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Is field-measured tree height as reliable as believed – Part II, A comparison study of tree height estimates from conventional field measurement and low-cost close-range remote sensing in a deciduous forest / Luka Jurjević in ISPRS Journal of photogrammetry and remote sensing, vol 169 (November 2020)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 169 (November 2020) . - pp 227 - 241 Titre : Is field-measured tree height as reliable as believed – Part II, A comparison study of tree height estimates from conventional field measurement and low-cost close-range remote sensing in a deciduous forest Type de document : Article/Communication Auteurs : Luka Jurjević, Auteur ; Xinlian Liang, Auteur ; Mateo Gašparović, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 227 - 241 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes descripteurs IGN] analyse comparative [Termes descripteurs IGN] balayage laser [Termes descripteurs IGN] corrélation [Termes descripteurs IGN] données de terrain [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] échantillonnage [Termes descripteurs IGN] forêt feuillue [Termes descripteurs IGN] hauteur des arbres [Termes descripteurs IGN] image de drone [Termes descripteurs IGN] modèle numérique de terrain [Termes descripteurs IGN] parcelle forestière [Termes descripteurs IGN] photogrammétrie métrologique [Termes descripteurs IGN] quercus pedunculata [Termes descripteurs IGN] semis de points Résumé : (auteur) Tree height is one of the most important tree attributes in forest inventory. However, using conventional field methods to measure tree height is a laborious and time-consuming process. Despite the great interest in the past to facilitate tree height measurements, new, upcoming solutions are not yet thoroughly investigated. In this study, we investigated the applicability of different close-range remote sensing options for tree height measurement in a complex lowland deciduous forest. Six sample plots in a pedunculate oak forest were measured in detail using conventional methods. Close-range remote sensing datasets used in this study represent solutions from low-cost sensors used for hand-held personal laser scanning (PLShh), unmanned–borne laser scanning (ULS) and unmanned aerial vehicle photogrammetry (UAVimage). Each tree in the sample plots was interactively measured directly from the point cloud, and correspondence of the field- and remote sensing measured trees was verified using tree positions collected during fieldwork. Cross-comparisons of different datasets were performed to evaluate the performances of different data sources in the tree height estimation with respect to crown class, tree height and species. All remote sensing data sources correlated well, e.g. biases between remote sensing sources were around ± 1%. The field-measured tree height in general correlated well with remote sensing data sources. The uncertainties and bias of the field measurements were dependent on the tree height and crown class. Field measurements tended to underestimate codominant and intermediate trees at the approximately 1 m magnitude, whilst remote sensing data sources were robust to crown classes. Low-cost ULS used in this study, and very likely in general, may not have enough penetration capability when measuring low and mostly occluded trees, causing missed treetops. PLShh gave tree height estimates closer to the real tree height than those derived from conventional field measurements for trees above 21 m height. Numéro de notice : A2020-641 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.09.014 date de publication en ligne : 03/10/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.09.014 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96064 [article]

From small sets of GPS trajectories to detailed movement profiles: quantifying personalized trip-dependent movement diversity / Elham Naghizade in International journal of geographical information science IJGIS, vol 34 n° 10 (October 2020)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 34 n° 10 (October 2020) . - pp 2004 - 2029 Titre : From small sets of GPS trajectories to detailed movement profiles: quantifying personalized trip-dependent movement diversity Type de document : Article/Communication Auteurs : Elham Naghizade, Auteur ; jeffrey Chan, Auteur ; Martin Tomko, Auteur Année de publication : 2020 Article en page(s) : pp 2004 - 2029 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes descripteurs IGN] comportement [Termes descripteurs IGN] données GPS [Termes descripteurs IGN] données spatiotemporelles [Termes descripteurs IGN] échantillonnage [Termes descripteurs IGN] gestion de trafic [Termes descripteurs IGN] modélisation spatio-temporelle [Termes descripteurs IGN] mouvement [Termes descripteurs IGN] origine - destination [Termes descripteurs IGN] trajectoire [Termes descripteurs IGN] trajet [Termes descripteurs IGN] voyage Résumé : (auteur) The ubiquity of personal sensing devices has enabled the collection of large, diverse, and fine-grained spatio-temporal datasets. These datasets facilitate numerous applications from traffic monitoring and management to location-based services. Recently, there has been an increasing interest in profiling individuals' movements for personalized services based on fine-grained trajectory data. Most approaches identify the most representative paths of a user by analyzing coarse location information, e.g., frequently visited places. However, even for trips that share the same origin and destination, individuals exhibit a variety of behaviors (e.g., a school drop detour, a brief stop at a supermarket). The ability to characterize and compare the variability of individuals' fine-grained movement behavior can greatly support location-based services and smart spatial sampling strategies. We propose a TRip DIversity Measure --TRIM – that quantifies the regularity of users' path choice between an origin and destination. TRIM effectively captures the extent of the diversity of the paths that are taken between a given origin and destination pair, and identifies users with distinct movement patterns, while facilitating the comparison of the movement behavior variations between users. Our experiments using synthetic and real datasets and across geographies show the effectiveness of our method. Numéro de notice : A2020-512 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2020.1730849 date de publication en ligne : 09/03/2020 En ligne : https://doi.org/10.1080/13658816.2020.1730849 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95666 [article]

Weighted spherical sampling of point clouds for forested scenes / Alex Fafard in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 10 (October 2020)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 86 n° 10 (October 2020) . - pp 619 - 625 Titre : Weighted spherical sampling of point clouds for forested scenes Type de document : Article/Communication Auteurs : Alex Fafard, Auteur ; Ali Rouzbeh Kargar, Auteur ; Jan Van Aardt, Auteur Année de publication : 2020 Article en page(s) : pp 619 - 625 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] Caroline (îles) [Termes descripteurs IGN] densité de la végétation [Termes descripteurs IGN] diamètre à hauteur de poitrine [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] échantillonnage [Termes descripteurs IGN] mangrove [Termes descripteurs IGN] semis de points [Termes descripteurs IGN] volume en bois Résumé : (Auteur) Numéro de notice : A2020-493 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.86.10.619 date de publication en ligne : 01/10/2020 En ligne : https://doi.org/10.14358/PERS.86.10.619 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96093 [article]

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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)  

Public [article]  inRemote sensing > vol 12 n° 17 (September - 1 2020) . - 22 p. 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 descripteurs IGN] analyse spectrale [Termes descripteurs IGN] azote [Termes descripteurs IGN] chlorophylle [Termes descripteurs IGN] coefficient de corrélation [Termes descripteurs IGN] échantillonnage [Termes descripteurs IGN] étalonnage de modèle [Termes descripteurs IGN] pomme de terre [Termes descripteurs IGN] réflectance [Termes descripteurs IGN] régression des moindres carrés partiels [Termes descripteurs IGN] transformation en ondelettes Résumé : (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 [article]

Extraction of urban built-up areas from nighttime lights using artificial neural network / Tingting Xu in Geocarto international, vol 35 n° 10 ([01/08/2020])  

Public [article]  inGeocarto international > vol 35 n° 10 [01/08/2020] . - pp 1049 - 1066 Titre : Extraction of urban built-up areas from nighttime lights using artificial neural network Type de document : Article/Communication Auteurs : Tingting Xu, Auteur ; Giovanni Coco, Auteur ; Jay Gao, Auteur Année de publication : 2020 Article en page(s) : pp 1049 - 1066 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] aménagement du territoire [Termes descripteurs IGN] bati [Termes descripteurs IGN] cartographie urbaine [Termes descripteurs IGN] classification dirigée [Termes descripteurs IGN] développement durable [Termes descripteurs IGN] échantillonnage [Termes descripteurs IGN] éclairage public [Termes descripteurs IGN] extraction de traits caractéristiques [Termes descripteurs IGN] Normalized Difference Vegetation Index [Termes descripteurs IGN] rayonnement lumineux [Termes descripteurs IGN] réseau neuronal artificiel [Termes descripteurs IGN] seuillage [Termes descripteurs IGN] température au sol [Termes descripteurs IGN] zone urbaine Résumé : (auteur) The spatial distribution of urban areas at the national and regional scales is critical for urban planners and governments to design sustainable and environment-friendly future development plans. The nighttime lights (NTL) data provide an effective way to monitor the urban at different scales however is usually achieved by using empirical threshold-based algorithms. This study proposed a novel Artificial Neural Network (ANN) approach, using moderate resolution imageries as NTL, MODIS NDVI and land surface temperature data, to map urban areas. Both random and maximum dissimilarity distance algorithm sampling methods were considered and compared. The validation of the urban areas extracted from MDA-based ANN against the 2011 US national land cover data showed a reasonable quality (overall accuracy = 97.84; Kappa = 0.74) and achieved more accurate result than the threshold method. This study demonstrates that ANN can provide an effective, rapid, and accurate alternative in extracting urban built-up areas from NTL. Numéro de notice : A2020-424 Affiliation des auteurs : non IGN Thématique : IMAGERIE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2018.1559887 date de publication en ligne : 21/03/2019 En ligne : https://doi.org/10.1080/10106049.2018.1559887 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95488 [article]

Towards a semi-automated mapping of Australia native invasive alien Acacia trees using Sentinel-2 and radiative transfer models in South Africa / Cecilia Masemola in ISPRS Journal of photogrammetry and remote sensing, vol 166 (August 2020)  

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Subpixel-pixel-superpixel-based multiview active learning for hyperspectral images classification / Yu Li in IEEE Transactions on geoscience and remote sensing, vol 58 n° 7 (July 2020)  

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Footprint determination of a spectroradiometer mounted on an unmanned aircraft system / Deepak Gautam in IEEE Transactions on geoscience and remote sensing, vol 58 n° 5 (May 2020)  

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A point cloud feature regularization method by fusing judge criterion of field force / Xijiang Chen in IEEE Transactions on geoscience and remote sensing, vol 58 n° 5 (May 2020)  

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Large-scale two-phase estimation of wood production by poplar plantations exploiting Sentinel-2 data as auxiliary information / Agnese Marcelli in Silva fennica, vol 54 n° 2 (2020)  

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Spectral Interference of Heavy Metal Contamination on Spectral Signals of Moisture Content for Heavy Metal Contaminated Soils / Haein Shin in IEEE Transactions on geoscience and remote sensing, vol 58 n° 4 (April 2020)  

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Poststack seismic data denoising based on 3-D convolutional neural network / Dawei Liu in IEEE Transactions on geoscience and remote sensing, vol 58 n° 3 (March 2020)  

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Identification of alpine glaciers in the central Himalayas using fully polarimetric L-Band SAR data / Guo-Hui Yao in IEEE Transactions on geoscience and remote sensing, vol 58 n° 1 (January 2020)  

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Variations in temperate forest biomass ratio along three environmental gradients are dominated by interspecific differences in wood density / Baptiste Kerfriden (2020)    

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The influence of sampling design on spatial data quality in a geographic citizen science project / Greg Brown in Transactions in GIS, Vol 23 n° 6 (November 2019)  

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