as seen in the article. The major component description and detailed setup and run instructions are also provided in the README file.


The project is conceptualized to 'Geo Web-Based Facility Mapping for Zone-2 in Greater Visakhapatnam Municipal Corporation- GVMC in Visakhapatnam, India'. The main objective is to share the spatial data to the public to help them find the information about the nearest Hospital, ATM, Educational institutions, petrol filling stations, and supermarkets by providing both web map services and web coverage services using QGIS Cloud.


Accurate information about crop rotation is essential for administrators, managers and various government departments for assessment, monitoring, and management of various resources for crop escalation. Radar remote sensing, because of its all-weather capability and assured uninterrupted data supply can show a substantial part in the evaluation of crop rotation.


The endmembers of a hyperspectral image (HSI) are more likely to be generated by independent sources and be mixed in a macroscopic degree before arriving at the sensor element of the imaging spectrometer as mixed spectra.


 This data package is parepared by Dr. Jianguo Niu (IMSG at NOAA NESDIS/STAR) on

        March 18, 2020


 The purpose of this OMPS LFSO2 retrieval products package is in support the paper:

 "Evaluation and Improvement of the Near-real-time Linear Fit SO2 retrievals from Suomi NPP (S-NPP) Ozone Mapping & Profiler Suite"


This package includes LFSO2 V8TOS retrievals of:

        1. "logic swith on" (original set as described by th paper 01824) products


 This data are in NetCDF format. Which can be read by an IDL code "". The usage example




The "data" is a structure, which included most of the parameters you needed.