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scientifique

Assessment of the accuracy of DTM river bed model using classical surveying measurement and LiDAR: a case study in Poland / Pawel Kotlarz in Survey review, vol 52 n° 372 (May 2020)  

Public [article]  inSurvey review > vol 52 n° 372 (May 2020) . - pp 246 - 252 Titre : Assessment of the accuracy of DTM river bed model using classical surveying measurement and LiDAR: a case study in Poland Type de document : Article/Communication Auteurs : Pawel Kotlarz, Auteur ; Monika Siejka, Auteur ; Monika Mika, Auteur Année de publication : 2020 Article en page(s) : pp 246 - 252 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] analyse comparative [Termes descripteurs IGN] Cracovie (Pologne) [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] lever direct [Termes descripteurs IGN] lit [Termes descripteurs IGN] modèle numérique de terrain [Termes descripteurs IGN] rivière Résumé : (Auteur) The aim of this paper is to show that natural watercourses surveying gives the best results using integrated measurement methods (classical surveying and LiDAR). The paper contains comparison of the riverbed DTM results obtained using LiDAR data in relation to data derived from direct measurements. The paper involved the performance of appropriate tests on selected structures using integrated measurement techniques – GNSS, tachymetry and LiDAR. The conducted studies showed some limitations method for acquiring data from LiDAR. This is because the method does not enable the determination of measuring points coordinates which describe the topography in places inaccessible for a laser beam. Numéro de notice : A2020-178 Thématique : IMAGERIE/POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2019.1696515 date de publication en ligne : 01/12/2019 En ligne : https://doi.org/10.1080/00396265.2019.1696515 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94840 [article]

Filtering of airborne LiDAR bathymetry based on bidirectional cloth simulation / Anxiu Yang in ISPRS Journal of photogrammetry and remote sensing, vol 163 (May 2020)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 163 (May 2020) . - pp 49 - 61 Titre : Filtering of airborne LiDAR bathymetry based on bidirectional cloth simulation Type de document : Article/Communication Auteurs : Anxiu Yang, Auteur ; Fanlin Yang, Auteur ; Dianpeng Su, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 49 - 61 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] ajustement de paramètres [Termes descripteurs IGN] Chine [Termes descripteurs IGN] courbe de Gauss [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] filtrage de points [Termes descripteurs IGN] itération [Termes descripteurs IGN] lidar bathymétrique [Termes descripteurs IGN] relief sous-marin [Termes descripteurs IGN] semis de points [Termes descripteurs IGN] télémétrie laser aéroporté Résumé : (auteur) Current filtering methods of airborne LiDAR bathymetry (ALB) point clouds cannot identify negative anomalies or avoid over-filtering of the data. To overcome these problems, we propose a bidirectional cloth simulation filtering (BCSF) method and verify it using captured data. First, a transfer iterative trend surface is established to eliminate the negative anomalies and realize the continuous expression of the seafloor topography. The terrain complexities of the seafloor points are calculated using four extracted feature factors: slope, standard deviation of depth, Gaussian curvature, and roughness. We then calculate the sub-regional terrain complexity and the adaptive distance threshold and obtain user-defined parameters. Finally, sub-regional filtering is carried out, and a filtered surface is established to solve the over-filtering problem of convex and concave seafloor topographies based on the BCSF correction model. To evaluate the performance of the proposed method, the BCSF method was applied to ALB data captured around Yuanzhi Island in the South China Sea. The experimental results show that the BCSF method effectively filters out non-seafloor points and fully preserves the seafloor microtopography to realize the integrity of the seafloor topography. The proposed BCSF method outperforms the cloth simulation filtering method in terms of the elimination rate, which decreases from 38.78% to 2.52% and from 29.52% to 0.70% in the whole study area and local study area, respectively. Consequently, the BCSF method that combines forward filtering with inverse filtering exhibits complementary advantages, avoids over-filtering, and demonstrates strong adaptability and robustness for ALB data. Numéro de notice : A2020-137 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.03.004 date de publication en ligne : 09/03/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.03.004 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94755 [article]

Modeling strawberry biomass and leaf area using object-based analysis of high-resolution images / Zhen Guan in ISPRS Journal of photogrammetry and remote sensing, vol 163 (May 2020)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 163 (May 2020) . - pp 171 - 186 Titre : Modeling strawberry biomass and leaf area using object-based analysis of high-resolution images Type de document : Article/Communication Auteurs : Zhen Guan, Auteur ; Amr Abd-Elrahman, Auteur ; Zhen Fan, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 171 - 186 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] analyse d'image orientée objet [Termes descripteurs IGN] biomasse [Termes descripteurs IGN] canopée [Termes descripteurs IGN] données spatiotemporelles [Termes descripteurs IGN] hauteur de la végétation [Termes descripteurs IGN] image à haute résolution [Termes descripteurs IGN] indice foliaire [Termes descripteurs IGN] orthophotoplan numérique [Termes descripteurs IGN] phénologie [Termes descripteurs IGN] semis de points [Termes descripteurs IGN] structure-from-motion Résumé : (auteur) Quantifying canopy biophysical parameters is critical to agricultural research and farm management. In this study, strawberry dry biomass and leaf area were modeled statistically using high spatial and temporal resolution imagery. A mobile field data acquisition system was used to acquire thousands of very high resolution (~0.5 mm) close-range images seven times throughout the strawberry growing season. Ortho-mosaics and dense point clouds were generated through Structure from Motion (SfM) and used in Object-Based Image Analysis (OBIA) at the sub-leaf level to extract canopy structure variables such as planimetric canopy area, canopy average height, and canopy smoothness metric. Regression analysis was carried out using these image-derived canopy variables as predictors to model leaf area ( = 0.79; ten-fold cross-validation RMSE = 0.056 m2) and dry biomass ( = 0.84; ten-fold cross-validation RMSE = 7.72 g) obtained through destructive measurements. Results indicate consistent predictive power through the season and across 17 strawberry genotypes. The study showed that the canopy smoothness metric developed in this study as an indicator of canopy density could complement other variables (planimetric canopy area, canopy average height) that describe canopy geometric properties. Numéro de notice : A2020-139 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.02.021 date de publication en ligne : 18/03/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.02.021 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94757 [article]

Spatio-temporal evaluation of transport accessibility of the Istanbul metrobus line / Wasim Shoman in Geocarto international, vol 35 n° 6 (May 2020)  

Public [article]  inGeocarto international > vol 35 n° 6 (May 2020) . - pp 602 - 622 Titre : Spatio-temporal evaluation of transport accessibility of the Istanbul metrobus line Type de document : Article/Communication Auteurs : Wasim Shoman, Auteur ; Hande Demirel, Auteur Année de publication : 2020 Article en page(s) : pp 602 - 622 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Systèmes d'information géographique [Termes descripteurs IGN] accessibilité [Termes descripteurs IGN] analyse spatio-temporelle [Termes descripteurs IGN] base de données temporelles [Termes descripteurs IGN] historique des données [Termes descripteurs IGN] image à haute résolution [Termes descripteurs IGN] image satellite [Termes descripteurs IGN] Istanbul (Turquie) [Termes descripteurs IGN] réseau de transport [Termes descripteurs IGN] transport urbain Résumé : (auteur) High budget transport infrastructure projects in the Istanbul Metropolitan Area endeavour to increase the efficiency of the transportation system. Among those investments; the bus rapid transit system – Istanbul Metrobus Line (IML) – is the most popular one that serves one million trips per day. Yet, the performance and impact of IML are not quantitatively assessed. Hence in this study, a high-resolution GIS-remote sensing framework is designed to analyse before and after accessibility over the period of 40 years (namely 1987–1997–2007–2014). High resolution satellite images were processed to generate the lacking historical land cover/use information with the expected high accuracy. Within the study area, utilized accessibility indices have unevenly increased after the operation of IML, such as 104.19% in potential and 99.07% in daily accessibility. According to the achieved results, such high spatio-temporal spatial framework could aid decision makers to quantitatively assess and evaluate the performance of such investments. Numéro de notice : A2020-201 Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2018.1524515 date de publication en ligne : 23/10/2018 En ligne : https://doi.org/10.1080/10106049.2018.1524515 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94871 [article]

Above-ground biomass estimation and yield prediction in potato by using UAV-based RGB and hyperspectral imaging / Bo Li in ISPRS Journal of photogrammetry and remote sensing, vol 162 (April 2020)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 162 (April 2020) . - pp 161 -1 72 Titre : Above-ground biomass estimation and yield prediction in potato by using UAV-based RGB and hyperspectral imaging Type de document : Article/Communication Auteurs : Bo Li, Auteur ; Xiangming Xu, Auteur ; Li Zhang, Auteur Année de publication : 2020 Article en page(s) : pp 161 -1 72 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] biomasse aérienne [Termes descripteurs IGN] classification par forêts aléatoires [Termes descripteurs IGN] couvert végétal [Termes descripteurs IGN] hauteur de la végétation [Termes descripteurs IGN] image de drone [Termes descripteurs IGN] image hyperspectrale [Termes descripteurs IGN] image RVB [Termes descripteurs IGN] indice de végétation [Termes descripteurs IGN] pomme de terre [Termes descripteurs IGN] régression des moindres carrés partiels [Termes descripteurs IGN] rendement agricole Résumé : (auteur) Rapid and accurate biomass and yield estimation facilitates efficient plant phenotyping and site-specific crop management. A low altitude unmanned aerial vehicle (UAV) was used to acquire RGB and hyperspectral imaging data for a potato crop canopy at two growth stages to estimate the above-ground biomass and predict crop yield. Field experiments included six cultivars and multiple treatments of nitrogen, potassium, and mixed compound fertilisers. Crop height was estimated using the difference between digital surface model and digital elevation models derived from RGB imagery. Combining with two narrow-band vegetation indices selected by the RReliefF feature selection algorithm. Random Forest regression models demonstrated high prediction accuracy for both fresh and dry above-ground biomass, with a coefficient of determination (r2) > 0.90. Crop yield was predicted using four narrow-band vegetation indices and crop height (r2 = 0.63) with imagery data obtained 90 days after planting. A Partial Least Squares regression model based on the full wavelength spectra demonstrated improved yield prediction (r2 = 0.81). This study demonstrated the merits of UAV-based RGB and hyperspectral imaging for estimating the above-ground biomass and yield of potato crops, which can be used to assist in site-specific crop management. Numéro de notice : A2020-125 Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.02.013 date de publication en ligne : 28/02/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.02.013 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94750 [article]

Antenna phase center correction differences from robot and chamber calibrations: the case study LEIAR25 / Grzegorz Krzan in GPS solutions, vol 24 n° 2 (April 2020)  

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Automated terrain feature identification from remote sensing imagery: a deep learning approach / Wenwen Li in International journal of geographical information science IJGIS, vol 34 n° 4 (April 2020)  

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Conterminous United States land cover change patterns 2001–2016 from the 2016 National Land Cover Database / Collin Homer in ISPRS Journal of photogrammetry and remote sensing, vol 162 (April 2020)  

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Directionally constrained fully convolutional neural network for airborne LiDAR point cloud classification / Congcong Wen in ISPRS Journal of photogrammetry and remote sensing, vol 162 (April 2020)  

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Experte image aérienne... / Laurent Polidori in Géomètre, n° 2179 (avril 2020)

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Geocoding of trees from street addresses and street-level images / Daniel Laumer in ISPRS Journal of photogrammetry and remote sensing, vol 162 (April 2020)  

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Monitoring of landslide activity at the Sirobagarh landslide, Uttarakhand, India, using LiDAR, SAR interferometry and geodetic surveys / Ashutosh Tiwari in Geocarto international, vol 35 n° 5 ([01/04/2020])  

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Performance of Galileo precise time and frequency transfer models using quad-frequency carrier phase observations / Pengfei Zhang in GPS solutions, vol 24 n° 2 (April 2020)  

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A Single Model CNN for Hyperspectral Image Denoising / Alessandro Maffei in IEEE Transactions on geoscience and remote sensing, vol 58 n° 4 (April 2020)  

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A single-receiver geometry-free approach to stochastic modeling of multi-frequency GNSS observables / Baocheng Zhang in Journal of geodesy, vol 94 n°4 (April 2020)  

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