Geoscience and 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.

Last Updated On: 
Tue, 02/08/2022 - 17:46
Citation Author(s): 
Nobre, R. H.; Rodrigues, F. A. A.; Rosa, R.; Medeiros, F.N.; Feitosa, R., Estevão, A.A., Barros, A.S.

Central Arkansas Water (CAW) supplies fresh water to about a half million of Arkansas population; therefore, to avoid service interruptions and damage cost, its pipes and other facility locations must be depicted in a realistic view of the subsurface before excavation work is done. Accordingly, Ground Penetrating Radar (GPR) surveys were conducted to locate the CAW pipelines as well as other potential utility lines beneath the old Broadway Bridge prior to the planned excavation work on the bridge site.

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Drone based wildfire detection and modeling methods enable high-precision, real-time fire monitoring that is not provided by traditional remote fire monitoring systems, such as satellite imaging. Precise, real-time information enables rapid, effective wildfire intervention and management strategies. Drone systems’ ease of deployment, omnidirectional maneuverability, and robust sensing capabilities make them effective tools for early wildfire detection and evaluation, particularly so in environments that are inconvenient for humans and/or terrestrial vehicles.

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Ground Penetrating Radar (GPR) has a wide range of applications such as detection of buried mines, pipes and wires. GPR has been used as a near-surface remote sensing technique, and its working principle is based on electromagnetic (EM) wave theory. Here proposed data set is meant for data driven surrogate modelling based Buried Object Characterization. The considered problem of estimating geophysical parameters of a buried object is 2D. The training and testing scenarios include B-scan images (2D data), which contain 16 pairs of A-scan (concatenated forms of A-scans).

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The NENU-MPF dataset is a spatiotemporally continuous melt pond fraction (MPF) dataset of Arctic sea ice from 2000 to 2020 (from May 8 to September 24). It was generated from the Moderate Resolution Imaging Spectroradiometer (MODIS) data using an artificial neural network and a statistical-based temporal filter.

The NENU-MPF dataset was saved in a binary format (.img), which can be easily read by the ENVI software. The information about the data files can be found in the corresponding .hdr file.

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This is the experimental photo dataset of the article "An Automatic and Accurate Method for Marking GCPs in UAV Photogrammetry".

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Magnetotellurics forward modeling synthesizing time series

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Glacial lake outburst floods (GLOFs) are a major threat to the local communities and important infrastructures in the high mountain regions. Early detection of glacial lakes can prevent these disastrous events. Towards this end, we collected Sentinel 2 true color scenes of High-Mountain Asia (HMA) region using glacial lakes inventory of this region. It covers an area of 2080.12 km2 with nearly 30,121 glacial lakes. After data collection, we retained 1200 cloud free true color images and manually generated their ground truth masks.

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The optical remote sensing (ORS) ship dataset contains eight ship classes (i.e., bulk carrier, car carrier, cargo, chemical tanker, container, dredge, oil tanker, tug) with a total of 8678 pictures. All pictures are collected using Google Earth with sub-meter resolution and corresponding class information are matched with the official website[http://www.marinetraffic.com/]

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The geological and hydrological pressures were generally neglected primarily due to the challenging nature of the monitoring task in an underwater setting, particularly over a large-scale region. Using repeated multibeam sonar measurements, we developed an uncertainty-based approach for interpreting the geomorphic change of the Lion City, an ancient Chinese city that is submerged in Qiandao lake.

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