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Dense stereo matching strategy for oblique images that considers the plane directions in urban areas / Jianchen Liu in IEEE Transactions on geoscience and remote sensing, vol 58 n° 7 (July 2020)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 58 n° 7 (July 2020) . - pp 5109 - 5116 Titre : Dense stereo matching strategy for oblique images that considers the plane directions in urban areas Type de document : Article/Communication Auteurs : Jianchen Liu, Auteur ; Linjing Zhang, Auteur ; Zhen Wang, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 5109 - 5116 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] algorithme d'appariement [Termes descripteurs IGN] appariement d'images [Termes descripteurs IGN] appariement semi-global [Termes descripteurs IGN] bati [Termes descripteurs IGN] carte de profondeur [Termes descripteurs IGN] corrélation épipolaire dense [Termes descripteurs IGN] distorsion d'image [Termes descripteurs IGN] erreur moyenne quadratique [Termes descripteurs IGN] image oblique [Termes descripteurs IGN] perspective [Termes descripteurs IGN] PLANEITE [Termes descripteurs IGN] zone urbaine Résumé : (auteur) The perspective distortion of oblique images has a substantial impact on dense matching, i.e., it reduces the matching precision. In this article, a strategy of dense matching in which the object plane direction is considered is proposed. According to many regular planes in urban areas, epipolar rectification with minimum distortions relative to the selected reference planes can be generated. The matching results of epipolar images relative to various reference planes are weighted and fused into a single depth map, which is a better matching result. The experimental results demonstrate that the perspective distortion has a substantial influence on the dense matching performance. The root-mean-square error (RMSE) of the flatness for horizontal objects is increased by approximately 30%, and the RMSE of the flatness for façades is increased by approximately 40%. Hence, the proposed matching strategy, in which the object plane is considered, can effectively improve the matching results. Numéro de notice : A2020-394 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.2972312 date de publication en ligne : 20/02/2020 En ligne : https://doi.org/10.1109/TGRS.2020.2972312 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95390 [article]

Estimation of tropospheric wet refractivity using tomography method and artificial neural networks in Iranian case study / Mir Reza Ghaffari Razin in GPS solutions, Vol 24 n° 3 (July 2020)  

Public [article]  inGPS solutions > Vol 24 n° 3 (July 2020) Titre : Estimation of tropospheric wet refractivity using tomography method and artificial neural networks in Iranian case study Type de document : Article/Communication Auteurs : Mir Reza Ghaffari Razin, Auteur ; Behzad Voosoghi, Auteur Année de publication : 2020 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale [Termes descripteurs IGN] coefficient de corrélation [Termes descripteurs IGN] données GPS [Termes descripteurs IGN] erreur moyenne quadratique [Termes descripteurs IGN] erreur relative [Termes descripteurs IGN] Iran [Termes descripteurs IGN] réfraction atmosphérique [Termes descripteurs IGN] réseau neuronal artificiel [Termes descripteurs IGN] retard troposphérique [Termes descripteurs IGN] retard troposphérique zénithal [Termes descripteurs IGN] tomographie par GPS [Termes descripteurs IGN] vapeur d'eau [Termes descripteurs IGN] voxel Résumé : (auteur) Using the observations from local and regional GPS networks, the estimation of slant wet delays (SWDs) is possible for each line of sight between satellite and receiver. The observations of SWD are used to model horizontal and vertical variations of the wet refractivity in the atmosphere above the study area. This work is done using the tomography method. In tomography, the horizontal variations of tropospheric wet refractivity are modeled with the polynomial in degree and rank of 2 with latitude and longitude as variables. Also, altitude variations are modeled in the form of discrete layers with constant heights. The main innovation is to estimate the tropospheric parameters for each line of sight by the artificial neural networks (ANNs). The SWD obtained from GPS observations for the different signals at each station is compared with the SWD generated by the ANNs (SWDGPS–SWDANNs). The square of the difference between these two values is introduced as the cost function in the ANNs. To evaluate, we used observations from October 27 to 31, 2011. The availability of GPS and radiosonde data is the main reason for choosing this timeframe. The correlation coefficient, root mean square error (RMSE), and relative error allow for evaluation of the proposed model. The results were also compared with the results of the voxel-based troposphere tomography method. For a more detailed evaluation, four test stations are selected and ANN zenith wet delays (ZWDANN) are compared with the ZWDGPS. Observations of test stations are not used in the modeling step. The correlation coefficient in the testing step for TomoANN and Tomovoxel is 0.9006 and 0.8863, respectively. The mean RMSE at 5 days for TomoANN and Tomovoxel is calculated as 0.63 and 0.71 mm/km, respectively. Also, the average relative error at the four test stations for TomoANN is 15.37% and for Tomovoxel it is 19.69%. The results demonstrate the better capability of the proposed method in the modeling of the tropospheric wet refractivity in the region of Iran. Numéro de notice : A2020-238 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10291-020-00979-y date de publication en ligne : 10/04/2020 En ligne : https://doi.org/10.1007/s10291-020-00979-y Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94986 [article]

Under-canopy UAV laser scanning for accurate forest field measurements / Eric Hyyppä in ISPRS Journal of photogrammetry and remote sensing, vol 164 (June 2020)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 164 (June 2020) . - pp 41 - 60 Titre : Under-canopy UAV laser scanning for accurate forest field measurements Type de document : Article/Communication Auteurs : Eric Hyyppä, Auteur ; Juha Hyyppä, Auteur ; Teemu Hakala, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 41 - 60 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] balayage laser [Termes descripteurs IGN] canopée [Termes descripteurs IGN] densité du bois [Termes descripteurs IGN] diamètre à hauteur de poitrine [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] erreur moyenne quadratique [Termes descripteurs IGN] Finlande [Termes descripteurs IGN] forêt boréale [Termes descripteurs IGN] hauteur à la base du houppier [Termes descripteurs IGN] hauteur des arbres [Termes descripteurs IGN] image captée par drone [Termes descripteurs IGN] inventaire forestier local [Termes descripteurs IGN] modèle de croissance [Termes descripteurs IGN] semis de points [Termes descripteurs IGN] Simultaneous Localisation And Mapping [Termes descripteurs IGN] télédétection aérienne [Termes descripteurs IGN] télémètre laser terrestre [Termes descripteurs IGN] télémétrie laser aéroporté [Termes descripteurs IGN] tronc Résumé : (auteur) Surveying and robotic technologies are converging, offering great potential for robotic-assisted data collection and support for labour intensive surveying activities. From a forest monitoring perspective, there are several technological and operational aspects to address concerning under-canopy flying unmanned airborne vehicles (UAV). To demonstrate this emerging technology, we investigated tree detection and stem curve estimation using laser scanning data obtained with an under-canopy flying UAV. To this end, we mounted a Kaarta Stencil-1 laser scanner with an integrated simultaneous localization and mapping (SLAM) system on board an UAV that was manually piloted with the help of video goggles receiving a live video feed from the onboard camera of the UAV. Using the under-canopy flying UAV, we collected SLAM-corrected point cloud data in a boreal forest on two 32 m 32 m test sites that were characterized as sparse ( = 42 trees) and obstructed ( = 43 trees), respectively. Novel data processing algorithms were applied for the point clouds in order to detect the stems of individual trees and to extract their stem curves and diameters at breast height (DBH). The estimated tree attributes were compared against highly accurate field reference data that was acquired semi-manually with a multi-scan terrestrial laser scanner (TLS). The proposed method succeeded in detecting 93% of the stems in the sparse plot and 84% of the stems in the obstructed plot. In the sparse plot, the DBH and stem curve estimates had a root-mean-squared error (RMSE) of 0.60 cm (2.2%) and 1.2 cm (5.0%), respectively, whereas the corresponding values for the obstructed plot were 0.92 cm (3.1%) and 1.4 cm (5.2%). By combining the stem curves extracted from the under-canopy UAV laser scanning data with tree heights derived from above-canopy UAV laser scanning data, we computed stem volumes for the detected trees with a relative RMSE of 10.1% in both plots. Thus, the combination of under-canopy and above-canopy UAV laser scanning allowed us to extract the stem volumes with an accuracy comparable to the past best studies based on TLS in boreal forest conditions. Since the stems of several spruces located on the test sites suffered from severe occlusion and could not be detected with the stem-based method, we developed a separate work flow capable of detecting trees with occluded stems. The proposed work flow enabled us to detect 98% of trees in the sparse plot and 93% of the trees in the obstructed plot with a 100% correction level in both plots. A key benefit provided by the under-canopy UAV laser scanner is the short period of time required for data collection, currently demonstrated to be much faster than the time required for field measurements and TLS. The quality of the measurements acquired with the under-canopy flying UAV combined with the demonstrated efficiency indicates operational potential for supporting fast and accurate forest resource inventories. Numéro de notice : A2020-240 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.03.021 date de publication en ligne : 11/04/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.03.021 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94994 [article]

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Validation of Sentinel-3A SRAL coastal sea level data at high posting rate: 80 Hz / Ana Aldarias in IEEE Transactions on geoscience and remote sensing, vol 58 n° 6 (June 2020)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 58 n° 6 (June 2020) . - pp 3809 - 3821 Titre : Validation of Sentinel-3A SRAL coastal sea level data at high posting rate: 80 Hz Type de document : Article/Communication Auteurs : Ana Aldarias, Auteur ; Jesus Gomez-Enri, Auteur ; Irene Laiz, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 3809 - 3821 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes descripteurs IGN] coefficient de corrélation [Termes descripteurs IGN] correction troposphérique [Termes descripteurs IGN] courbe de Pearson [Termes descripteurs IGN] données altimétriques [Termes descripteurs IGN] données marégraphiques [Termes descripteurs IGN] eaux côtières [Termes descripteurs IGN] erreur moyenne quadratique [Termes descripteurs IGN] Espagne [Termes descripteurs IGN] forme d'onde [Termes descripteurs IGN] image Sentinel-SRAL [Termes descripteurs IGN] niveau de la mer [Termes descripteurs IGN] série temporelle Résumé : (auteur) Altimetry data of two and a half years (June 2016–November 2018) of Sentinel-3A SRAL (S3A-SRAL) were validated at the sampling frequency of 80 Hz. The data were obtained from the European Space Agency (ESA) Grid Processing On Demand (GPOD) service over three coastal sites in Spain: Huelva (HU) (Gulf of Cádiz), Barcelona (BA) (Western Mediterranean Sea), and Bilbao (BI) (Bay of Biscay). Two tracks were selected in each site: one ascending and one descending. Data were validated using in situ tide gauge (TG) data provided by the Spanish Puertos del Estado. The altimetry sea level anomaly time series were obtained using the corrections available in GPOD with the exception of the sea state bias (SSB) correction, not available at 80 Hz. Hence, the SSB was approximated to 5% of the significant wave height (SWH). The validation was performed using two statistical parameters, the Pearson correlation coefficient (r) and the root mean square error (rmse). In the 5–20-km segment with respect to the coastline, the results were 6–8 cm (rmse) and 0.7–0.8 (r) for all the tracks. The 0–5-km segment was also analyzed in detail to study the land effect on the altimetry data quality. The results showed that the track orientation, the angle of intersection with the coast, and the land topography concur to determine the nearest distance to the coast at which the data retain a similar level of accuracy than in the 5–20-km segment. This “distance of good quality” to shore reaches a minimum of 3 km for the tracks at HU and the descending track at BA. Numéro de notice : A2020-281 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2019.2957649 date de publication en ligne : 01/01/2020 En ligne : https://doi.org/10.1109/TGRS.2019.2957649 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95102 [article]

Soil moisture estimation with SVR and data augmentation based on alpha approximation method / Wei Xu in IEEE Transactions on geoscience and remote sensing, vol 58 n° 5 (May 2020)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 58 n° 5 (May 2020) . - pp 3190 - 3201 Titre : Soil moisture estimation with SVR and data augmentation based on alpha approximation method Type de document : Article/Communication Auteurs : Wei Xu, Auteur ; Zhaoxu Zhang, Auteur ; Qiming Qin, Auteur Année de publication : 2020 Article en page(s) : pp 3190 - 3201 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] approximation [Termes descripteurs IGN] erreur moyenne quadratique [Termes descripteurs IGN] humidité du sol [Termes descripteurs IGN] image ALOS [Termes descripteurs IGN] image radar moirée [Termes descripteurs IGN] image Sentinel-SAR [Termes descripteurs IGN] irrigation [Termes descripteurs IGN] modèle de régression [Termes descripteurs IGN] surveillance agricole Résumé : (auteur) Soil moisture content is an important parameter in hydrological, meteorological, and agricultural applications. Balenzano et al. proposed the alpha approximation method in 2011 for solving some complex issues during the retrieval of soil moisture over agricultural crops with synthetic aperture radar data. However, determining the constraints and solving the underdetermined system of equations in this method add new challenges. Considering the questions of constraints and underdetermined system of equations, the alpha approximation method is used to augment the measured data, and can avoid solving the underdetermined system of equations with constraints directly. Then, these data are applied in a support vector regression machine for soil moisture estimation. It is found that when an optimal model is determined, the method proposed in this article is superior to the direct use of the alpha approximation method, and the root-mean-squared error (RMSE) decreased from 0.0775 to 0.0339 and R 2 increased from 0.0467 to 0.6491. In addition, the method obtained a good result from a data set collected that included a different growing period of crops by changing the standardized method from StandardScaler to Scale , where the RMSE is 0.0501 and R 2 is 0.3204. This indicates the good generalization capability of this method. In conclusion, the proposed method solves the two questions effectively and provides a potential way for long-time or large-scale soil moisture monitoring with much less in situ measurements. Numéro de notice : A2020-235 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2019.2950321 date de publication en ligne : 26/11/2019 En ligne : https://doi.org/10.1109/TGRS.2019.2950321 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94981 [article]

Generation of digital terrain model for forest areas using a new particle swarm optimization on LiDAR data / Behnaz Bigdeli in Survey review, vol 52 n° 371 (March 2020)  

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An OD flow clustering method based on vector constraints: a case study for Beijing taxi origin-destination data / Xiaogang Guo in ISPRS International journal of geo-information, vol 9 n° 2 (February 2020)  

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Using Ranked Probability Skill Score (RPSS) as Nonlocal Root-Mean-Square Errors (RMSEs) for Mitigating Wet Bias of Soil Moisture Ocean Salinity (SMOS) Soil Moisture / Ju Hyoung Lee in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 2 (February 2020)  

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Modelling the orthoimage accuracy using DEM accuracy and off-nadir angle / Altan Yilmaz in Geocarto international, Vol 35 n° 1 ([02/01/2020])  

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A new global grid model for the determination of atmospheric weighted mean temperature in GPS precipitable water vapor / Liangke Huang in Journal of geodesy, vol 93 n° 2 (February 2019)  

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Estimating forest structural attributes using UAV-LiDAR data in Ginkgo plantations / Kun Liu in ISPRS Journal of photogrammetry and remote sensing, vol 146 (December 2018)  

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Super-resolution of Sentinel-2 images : Learning a globally applicable deep neural network / Charis Lanaras in ISPRS Journal of photogrammetry and remote sensing, vol 146 (December 2018)  

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La mesure du niveau de la mer par bouées GPS : l'expérience multi-capteurs de l'île d'Aix / Gaël André in XYZ, n° 140 (septembre - novembre 2014)

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Root mean square error compared to, and contrasted with, standard deviation / Thomas H. Meyer in SaLIS Surveying and land information science, vol 72 n° 3 (September 2012)

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Generalization of DEM for terrain analysis using a compound method / Q. Zhou in ISPRS Journal of photogrammetry and remote sensing, vol 66 n° 1 (January - February 2011)

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