Remote sensing . vol 12 n° 17Paru le : 01/09/2020 |
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Ajouter le résultat dans votre panierApplication of UAV photogrammetry with LiDAR data to facilitate the estimation of tree locations and DBH values for high-value timber species in Northern Japanese mixed-wood forests / Kyaw Thu Moe in Remote sensing, vol 12 n° 17 (September-1 2020)
[article]
Titre : Application of UAV photogrammetry with LiDAR data to facilitate the estimation of tree locations and DBH values for high-value timber species in Northern Japanese mixed-wood forests Type de document : Article/Communication Auteurs : Kyaw Thu Moe, Auteur ; Toshiaki Owari, Auteur ; Naoyuki Furuya, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : 19 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] aménagement forestier
[Termes IGN] analyse d'image orientée objet
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] couvert forestier
[Termes IGN] diamètre à hauteur de poitrine
[Termes IGN] données lidar
[Termes IGN] image captée par drone
[Termes IGN] Japon
[Termes IGN] orthophotographie
[Termes IGN] peuplement mélangé
[Termes IGN] photogrammétrie aérienne
[Termes IGN] semis de pointsRésumé : (auteur) High-value timber species play an important economic role in forest management. The individual tree information for such species is necessary for practical forest management and for conservation purposes. Digital aerial photogrammetry derived from an unmanned aerial vehicle (UAV-DAP) can provide fine spatial and spectral information, as well as information on the three-dimensional (3D) structure of a forest canopy. Light detection and ranging (LiDAR) data enable area-wide 3D tree mapping and provide accurate forest floor terrain information. In this study, we evaluated the potential use of UAV-DAP and LiDAR data for the estimation of individual tree location and diameter at breast height (DBH) values of large-size high-value timber species in northern Japanese mixed-wood forests. We performed multiresolution segmentation of UAV-DAP orthophotographs to derive individual tree crown. We used object-based image analysis and random forest algorithm to classify the forest canopy into five categories: three high-value timber species, other broadleaf species, and conifer species. The UAV-DAP technique produced overall accuracy values of 73% and 63% for classification of the forest canopy in two forest management sub-compartments. In addition, we estimated individual tree DBH Values of high-value timber species through field survey, LiDAR, and UAV-DAP data. The results indicated that UAV-DAP can predict individual tree DBH Values, with comparable accuracy to DBH prediction using field and LiDAR data. The results of this study are useful for forest managers when searching for high-value timber trees and estimating tree size in large mixed-wood forests and can be applied in single-tree management systems for high-value timber species. Numéro de notice : A2020-597 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.3390/rs12172865 Date de publication en ligne : 03/09/2020 En ligne : https://doi.org/10.3390/rs12172865 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95942
in Remote sensing > vol 12 n° 17 (September-1 2020) . - 19 p.[article]Detecting classic Maya settlements with Lidar-derived relief visualizations / Amy E. Thompson in Remote sensing, vol 12 n° 17 (September-1 2020)
[article]
Titre : Detecting classic Maya settlements with Lidar-derived relief visualizations Type de document : Article/Communication Auteurs : Amy E. Thompson, Auteur Année de publication : 2020 Article en page(s) : 29 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] analyse d'image orientée objet
[Termes IGN] Belize
[Termes IGN] données topographiques
[Termes IGN] fouille archéologique
[Termes IGN] modèle numérique de terrain
[Termes IGN] relief
[Termes IGN] semis de points
[Termes IGN] site archéologiqueRésumé : (auteur) In the past decade, Light Detection and Ranging (lidar) has fundamentally changed our ability to remotely detect archaeological features and deepen our understanding of past human-environment interactions, settlement systems, agricultural practices, and monumental constructions. Across archaeological contexts, lidar relief visualization techniques test how local environments impact archaeological prospection. This study used a 132 km2 lidar dataset to assess three relief visualization techniques—sky-view factor (SVF), topographic position index (TPI), and simple local relief model (SLRM)—and object-based image analysis (OBIA) on a slope model for the non-automated visual detection of small hinterland Classic (250–800 CE) Maya settlements near the polities of Uxbenká and Ix Kuku’il in Southern Belize. Pedestrian survey in the study area identified 315 plazuelas across a 35 km2 area; the remaining 90 km2 in the lidar dataset is yet to be surveyed. The previously surveyed plazuelas were compared to the plazuelas visually identified on the TPI and SLRM. In total, an additional 563 new possible plazuelas were visually identified across the lidar dataset, using TPI and SLRM. Larger plazuelas, and especially plazuelas located in disturbed environments, are often more likely to be detected in a visual assessment of the TPI and SLRM. These findings emphasize the extent and density of Classic Maya settlements and highlight the continued need for pedestrian survey to ground-truth remotely identified archaeological features and the impact of modern anthropogenic behaviors for archaeological prospection. Remote sensing and lidar have deepened our understanding of past human settlement systems and low-density urbanism, processes that we experience today as humans residing in modern cities Numéro de notice : A2020-598 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.3390/rs12172838 Date de publication en ligne : 01/09/2020 En ligne : https://doi.org/10.3390/rs12172838 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95944
in Remote sensing > vol 12 n° 17 (September-1 2020) . - 29 p.[article]Illuminating the spatio-temporal evolution of the 2008–2009 Qaidam earthquake sequence with the joint use of Insar time series and teleseismic data / Simon Daout in Remote sensing, vol 12 n° 17 (September-1 2020)
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Titre : Illuminating the spatio-temporal evolution of the 2008–2009 Qaidam earthquake sequence with the joint use of Insar time series and teleseismic data Type de document : Article/Communication Auteurs : Simon Daout, Auteur ; Andreas Steinberg, Auteur ; Marius Paul Isken, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : 23 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] analyse spatio-temporelle
[Termes IGN] données géodésiques
[Termes IGN] faille géologique
[Termes IGN] image Envisat
[Termes IGN] image radar moirée
[Termes IGN] inférence
[Termes IGN] interféromètrie par radar à antenne synthétique
[Termes IGN] séisme
[Termes IGN] série temporelle
[Termes IGN] sismologie
[Termes IGN] Tsinghai (Chine)Résumé : (auteur) Inferring the geometry and evolution of an earthquake sequence is crucial to understand how fault systems are segmented and interact. However, structural geological models are often poorly constrained in remote areas and fault inference is an ill-posed problem with a reliability that depends on many factors. Here, we investigate the geometry of the Mw 6.3 2008 and 2009 Qaidam earthquakes, in northeast Tibet, by combining InSAR time series and teleseismic data. We conduct a multi-array back-projection analysis from broadband teleseismic data and process three overlapping Envisat tracks covering the two earthquakes to extract the spatio-temporal evolution of seismic ruptures. We then integrate both geodetic and seismological data into a self-consistent kinematic model of the earthquake sequence. Our results constrain the depth and along-strike segmentation of the thrust-faulting sequence. The 2008 earthquake ruptured a ∼32° north-dipping fault that roots under the Olongbulak pop-up structure at ∼12 km depth and fault slip evolved post-seismically in a downdip direction. The 2009 earthquake ruptured three south-dipping high-angle thrusts and propagated from ∼9 km depth to the surface and bilaterally along the south-dipping segmented 55–75° high-angle faults of the Olonbulak pop-up structure that displace basin deformed sedimentary sequences above Paleozoic bedrock. Our analysis reveals that the inclusion of the post-seismic afterslip into modelling is beneficial in the determination of fault geometry, while teleseismic back-projection appears to be a robust tool for identifying rupture segmentation for moderate-sized earthquakes. These findings support the hypothesis that the Qilian Shan is expanding southward along a low-angle décollement that partitions the oblique convergence along multiple flower and pop-up structures. Numéro de notice : A2020-599 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.3390/rs12172850 Date de publication en ligne : 02/09/2020 En ligne : https://doi.org/10.3390/rs12172850 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95947
in Remote sensing > vol 12 n° 17 (September-1 2020) . - 23 p.[article]Analysis of chlorophyll concentration in potato crop by coupling continuous wavelet transform and spectral variable optimization / Ning Liu in Remote sensing, vol 12 n° 17 (September-1 2020)
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Titre : Analysis of chlorophyll concentration in potato crop by coupling continuous wavelet transform and spectral variable optimization Type de document : Article/Communication Auteurs : Ning Liu, Auteur ; Zizheng Xing, Auteur ; Ruomei Zhao, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : 22 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse spectrale
[Termes IGN] azote
[Termes IGN] chlorophylle
[Termes IGN] coefficient de corrélation
[Termes IGN] échantillonnage
[Termes IGN] étalonnage de modèle
[Termes IGN] pomme de terre
[Termes IGN] réflectance
[Termes IGN] régression des moindres carrés partiels
[Termes IGN] transformation en ondelettesRésumé : (auteur) The analysis of chlorophyll concentration based on spectroscopy has great importance for monitoring the growth state and guiding the precision nitrogen management of potato crops in the field. A suitable data processing and modeling method could improve the stability and accuracy of chlorophyll analysis. To develop such a method, we collected the modelling data by conducting field experiments at the tillering, tuber-formation, tuber-bulking, and tuber-maturity stages in 2018. A chlorophyll analysis model was established using the partial least-square (PLS) algorithm based on original reflectance, standard normal variate reflectance, and wavelet features (WFs) under different decomposition scales (21–210, Scales 1–10), which were optimized by the competitive adaptive reweighted sampling (CARS) algorithm. The performances of various models were compared. The WFs under Scale 3 had the strongest correlation with chlorophyll concentration with a correlation coefficient of −0.82. In the model calibration process, the optimal model was the Scale3-CARS-PLS, which was established based on the sensitive WFs under Scale 3 selected by CARS, with the largest coefficient of determination of calibration set (R2c) of 0.93 and the smallest R2c−R2cv value of 0.14. In the model validation process, the Scale3-CARS-PLS model had the largest coefficient of determination of validation set (R2v) of 0.85 and the smallest root–mean–square error of cross-validation (RMSEV) value of 2.77 mg/L, demonstrating good prediction capability of chlorophyll concentration. Finally, the analysis performance of the Scale3-CARS-PLS model was measured using the testing data collected in 2020; the R2 and RMSE values were 0.69 and 3.36 mg/L, showing excellent applicability. Therefore, the Scale3-CARS-PLS model could be used to analyze chlorophyll concentration. This study indicated the best decomposition scale of continuous wavelet transform and provided an important support method for chlorophyll analysis in the potato crops. Numéro de notice : A2020-600 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.3390/rs12172826 Date de publication en ligne : 31/08/2020 En ligne : https://doi.org/10.3390/rs12172826 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95950
in Remote sensing > vol 12 n° 17 (September-1 2020) . - 22 p.[article]