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Titre : Learning harmonised Pleiades and Sentinel-2 surface reflectances Type de document : Article/Communication Auteurs : J. Michel, Auteur ; Jordi Inglada, Auteur Editeur : International Society for Photogrammetry and Remote Sensing ISPRS Année de publication : 2021 Collection : International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, ISSN 1682-1750 num. 43-B2-2021 Conférence : ISPRS 2021, Commission 2, XXIV ISPRS Congress, Imaging today foreseeing tomorrow 05/07/2021 09/07/2021 Nice Virtuel France OA Archives Commission 2 Importance : pp 265 - 272 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] classification par Perceptron multicouche
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] image Pléiades
[Termes IGN] image Sentinel-MSI
[Termes IGN] réflectance de surface
[Termes IGN] régression linéaireRésumé : (auteur) In this paper, we investigate the use of machine-learning techniques in order to produce harmonised surface reflectances between Sentinel-2 and Pleiades images, and reduce the impact of the differences in sensors, view conditions, and atmospheric correction differences between them. We demonstrate that if a simple linear regression considering Sentinel-2 surface reflectances as the target domain can overcome this problem when both images are calibrated to Top of Canopy reflectances, the non-linearity brought by a simple Multi-Layer-Perceptron is already useful when Pleiades is corrected to Top of Atmosphere level and contributions of the atmosphere need to be learned. We also demonstrate that learning a Convolution Neural Network instead of a plain MLP can learn undesired spatial effects such as mis-registration or differences in spatial frequency content, that will affect the image quality of the corrected Pleiades product. We overcome this issue by proposing an adhoc input convolutional layer that will capture those effects and can later be unplugged during inference. Last, we also propose an architecture and loss function that is robust to unmasked clouds and produces a confidence prediction during inference. Numéro de notice : C2021-019 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Communication DOI : 10.5194/isprs-archives-XLIII-B3-2021-265-2021 Date de publication en ligne : 28/06/2021 En ligne : https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-265-2021 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98071 Retrieving surface soil water content using a soil texture adjusted vegetation index and unmanned aerial system images / Haibin Gu in Remote sensing, vol 13 n° 1 (January-1 2021)
[article]
Titre : Retrieving surface soil water content using a soil texture adjusted vegetation index and unmanned aerial system images Type de document : Article/Communication Auteurs : Haibin Gu, Auteur ; Zhe Lin, Auteur ; Wenxuan Guo, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 145 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] humidité du sol
[Termes IGN] image captée par drone
[Termes IGN] image multibande
[Termes IGN] image thermique
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] régression linéaire
[Termes IGN] stress hydrique
[Termes IGN] texture du solRésumé : (auteur) Surface soil water content (SWC) is a major determinant of crop production, and accurately retrieving SWC plays a crucial role in effective water management. Unmanned aerial systems (UAS) can acquire images with high temporal and spatial resolutions for SWC monitoring at the field scale. The objective of this study was to develop an algorithm to retrieve SWC by integrating soil texture into a vegetation index derived from UAS multispectral and thermal images. The normalized difference vegetation index (NDVI) and surface temperature (Ts) derived from the UAS multispectral and thermal images were employed to construct the temperature vegetation dryness index (TVDI) using the trapezoid model. Soil texture was incorporated into the trapezoid model based on the relationship between soil texture and the lower and upper limits of SWC to form the texture temperature vegetation dryness index (TTVDI). For validation, 128 surface soil samples, 84 in 2019 and 44 in 2020, were collected to determine soil texture and gravimetric SWC. Based on the linear regression models, the TTVDI had better performance in estimating SWC compared to the TVDI, with an increase in R2 (coefficient of determination) by 14.5% and 14.9%, and a decrease in RMSE (root mean square error) by 46.1% and 10.8%, for the 2019 and 2020 samples, respectively. The application of the TTVDI model based on high-resolution multispectral and thermal UAS images has the potential to accurately and timely retrieve SWC at the field scale. Numéro de notice : A2021-077 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/rs13010145 Date de publication en ligne : 04/01/2021 En ligne : https://doi.org/10.3390/rs13010145 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96815
in Remote sensing > vol 13 n° 1 (January-1 2021) . - n° 145[article]Optimizing local geoid undulation model using GPS/levelling measurements and heuristic regression approaches / Mosbeh R. Kaloop in Survey review, vol 52 n° 375 (November 2020)
[article]
Titre : Optimizing local geoid undulation model using GPS/levelling measurements and heuristic regression approaches Type de document : Article/Communication Auteurs : Mosbeh R. Kaloop, Auteur ; Ahmed Zaki, Auteur ; Hamad Al-Ajami, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 544 - 554 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie physique
[Termes IGN] anomalie de pesanteur
[Termes IGN] géoïde local
[Termes IGN] Koweit
[Termes IGN] méthode fondée sur le noyau
[Termes IGN] méthode heuristique
[Termes IGN] modèle de géopotentiel
[Termes IGN] nivellement avec assistance GPS
[Termes IGN] processus gaussien
[Termes IGN] régression
[Termes IGN] régression multivariée par spline adaptativeRésumé : (auteur) This study investigates to use GPS/Levelling measurements of Kuwait and four heuristic regression methods including Least Square Support Vector Regression (LSSVR), Gaussian Process Regression (GPR), Kernel Ridge Regression (KRR), and Multivariate Adaptive Regression Splines (MARS) for modelling local geoid undulation. The accuracy of the models was compared by geoid undulation of gravitational observations and Global Geopotential Models (GGMs). The results show that the KRR model is suitable for Kuwait geoid model, its error of percentage is 0.018 and 0.124% relative to gravity and GPS/Levelling geoid undulation models, respectively. Furthermore, the comparison of KRR model with GGMs models signifies its accuracy. Numéro de notice : A2020-688 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2019.1665615 Date de publication en ligne : 16/09/2019 En ligne : https://doi.org/10.1080/00396265.2019.1665615 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96221
in Survey review > vol 52 n° 375 (November 2020) . - pp 544 - 554[article]Analysis of shoreline changes in Vishakhapatnam coastal tract of Andhra Pradesh, India: an application of digital shoreline analysis system (DSAS) / Mirza Razi Imam Baig in Annals of GIS, vol 26 n° 4 (October 2020)
[article]
Titre : Analysis of shoreline changes in Vishakhapatnam coastal tract of Andhra Pradesh, India: an application of digital shoreline analysis system (DSAS) Type de document : Article/Communication Auteurs : Mirza Razi Imam Baig, Auteur ; Ishita Afreen Ahmad, Auteur ; Mohammad Tayyab, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 361 - 376 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Andhra Pradesh (Inde ; état)
[Termes IGN] détection de changement
[Termes IGN] érosion côtière
[Termes IGN] géomorphologie locale
[Termes IGN] image Landsat
[Termes IGN] pondération
[Termes IGN] régression linéaire
[Termes IGN] série temporelle
[Termes IGN] surveillance du littoral
[Termes IGN] trait de côteRésumé : (auteur) Coastline or Shoreline calculation is one of the important factors in the finding of coastal accretion and erosion and the study of coastal morphodynamic. Coastal erosion is a tentative hazard for communities especially in coastal areas as it is extremely susceptible to increasing coastal disasters. The study has been conducted along the coast of Vishakhapatnam district, Andhra Pradesh, India with the help of multi-temporal satellite images of 1991 2001, 2011 and 2018. The continuing coastal erosion and accretion rates have been calculated using the Digital Shoreline Analysis System (DSAS). Linear regression rate (LRR), End Point Rate (EPR) and Weighted Linear Regression (WLR) are used for calculating shoreline change rate. Based on calculations the district shoreline has been classified into five categories as high and low erosion, no change and high and low accretion. Out of 135 km, high erosion occupied 5.8 km of coast followed by moderate or low erosion 46.2 km. Almost 34.7 km coastal length showed little or no change. Moderate accretion is found along 30.5 km whereas high accretion trend found around 17.8 km. The outcome of shows that erosion is prevailing in Vishakhapatnam taluk, Ankapalli taluk, Yellamanchili taluk whereas most of the Bhemunipatnam coast is accreting. Natural and manmade activities and phenomena influence the coastal areas in terms of erosion and accretion. The study could be used for further planning and development and also for disaster management authority in the decision-making process in the study area. Numéro de notice : A2020-801 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/19475683.2020.1815839 Date de publication en ligne : 09/10/2020 En ligne : https://doi.org/10.1080/19475683.2020.1815839 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96724
in Annals of GIS > vol 26 n° 4 (October 2020) . - pp 361 - 376[article]Semi-automatic building extraction from WorldView-2 imagery using taguchi optimization / Hasan Tonbul in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 9 (September 2020)
[article]
Titre : Semi-automatic building extraction from WorldView-2 imagery using taguchi optimization Type de document : Article/Communication Auteurs : Hasan Tonbul, Auteur ; Taskin Kavzoglu, Auteur Année de publication : 2020 Article en page(s) : pp 547-555 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse de variance
[Termes IGN] carte d'occupation du sol
[Termes IGN] détection du bâti
[Termes IGN] extraction semi-automatique
[Termes IGN] image Worldview
[Termes IGN] optimisation (mathématiques)
[Termes IGN] rapport signal sur bruit
[Termes IGN] régression linéaire
[Termes IGN] segmentation multi-échelle
[Termes IGN] séparateur à vaste margeRésumé : (Auteur) Due to the complex spectral and spatial structures of remotely sensed images, the delineation of land use/land cover classes using conventional approaches is a challenging task. This article tackles the problem of seeking optimal parameters of multi-resolution segmentation for a classification task using WorldView-2 imagery. Taguchi optimization was applied to search optimal parameters using the plateau objective function (POF) and quality rate (Qr) as fitness criteria. Analysis of variance was also used to estimate the contributions of the parameters for POF and Qr, separately. The scale parameter was the most effective one, with contribution levels of 87.45% and 56.87% for POF and Qr, respectively. Linear regression and support-vector regression methods were used to predict the results of the experiment. Test results revealed that Taguchi optimization was more effective than linear regression and support-vector regression for predicting POF and Qr values. Numéro de notice : A2020-490 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.86.9.547 Date de publication en ligne : 01/09/2020 En ligne : https://doi.org/10.14358/PERS.86.9.547 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95931
in Photogrammetric Engineering & Remote Sensing, PERS > vol 86 n° 9 (September 2020) . - pp 547-555[article]Réservation
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