Remote Sensing
Emergency managers of today grapple with post-hurricane damage assessment that is often labor-intensive, slow,costly, and error-prone. As an important first step towards addressing the challenge, this paper presents the development of benchmark datasets to enable the automatic detection ofdamaged buildings from post-hurricane remote sensing imagerytaken from both airborne and satellite sensors. Our work has two major contributions: (1) we propose a scalable framework to create benchmark datasets of hurricane-damaged buildings
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This work quantifies water contamination in jet fuel (Jet A-1), using silica-based Bragg gratings. The optical sensor geometry exposes the evanescent optical field of a guided mode to enable refractometery. Quantitative analysis is made in addition to the observation of spectral features consistent with emulsification of water droplets and Stokes’ settling. Measurements are observed for cooling and heating cycles between ranges of 22oC and -60oC. The maximum spectral sensitivity for water contamination was 2.4 pm/ppm-v with a resolution of < 5 ppm-v.
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This work quantifies water contamination in jet fuel (Jet A-1), using silica-based Bragg gratings. The optical sensor geometry exposes the evanescent optical field of a guided mode to enable refractometery. Quantitative analysis is made in addition to the observation of spectral features consistent with emulsification of water droplets and Stokes’ settling. Measurements are observed for cooling and heating cycles between ranges of 22oC and -60oC. The maximum spectral sensitivity for water contamination was 2.4 pm/ppm-v with a resolution of < 5 ppm-v.
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The Doppler spectrum (DS) of the signal backscattered at the low incidence angles from the sea surface was measured by the Ka-band radar in an experiment on a marine oceanographic platform on October 5, 2016. The dependence of DS shift and width on incidence angle and azimuth angle is given.
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Run_IMA_proceure.R is an script that fills the clouds of the 3 target images or the complete neighborhood of 27 images of LST and NDVI remote sensing data in Navarre(Spain) and estimates the standard errors.
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Automatic classification of sensitive content in remote sensing images, such as drug crop sites, is a promising task as it can aid law-enforcement institutions fighting illegal drug dealers worldwide, while, at the same time, it can help monitoring legalized crops in countries that regulate them. However, existing art on detecting drug crops from remote sensing images is limited in some key factors not taking full advantage of the available hyperspectral info for analysis.
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High-fidelity, physics-based multichannel radar data cube provided by the DARPA KASSPER project. This data is ideal for analyzing space-time adaptive processing (STAP) algorithms since both sample data and truth data are provided.
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This dataset contains aerial images acquired with a medium format digital camera and point clouds collected using an airborne laser scanning (ALS) unit, as well as ground control points and direct georeferencing data. The flights were performed in 2014 over an urban area in Presidente Prudente, State of São Paulo, Brazil, using different flight heights. These flights covered several features of interest for research, including buildings of different sizes and roof materials, roads and vegetation.
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This study deals with derivation of an exact expressions for the current distribution and the input impedance of a circular loop antenna over a lossy half-space. the analysis is based on the image method, the direct integration of the vector potential, and the spherical function expansion. the results for the current distribution of this study are in very good agreement with those corresponding results available in the literature, which checks the correctness of formulations of the study.
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