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Urban geospatial information acquisition mobile mapping system based on close-range photogrammetry and IGS site calibration / Ming Guo in Geo-spatial Information Science, vol 24 n° 4 (October 2021)  

Public [article]  inGeo-spatial Information Science > vol 24 n° 4 (October 2021) . - pp 558 - 579 Titre : Urban geospatial information acquisition mobile mapping system based on close-range photogrammetry and IGS site calibration Type de document : Article/Communication Auteurs : Ming Guo, Auteur ; Yuquan Zhou, Auteur ; Jianghong Zhao, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 558 - 579 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie terrestre [Termes IGN] coordonnées GNSS [Termes IGN] couplage GNSS-INS [Termes IGN] données lidar [Termes IGN] étalonnage de capteur (imagerie) [Termes IGN] orientation du capteur [Termes IGN] précision des mesures [Termes IGN] Ransac (algorithme) [Termes IGN] semis de points [Termes IGN] station GNSS [Termes IGN] système de numérisation mobile [Termes IGN] zone urbaine Résumé : (auteur) The measurement accuracy of the Mobile Mapping System (MMS) is the main problem, which restricts its development and application, so how to calibrate the MMS to improve its measurement accuracy has always been a research hotspot in the industry. This paper proposes a position and attitude calibration method with error correction based on the combination of the feature point and feature surface. First, the initial value of the spatial position relationship between each sensor of MMS is obtained by close-range photogrammetry. Second, the optimal solution for error correction is calculated by feature points in global coordinates jointly measured with International GNSS Service (IGS) stations. Then, the final transformation parameters are solved by combining the initial values obtained originally, thereby realizing the rapid calibration of the MMS. Finally, it analyzed the RMSE of MMS point cloud after calibration, and the results demonstrate the feasibility of the calibration approach proposed by this method. Under the condition of a single measurement sensor accuracy is low, the plane and elevation absolute accuracy of the point cloud after calibration can reach 0.043 m and 0.072 m, respectively, and the relative accuracy is smaller than 0.02 m. It meets the precision requirements of data acquisition for MMS. It is of great significance for promoting the development of MMS technology and the application of some novel techniques in the future, such as autonomous driving, digital twin city, urban brain et al. Numéro de notice : A2021-128 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/10095020.2021.1924084 Date de publication en ligne : 20/08/2021 En ligne : https://doi.org/10.1080/10095020.2021.1924084 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99354 [article]

An internal-external optimized convolutional neural network for arbitrary orientated object detection from optical remote sensing images / Sihang Zhang in Geo-spatial Information Science, vol 24 n° 4 (October 2021)  

Public [article]  inGeo-spatial Information Science > vol 24 n° 4 (October 2021) . - pp 654 - 665 Titre : An internal-external optimized convolutional neural network for arbitrary orientated object detection from optical remote sensing images Type de document : Article/Communication Auteurs : Sihang Zhang, Auteur ; Zhenfeng Shao, Auteur ; Xiao Huang, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 654 - 665 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] apprentissage profond [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] détection d'objet [Termes IGN] image optique [Termes IGN] optimisation (mathématiques) Résumé : (auteur) Due to the bird’s eye view of remote sensing sensors, the orientational information of an object is a key factor that has to be considered in object detection. To obtain rotating bounding boxes, existing studies either rely on rotated anchoring schemes or adding complex rotating ROI transfer layers, leading to increased computational demand and reduced detection speeds. In this study, we propose a novel internal-external optimized convolutional neural network for arbitrary orientated object detection in optical remote sensing images. For the internal optimization, we designed an anchor-based single-shot head detector that adopts the concept of coarse-to-fine detection for two-stage object detection networks. The refined rotating anchors are generated from the coarse detection head module and fed into the refining detection head module with a link of an embedded deformable convolutional layer. For the external optimization, we propose an IOU balanced loss that addresses the regression challenges related to arbitrary orientated bounding boxes. Experimental results on the DOTA and HRSC2016 benchmark datasets show that our proposed method outperforms selected methods. Numéro de notice : A2021-129 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/10095020.2021.1972772 Date de publication en ligne : 27/09/2021 En ligne : https://doi.org/10.1080/10095020.2021.1972772 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99355 [article]

Performance investigation of LAMBDA and bootstrapping methods for PPP narrow-lane ambiguity resolution / Omer Faruk Atiz in Geo-spatial Information Science, vol 24 n° 4 (October 2021)  

Public [article]  inGeo-spatial Information Science > vol 24 n° 4 (October 2021) . - ppp 604 - 614 Titre : Performance investigation of LAMBDA and bootstrapping methods for PPP narrow-lane ambiguity resolution Type de document : Article/Communication Auteurs : Omer Faruk Atiz, Auteur ; Sermet Ogutcu, Auteur ; Salih Alcay, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : ppp 604 - 614 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale [Termes IGN] Bootstrap (statistique) [Termes IGN] compensation Lambda [Termes IGN] coordonnées GNSS [Termes IGN] positionnement ponctuel précis [Termes IGN] résolution d'ambiguïté [Termes IGN] traitement de données GNSS Résumé : (auteur) Precise point positioning with ambiguity resolution (PPP-AR) is a powerful tool for geodetic and time-constrained applications that require high precision. The performance of PPP-AR highly depends on the reliability of the correct integer carrier-phase ambiguity estimation. In this study, the performance of narrow-lane ambiguity resolution of PPP using the Least-squares AMBiguity Decorrelation (LAMBDA) and bootstrapping methods is extensively investigated using real data from 55 IGS stations over one-month in 2020. Static PPP with 24-, 12-, 8-, 4-, 2-, 1- and ½-h sessions using two different cutoff angles (7° and 30°) was conducted with three PPP modes: i.e. ambiguity-float and two kinds of ambiguity-fixed PPP using the LAMBDA and bootstrapping methods for narrow-lane AR, respectively. The results show that the LAMBDA method can produce more reliable results for 2 hour and shorter observation sessions compared with the bootstrapping method using a 7° cutoff angle. For a 30° cutoff angle, the LAMBDA method outperforms the bootstrapping method for observation sessions of 4 h and less. For long observation times, the bootstrapping method produced much more accurate coordinates compared with the LAMBDA method without considering the wrong fixes cases. The results also show that occurrences of fixing the wrong integer ambiguities using the bootstrapping method are higher than that of the LAMBDA method. Numéro de notice : A2021-968 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1080/10095020.2021.1942236 En ligne : https://doi.org/10.1080/10095020.2021.1942236 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100384 [article]

Phenology-based delineation of irrigated and rain-fed paddy fields with Sentinel-2 imagery in Google Earth Engine / Daniel Marc G. dela Torre in Geo-spatial Information Science, vol 24 n° 4 (October 2021)  

Public [article]  inGeo-spatial Information Science > vol 24 n° 4 (October 2021) . - pp 695 - 710 Titre : Phenology-based delineation of irrigated and rain-fed paddy fields with Sentinel-2 imagery in Google Earth Engine Type de document : Article/Communication Auteurs : Daniel Marc G. dela Torre, Auteur ; Jay Gao, Auteur ; Cate Macinnis-Ng, Auteur ; Yan Shi, Auteur Année de publication : 2021 Article en page(s) : pp 695 - 710 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] carte thématique [Termes IGN] Google Earth Engine [Termes IGN] image Sentinel-MSI [Termes IGN] Oryza (genre) [Termes IGN] phénologie [Termes IGN] rizière Résumé : (auteur) Paddy rice agriculture is practiced in both rain-fed and irrigated ecosystems in the Philippines. However, small farms are prevalent in the region, and current satellite-based mapping techniques do not distinguish between the two ecosystems at farm scales. This study developed an approach to rapidly map irrigated and rain-fed paddy rice in Iloilo, Philippines at 10 m resolutions using Google Earth Engine. This approach used an ensemble of classifiers based on time-series vegetation indices to produce dry and wet seasonal maps for the entire province. Results showed a predominance of rain-fed rice areas in both seasons, with irrigated rice making up only one-fourth of the total rice area. The overall accuracy was achieved at 68% for the dry season and 75% for the wet season based on ground-acquired points and very high-resolution imagery. The two types of paddies were classified at accuracies up to 87%. Furthermore, the land cover maps showed a strong agreement with the municipal statistics. The resultant maps complement current official statistics and demonstrate the prowess of phenology-based mapping to create paddy inventories in a timely manner to inform food security and agricultural policies. Numéro de notice : A2021-969 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Article DOI : 10.1080/10095020.2021.1984183 En ligne : https://doi.org/10.1080/10095020.2021.1984183 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100385 [article]