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Kayadibi O.,General Sensing
RAST 2011 - Proceedings of 5th International Conference on Recent Advances in Space Technologies | Year: 2011

After Landsat satellite launched in 1972, multispectral satellite images (Landsat TM/ETM+, Aster, ALI, Spot, Ikonos, Quickbird etc.) were used in many disciplines such as geology, environment, hydrogeology and ore deposits, etc. For several decades, imaging spectroscopy or hypespektral images are used with an increasing importance in many applications and various disciplines of geology. Imaging Spectroscopy is one of the new and fast growing technologies in remote sensing. © 2011 IEEE.


San B.T.,General Sensing | Suzen M.L.,Middle East Technical University
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives | Year: 2010

Hyperspectral remote sensing is a powerful tool in discriminating lithological units and in preparation of mineral maps. Hyperion is a space borne sensor of Hyperspectral imagery having 220 channels within the 400 nm to 2500 nm wavelength range. Although the technical specifications of the sensor are quite high, in the operational stage there exist many nuisances like atmosphere. The presence of atmosphere with aerosols and gases alters the reflected signal from the surface resulting in a decrease in the quality of the Hyperion image. In order to obtain accurate and reliable results, atmospheric correction must be carried out for Hyperion data. There are many atmospheric correction algorithms based on MODTRAN or LOWTRAN in literature and/or in commercial use. In this study, the Atmospheric CORrection Now (ACORN), the Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH), and ATmospheric CORrection (ATCOR 2-3) atmospheric correction algorithms were tested for atmospheric correction of Hyperion data. Test site is located on Central Anatolia having sparse vegetation cover. Both the obtained resultant images and the whole spectral signatures from the field samples were compared with cross correlations of whole spectra and specific wavelengths in spectral domain. Despite the compromises in different wavelength regions ACORN is found to be a slightly better corrector algorithm for natural earth materials through lithological and mineralogical mapping needs.


The retrieval of surface reflectance information from the same single pixel of the Hyperion image atmospherically corrected by using image-based [internal average relative reflectance (IARR), log residuals, and flat field] and radiative transfer model (RTM)-based [the fast line-of-sight atmospheric analysis of spectral hypercubes (FLAASH) and the Atmospheric and Topographic Correction 2 (ATCOR-2)] approaches and the spectral feature characteristics of this information were quantitatively and comparatively examined based on measured ground spectral reflectance data. The spectral features quantitative analysis results of the reflectance data showed that spectral reflectances that are suitable and best fitting to the ground spectral reflectances which were obtained from the pixels of FLAASH, ATCOR-2, and flat field-corrected images, respectively. The retrieval of surface reflectance from the FLAASH-corrected image pixels, in general, produced high scores in spectral parameter analyses. Of the image-based approaches, only in flat field-derived reflectance data, results were obtained which are high and nearest to those of RTM and ground spectral reflectance data. Generally, low scores obtained in the spectral parameter analyses of the surface reflectance values retrieved from single pixels of IARR and log residuals-corrected images showed the results that fit worst to the measured ground spectral reflectance. © 2013 Society of Photo-Optical Instrumentation Engineers.


G

Trademark
General Sensing | Date: 2012-01-03

A system comprised of electronic wireless sensors and devices, namely, body-worn electronically encoded wireless badges, wireless digital transceiver beacons placed in the hospital environment, wireless electronic base station transceivers connected to an electronic network, badge battery chargers, and wireless electric sensors embedded in and attached to hand hygiene product dispensers, that together aggregate information from and provide feedback to healthcare institutions, professionals, and patients through an Internet service and physical indicators.


Trademark
General Sensing | Date: 2012-01-03

A system comprised of electronic wireless sensors and devices, namely, body-worn electronically encoded wireless badges, wireless digital transceiver beacons placed in the hospital environment, wireless electronic base station transceivers connected to an electronic network, badge battery chargers, and wireless electric sensors embedded in and attached to hand hygiene product dispensers, that together aggregate information from and provide feedback to healthcare institutions, professionals, and patients through an Internet service and physical indicators.

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