Remote Sensing

Remote sensing of environment research has explored the benefits of using synthetic aperture radar imagery systems for a wide range of land and marine applications since these systems are not affected by weather conditions and therefore are operable both daytime and nighttime. The design of image processing techniques for  synthetic aperture radar applications requires tests and validation on real and synthetic images. The GRSS benchmark database supports the desing and analysis of algorithms to deal with SAR and PolSAR data.

  • Remote Sensing
  • Geoscience and Remote Sensing
  • Other
  • Last Updated On: 
    Tue, 11/12/2019 - 10:38
    Citation Author(s): 
    Nobre, R. H.; Rodrigues, F. A. A.; Rosa, R.; Medeiros, F.N.; Feitosa, R., Estevão, A.A., Barros, A.S.

    Cloud-free imageries, acquired from Landsat 8 OLI during 2016 to 2018, were used to delineate the extents of the glacial lakes in the mountainous terrain of CPEC

    76 views
  • Remote Sensing
  • Last Updated On: 
    Mon, 11/18/2019 - 07:09

    This study was conducted in Mayaguez – Puerto Rico, and an area of around 18 Km2 was covered, which were determined using the following classification of places:

    ·         Main Avenues: Wide public ways that has hospitals, vegetation, buildings, on either side

    ·         Open Places: Mall parking lots and public plazas

    ·         Streets & Roads: Dense residential and commercial areas on both sides

         Vendor             Equipment                  Description      

    KEYSIGHT®      N9343C                    Handheld Spectrum Analyzer

    196 views
  • IoT
  • Last Updated On: 
    Sun, 10/27/2019 - 21:54

    Dataset for the article: "Impacts of flow alteration on Swiss floodplains observed by remote sensing".

    The present data are originating from two kinds of product:

    - landsat time series of surface reflectances (product of)

    - discharge statistics from the Swiss Federal Office for the Environment (extracted statistics)

    21 views
  • Remote Sensing
  • Last Updated On: 
    Wed, 10/16/2019 - 04:00

    The dataset contains information about roses cultivation in greenhouses. It is aimed at identifying corrective actions to improve the roses state. Data acquisition was done with an autonomous robot incorporating sensors such as: soil humidity, light, temperature and humidity, and CO2.

    227 views
  • Remote Sensing
  • Last Updated On: 
    Tue, 07/23/2019 - 11:12

    Data set contains logs from OptiTrack motion camera system and flex sensor information from a smart glove. Participants performed finger taps for 10 secs.

    29 views
  • Remote Sensing
  • Last Updated On: 
    Mon, 07/15/2019 - 16:47

    Infrared imaging from aerial platforms can be used to detect landmines and minefields remotely and can save many lives. This dataset contains thermal images of buried and surface landmines. The images were recorded from a fixed camera for 24 hours with 15-minute intervals. DM-11 type anti-personnel landmines were used. This dataset is available for landmine detection research.

    189 views
  • Remote Sensing
  • Last Updated On: 
    Sun, 06/30/2019 - 15:55

    The SWINSEG dataset contains 115 nighttime images of sky/cloud patches along with their corresponding binary ground truth maps The ground truth annotation was done in consultation with experts from Singapore Meteorological Services. All images were captured in Singapore using WAHRSIS, a calibrated ground-based whole sky imager, over a period of 12 months from January to December 2016. All image patches are 500x500 pixels in size, and were selected considering several factors such as time of the image capture, cloud coverage, and seasonal variations.

     

    178 views
  • Energy
  • Last Updated On: 
    Thu, 04/04/2019 - 10:06

    This is the images and the image masks used in the paper "Z. Petrou and Y. Tian, Prediction of Sea Ice Motion with Convolutional Long Short-Term Memory Networks,IEEE Transactions on Geoscience and Remote Sensing."

    60 views
  • Remote Sensing
  • Last Updated On: 
    Sun, 03/31/2019 - 23:30

    Empirical line methods (ELM) are frequently used to correct images from aerial remote sensing. Remote sensing of aquatic environments captures only a small amount of energy because the water absorbs much of it. The small signal response of the water is proportionally smaller when compared to the other land surface targets.

     

    This dataset presents some resources and results of a new approach to calibrate empirical lines combining reference calibration panels with water samples. We optimize the method using python algorithms until reaches the best result.

     

    458 views
  • Sensors
  • Last Updated On: 
    Fri, 03/08/2019 - 20:47

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