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Unmanned Aerial System multispectral mapping for low and variable solar irradiance conditions: Potential of tensor decomposition / Sheng Wang in ISPRS Journal of photogrammetry and remote sensing, vol 155 (September 2019)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 155 (September 2019) . - pp 58 - 71 Titre : Unmanned Aerial System multispectral mapping for low and variable solar irradiance conditions: Potential of tensor decomposition Type de document : Article/Communication Auteurs : Sheng Wang, Auteur ; Andreas Baum, Auteur ; Pablo J. Zarco-Tejada, Auteur ; Carsten Dam-Hansen, Auteur ; Anders Thorseth, Auteur ; Peter Bauer-Gottwein, Auteur ; Filippo Bandini, Auteur ; Monica Garcia, Auteur Année de publication : 2019 Article en page(s) : pp 58 - 71 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] étalonnage de capteur (imagerie) [Termes descripteurs IGN] image de drone [Termes descripteurs IGN] image multibande [Termes descripteurs IGN] nébulosité [Termes descripteurs IGN] rayonnement solaire [Termes descripteurs IGN] réflectance [Termes descripteurs IGN] réflectance spectrale [Termes descripteurs IGN] tenseur Résumé : (Auteur) Unlike satellite earth observation, multispectral images acquired by Unmanned Aerial Systems (UAS) provide great opportunities to monitor land surface conditions also in cloudy or overcast weather conditions. This is especially relevant for high latitudes where overcast and cloudy days are common. However, multispectral imagery acquired by miniaturized UAS sensors under such conditions tend to present low brightness and dynamic ranges, and high noise levels. Additionally, cloud shadows over space (within one image) and time (across images) are frequent in UAS imagery collected under variable irradiance and result in sensor radiance changes unrelated to the biophysical dynamics at the surface. To exploit the potential of UAS for vegetation mapping, this study proposes methods to obtain robust and repeatable reflectance time series under variable and low irradiance conditions. To improve sensor sensitivity to low irradiance, a radiometric pixel-wise calibration was conducted with a six-channel multispectral camera (mini-MCA6, Tetracam) using an integrating sphere simulating the varying low illumination typical of outdoor conditions at 55oN latitude. The sensor sensitivity was increased by using individual settings for independent channels, obtaining higher signal-to-noise ratios compared to the uniform setting for all image channels. To remove cloud shadows, a multivariate statistical procedure, Tucker tensor decomposition, was applied to reconstruct images using a four-way factorization scheme that takes advantage of spatial, spectral and temporal information simultaneously. The comparison between reconstructed (with Tucker) and original images showed an improvement in cloud shadow removal. Outdoor vicarious reflectance validation showed that with these methods, the multispectral imagery can provide reliable reflectance at sunny conditions with root mean square deviations of around 3%. The proposed methods could be useful for operational multispectral mapping with UAS under low and variable irradiance weather conditions as those prevalent in northern latitudes. Numéro de notice : A2019-311 Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.isprsjprs.2019.06.017 date de publication en ligne : 04/07/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.06.017 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93336 [article]

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Pavement marking retroreflectivity estimation and evaluation using mobile Lidar data / Erzhuo Che in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 8 (August 2019)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 85 n° 8 (August 2019) . - pp 573 - 583 Titre : Pavement marking retroreflectivity estimation and evaluation using mobile Lidar data Type de document : Article/Communication Auteurs : Erzhuo Che, Auteur ; Michael J. Olsen, Auteur ; Christopher E. Parrish, Auteur ; Jaehoon Jung, Auteur Année de publication : 2019 Article en page(s) : pp 573 - 583 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] étalonnage radiométrique [Termes descripteurs IGN] lidar mobile [Termes descripteurs IGN] régression [Termes descripteurs IGN] rétroréflecteur [Termes descripteurs IGN] semis de points [Termes descripteurs IGN] signalisation routière Résumé : (Auteur) Pavement markings are produced with retroreflective materials to enhance visibility for motorists, particularly at night. Retroreflectivity evaluation throughout an extensive highway network for maintenance and asset management purposes is a critical, yet challenging task for transportation agencies because visual evaluation can often be subjective and inconsistent, while field measurement can be time-consuming. Mobile Light Detection and Ranging (Lidar) datasets can potentially provide a safe, cost-effective, and reliable method of performing the required evaluation. This paper presents an empirical model for radiometric calibration of Lidar intensity information from the Leica Pegasus:Two system for pavement marking evaluation. The model was developed using dense handheld retroreflectometer measurements and mobile Lidar data collected in a variety of geometric configurations on a test site consisting of various markings with varying degrees of wear. The quantitative accuracy assessment of the proposed radiometric calibration model for estimating retroreflectivity was conducted to another independent dataset collected in different lanes and system configurations. Numéro de notice : A2019-409 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.85.8.573 date de publication en ligne : 01/08/2019 En ligne : https://doi.org/10.14358/PERS.85.8.573 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93540 [article]

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An evaluation of reflectance calibration methods for UAV spectral imagery / Jarrod Edwards in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 3 (March 2019)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 85 n° 3 (March 2019) . - pp 221 - 230 Titre : An evaluation of reflectance calibration methods for UAV spectral imagery Type de document : Article/Communication Auteurs : Jarrod Edwards, Auteur ; John Anderson, Auteur ; William Shuart, Auteur ; Jason Woolard, Auteur Année de publication : 2019 Article en page(s) : pp 221 - 230 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s) [Termes descripteurs IGN] capteur multibande [Termes descripteurs IGN] étalonnage de capteur (imagerie) [Termes descripteurs IGN] étalonnage radiométrique [Termes descripteurs IGN] image de drone [Termes descripteurs IGN] méthode empirique de ligne [Termes descripteurs IGN] orthophotoplan numérique [Termes descripteurs IGN] Pix4D [Termes descripteurs IGN] réflectance spectrale [Termes descripteurs IGN] régression Résumé : (Auteur) Spectral imagery using micro-unmanned aerial vehicles is rapidly advancing. This study compared reflectance calibration methods for imagery acquired using the Parrot Sequoia imager, a commercial multispectral sensor package. For the study, two orthomosaics were calibrated using 1) a manufacturer-suggested AIRINOV standard correction using PIX4D software and 2) the Empirical Line Calibration (ELC) method using ground radiometric data on specific in-scene targets. Both scenes were analyzed for target spectral agreement by ground radiometric survey. Regression analysis demonstrated more favorable target correlation for the ELC imagery than the AIRINOV-calibrated imagery, with Root Mean Square Error (RMSE) analysis supporting these results. Finally, classification maps were produced between the data sets. Error analysis resulted in an overall accuracy of 24% for the AIRINOV map compared to ELC-based truth data, with a considerable number of pixels associated with brighter targets unclassified. These results demonstrate the need for standardized calibration procedures in the spectral correction of small-format remote sensor data. Numéro de notice : A2019-149 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.85.3.221 date de publication en ligne : 01/03/2019 En ligne : https://doi.org/10.14358/PERS.85.3.221 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92502 [article]

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Calibration of the normalized radar cross section for sentinel-1 wave mode / Huimin Li in IEEE Transactions on geoscience and remote sensing, vol 57 n° 3 (March 2019)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 57 n° 3 (March 2019) . - pp 1514 - 1522 Titre : Calibration of the normalized radar cross section for sentinel-1 wave mode Type de document : Article/Communication Auteurs : Huimin Li, Auteur ; Alexis Mouche, Auteur ; Justin E. Stopa, Auteur ; Bertrand Chapron, Auteur Année de publication : 2019 Article en page(s) : pp 1514 - 1522 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes descripteurs IGN] Amazonie [Termes descripteurs IGN] étalonnage radiométrique [Termes descripteurs IGN] forêt équatoriale [Termes descripteurs IGN] image Sentinel-SAR [Termes descripteurs IGN] résidu Résumé : (Auteur) Sentinel-1 (S-1) is a two-satellite constellation for continuity of operational synthetic aperture radar (SAR) observations. Wave mode (WV) is the default mode over open ocean for S-1 to monitor global ocean waves and wind field. Therefore, proper radiometric calibration is essential to accurately infer these geophysical quantities. Based on the global data set acquired by S-1A WV, assessment of normalized radar cross section (NRCS) is carried out through comparison with CMOD5.N predictions over open ocean. The calibration accuracy quantified by NRCS residuals between SAR measurements and CMOD5.N demonstrates distinct features for two incidence angles (23.8° and 36.8°). Particularly, NRCS at 23.8° is overall consistent with CMOD5.N, while NRCS at 36.8° displays great deviation. Two recalibration methods are then implemented by examining the backscattering profile over Amazon rain forest and ocean calibration. Both methods show the necessity for recalibration and obtain comparable correction factors for WV1 and WV2, respectively. The NRCS residuals by applying both methods are significantly reduced toward zero. By comparison, ocean calibration is more efficient and practical to implement. Numéro de notice : A2019-128 Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2018.2867035 date de publication en ligne : 14/09/2018 En ligne : https://doi.org/10.1109/TGRS.2018.2867035 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92457 [article]

Radiometric calibration assessments for UAS-borne multispectral cameras: Laboratory and field protocols / Sen Cao in ISPRS Journal of photogrammetry and remote sensing, vol 149 (March 2019)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 149 (March 2019) . - pp 132 - 145 Titre : Radiometric calibration assessments for UAS-borne multispectral cameras: Laboratory and field protocols Type de document : Article/Communication Auteurs : Sen Cao, Auteur ; Brad Danielson, Auteur ; Shari Clare, Auteur Année de publication : 2019 Article en page(s) : pp 132 - 145 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s) [Termes descripteurs IGN] analyse comparative [Termes descripteurs IGN] bande infrarouge [Termes descripteurs IGN] bande rouge [Termes descripteurs IGN] capteur multibande [Termes descripteurs IGN] drone [Termes descripteurs IGN] étalonnage radiométrique [Termes descripteurs IGN] Normalized Difference Vegetation Index [Termes descripteurs IGN] réflectance spectrale [Termes descripteurs IGN] test de performance Résumé : (Auteur) The main objective of this study was to develop and test a framework that can be used by Unmanned Aerial Systems (UAS) operators with varying technical backgrounds to estimate the accuracy and reliability of multispectral (visible and Near-Infrared or NIR) sensor measurements. We evaluated the performance of two multispectral sensors – the MicaSense RedEdge and the Airinov MultiSpec 4C – in both a laboratory and field setting. In the laboratory, we measured the reflectance of a number of reference target materials using each UAS sensor, and compared the values to those measured using a calibrated spectrometer. We found a strong linear relationship between the measurements made by the MicaSense RedEdge and the spectrometer, while the relationship was much weaker for the Airinov MultiSpec 4C, particularly in the longer wavelength bands (red-edge and NIR). A sub-set of the target materials were selected as ground reference targets for three field calibration exercises. In field calibration assessment No. 1, imagery was collected using each UAS sensor and reflectance values were extracted from pixels covering the ground reference targets. The extracted values were compared to the reflectance values acquired in the laboratory, and both UAS sensors were found to over-estimate reflectance, with lower accuracy in red-edge and NIR bands. Field calibration assessment No. 2 involved a calculation of Normalized Difference Vegetation Index (NDVI) values at field control points using both UAS sensors, and we found a strong linear relationship between the NDVI values and measurements made by a hand-held NDVI sensor, suggesting that the calculation of a normalized band ratio (i.e., NDVI) effectively reduces the reflectance measurement inaccuracy that we observed previously. Field calibration assessment No. 3 included image acquisition of ground reference targets using the MicaSense RedEdge sensor over seventeen sequential field surveys. Results revealed measurement variability over time, suggesting that daily differences in solar illumination and atmospheric conditions may influence derived reflectance values. In light of these results, we propose simplified procedures that can be adopted by UAS operators to periodically assess the radiometric fidelity of their multispectral sensors. Numéro de notice : A2019-226 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.01.016 date de publication en ligne : 29/01/2019 En ligne : https://doi.org/ Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92445 [article]

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Improvement of photogrammetric accuracy by modeling and correcting the thermal effect on camera calibration / Mehdi Daakir in ISPRS Journal of photogrammetry and remote sensing, vol 148 (February 2019)  

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Analyzing the role of pulse density and voxelization parameters on full-waveform LiDAR-derived metrics / Pablo Crespo-Peremarch in ISPRS Journal of photogrammetry and remote sensing, vol 146 (December 2018)  

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Second iteration of photogrammetric processing to refine image orientation with improved tie-points / Truong Giang Nguyen in Sensors, vol 18 n° 7 (July 2018)    

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Advancement of close range photogrammetry with a portable panoramic image mapping system (PPIMS) / Yung-Chuan Chen in Photogrammetric record, vol 33 n° 162 (June 2018)  

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Geometric model and assessment of a dual‐fisheye imaging system / Mariana Batista Campos in Photogrammetric record, vol 33 n° 162 (June 2018)  

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Modelling and automated calibration of a general multi‐projective camera / Ehsan Khoramshahi in Photogrammetric record, vol 33 n° 161 (March 2018)  

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Evaluation of photogrammetric block orientation using quality descriptors from statistically filtered tie points / Alessio Calantropio (2018)  

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Hemispherical sky radiance measurement using a fish-eye camera / Manchun Lei (2018)    

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Sentinel-2 level-1 calibration and validation status from the mission performance centre / Catherine Bouzinac (2018)  

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Suivi et conservation du patrimoine historique et culturel / Jocelyn Le Maître (2018)

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