Remote Sensing
Slow moving motions are mostly tackled by using the phase information of Synthetic Aperture Radar (SAR) images through Interferometric SAR (InSAR) approaches based on machine and deep learning. Nevertheless, to the best of our knowledge, there is no dataset adapted to machine learning approaches and targeting slow ground motion detections. With this dataset, we propose a new InSAR dataset for Slow SLIding areas DEtections (ISSLIDE) with machine learning. The dataset is composed of standardly processed interferograms and manual annotations created following geomorphologist strategies.
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A spectral signatures database of major crops in the East Mediterranean basin was created to support remote sensing applications specifically satellite hyperspectral and multispectral image classification. Moreover, it can be used to compute many important hyperspectral vegetation indices such as:
Atmospherically Resistant Vegetation Index (ARVI)
Modified Chlorophyll Absorption Ratio Index (MCARI)
Modified Chlorophyll Absorption Ratio Index - Improved (MCARI2)
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Blade damage inspection without stopping the normal operation of wind turbines has significant economic value. This study proposes an AI-based method AQUADA-Seg to segment the images of blades from complex backgrounds by fusing optical and thermal videos taken from normal operating wind turbines. The method follows an encoder-decoder architecture and uses both optical and thermal videos to overcome the challenges associated with field application.
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Progress toward the use of S-band SoOp in sea surface remote sensing was demonstrated in a 2012-2013 experiment based at the Harvest Oil Platform located at 34.469° N and 120.682° W, roughly 11 km from Point Conception, Santa Barbara, CA. Satellite transmissions from the XM-radio service were observed, using one channel each from the “Rhythm” (located above 85°W) and the “Blues” (115°W) satellites. Each downlink channel had a bandwidth of 1.886 MHz with a symbol rate of 1.64 Msps in Quadrature Phase Shift Key (QPSK) modulation.
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AndalUnmixingRGB is a Sentinel-2 satellite digital RGB imagery enriched with environmental ancillary data and designed for blind spectral unmixing using deep learning. Generally, spectral unmixing involves two main tasks: spectral signature identification of different available land use/cover types in the analyzed hyperspectral or multispectral imagery (endmember identification task) and their respective proportions measurement (abundance estimation task).
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Generating accurate thematic land use maps is importance in ecologically vulnerable regions, especially considering the challenges associated with extracting the forest-steppe ecotone and its associated uncertainties and high error rates. By employing the Principal Component Analysis (PCA) method to integrate Sentinel-1 and Sentinel-2 imagery, high-resolution (10 meters) land use cover products were generated for the forest-steppe ecotone of the Greater Khingan Mountains from 2019 to 2021.
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This dataset corresponds to the paper Calibration of a Hail-Impact Energy Electroacoustic Sensor, submitted to IEEE Transactions in Instrumentation and Measurement by Florencia Blasina, Andrés Echarri, and Nicolás Pérez.
The dataset corresponds to the voltage signals acquired regarding several steel-ball impacts on the proposed hail-sensor plate to calibrate it.
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Gorakhpur is a city located in the north-eastern region of
Uttar Pradesh state of India. It is a sub-part of Purvanchal
region of Uttar Pradesh and Bihar. In the south-western
part, Gorakhpur periphery spreads along Rapti river. In
the north-western region, Gorakhpur shares its periphery
with Chillua Tal. In the southern part, Ramgarh Tal with a
perimeter of 18 km is located.
Water Bodies:
+ Ramgarh Tal is a historically important heritage site and
is also a tourist attraction; spread over 700 hectares of
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India is a sub-continent that stretches from Ladakh in
the North to Kanyakumari in the South and from
Gujrat in the West to Arunachal Pradesh, Nagaland
and Manipur in the East. India is currently the
seventh largest country by land covering an area of
approximately 32,87,263 kms.
India's Space Strengths:
India is the fourth country in the world to have
destroyed a satellite of its own. India built the
record-breaking space capability of launching 104
satellites on a single Polar Satellite Launch Vehicle
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This is an indoor environment data set collected from our research team's laboratory, and the data is collected from the Intel RealSense D435i camera. There are a total of 12 datasets, each in the format of a `.bag` file in ROS packet format. Each file contains RGB images and IMU data.
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