Geoscience and Remote Sensing

This dataset was created from all Landsat-8 images from South America in the year 2018. More than 31 thousand images were processed (15 TB of data), and approximately on half of them active fire pixels were found. The Landsat-8 sensor has 30 meters of spatial resolution (1 panchromatic band of 15m), 16 bits of radiometric resolution and 16 days of temporal resolution (revisit). The images in our dataset are in TIFF (geotiff) format with 10 bands (excluding the 15m panchromatic band).


This dataset extends the Urban Semantic 3D (US3D) dataset developed and first released for the 2019 IEEE GRSS Data Fusion Contest (DFC19). We provide additional geographic tiles to supplement the DFC19 training data and also new data for each tile to enable training and validation of models to predict geocentric pose, defined as an object's height above ground and orientation with respect to gravity. We also add to the DFC19 data from Jacksonville, Florida and Omaha, Nebraska with new geographic tiles from Atlanta, Georgia.


This dataset includes the following data in supporting the submitted manuscript 'Datacube Parametrization-Based Model for Rough Surface Polarimetric Bistatic Scattering' to IEEE Transactions on Geoscience and Remote Sensing. 

  • LUT of coefficient c from fitting the contour level bounds
  • LUT of coefficient c from fitting the contour center shifts
  • specular scattering coefficients from the SEBCM simulated datacube

Depths to the various subsurface anomalies have been the primary interest in all the applications of magnetic methods of geophysical prospection. Depths to the subsurface geologic features of interest are more valuable and superior to all other properties in any correct subsurface geologic structural interpretations.


This dataset contains four types of geospatial events coverage in Indonesian news online portal: flood, traffic jam, earthquake, and fire. The corpus itself was composed of 926 manually annotated, disambiguated, and event extracted sentences that was filtered from 83 of 645,679 documents of our earlier news corpus based on four major geospatial events: flood, earthquake, fire, and accidents



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.


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". 


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).