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Developing a site index model for P. Pinaster stands in NW Spain by combining bi-temporal ALS data and environmental data / Juan Guerra-Hernández in Forest ecology and management, vol 481 (February 2021)  

Public [article]  inForest ecology and management > vol 481 (February 2021) . - n° 118690 Titre : Developing a site index model for P. Pinaster stands in NW Spain by combining bi-temporal ALS data and environmental data Type de document : Article/Communication Auteurs : Juan Guerra-Hernández, Auteur ; Stefano Arellano-Pérez, Auteur ; Eduardo González-Ferreiro, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 118690 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] anomalie de croissance des arbres [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] échantillonnage [Termes IGN] Galice (Espagne) [Termes IGN] gestion forestière [Termes IGN] hauteur des arbres [Termes IGN] indice de végétation [Termes IGN] inventaire forestier étranger (données) [Termes IGN] lasergrammétrie [Termes IGN] Pinus pinaster [Termes IGN] régression multivariée par spline adaptative [Termes IGN] série temporelle Résumé : (auteur) Site index (SI) is a common measure of forest site productivity, serving as a valuable baseline for forest management. The main objective of this study was to develop a SI model for Pinus pinaster Ait. in north-west Spain by combining bi–temporal, low–density airborne laser scanning (ALS) data (acquired in the periods 2009–2011 and 2015–2017) with climatic, edaphic and physiographical data. Site productivity, assessed by site quality curves, was modelled using an age-independent difference equation method based on ALS metrics and environmental variables. For the model development process, we used data from 156 sample plots in pure and even-aged P. pinaster stands distributed throughout Galicia (NW Spain) and measured in the Spanish National Forest Inventory (SNFI). The generalized algebraic difference approach (GADA) formulation was tested by using two different base equations for modelling the dominant height growth (ΔH) from ALS variables. The GADA formulation derived from the Bertalanffy’s base model produced the best estimates of dominant height (H) for P. pinaster stands in Galicia. Use of the proposed model to estimate ΔH for a new pine stand requires two ALS data sets for estimating site-specific (local) parameters. To enable use of the model when such information is not available, the relationship between the values of the site-specific parameter and environmental variables was described using Multivariate Adaptive Regression Splines (MARS). Use of the MARS equation enabled us to develop spatially-explicit predictive maps of the site-specific parameter values, which can be used together with the GADA model to derive ΔH curves and SI estimates for P. pinaster stands in the whole study region. Numéro de notice : A2021-225 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.foreco.2020.118690 date de publication en ligne : 01/11/2021 En ligne : https://doi.org/10.1016/j.foreco.2020.118690 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97200 [article]

Optimizing local geoid undulation model using GPS/levelling measurements and heuristic regression approaches / Mosbeh R. Kaloop in Survey review, vol 52 n° 375 (November 2020)  

Public [article]  inSurvey review > vol 52 n° 375 (November 2020) . - pp 544 - 554 Titre : Optimizing local geoid undulation model using GPS/levelling measurements and heuristic regression approaches Type de document : Article/Communication Auteurs : Mosbeh R. Kaloop, Auteur ; Ahmed Zaki, Auteur ; Hamad Al-Ajami, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 544 - 554 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie physique [Termes IGN] anomalie de pesanteur [Termes IGN] géoïde local [Termes IGN] Koweit [Termes IGN] méthode fondée sur le noyau [Termes IGN] méthode heuristique [Termes IGN] modèle de géopotentiel [Termes IGN] nivellement avec assistance GPS [Termes IGN] processus gaussien [Termes IGN] régression [Termes IGN] régression multivariée par spline adaptative Résumé : (auteur) This study investigates to use GPS/Levelling measurements of Kuwait and four heuristic regression methods including Least Square Support Vector Regression (LSSVR), Gaussian Process Regression (GPR), Kernel Ridge Regression (KRR), and Multivariate Adaptive Regression Splines (MARS) for modelling local geoid undulation. The accuracy of the models was compared by geoid undulation of gravitational observations and Global Geopotential Models (GGMs). The results show that the KRR model is suitable for Kuwait geoid model, its error of percentage is 0.018 and 0.124% relative to gravity and GPS/Levelling geoid undulation models, respectively. Furthermore, the comparison of KRR model with GGMs models signifies its accuracy. Numéro de notice : A2020-688 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2019.1665615 date de publication en ligne : 16/09/2019 En ligne : https://doi.org/10.1080/00396265.2019.1665615 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96221 [article]

The extension of the parametrization of the radio source coordinates in geodetic VLBI and its impact on the time series analysis / Maria Karbon in Journal of geodesy, vol 91 n° 7 (July 2017)  

Public [article]  inJournal of geodesy > vol 91 n° 7 (July 2017) . - pp 755 - 765 Titre : The extension of the parametrization of the radio source coordinates in geodetic VLBI and its impact on the time series analysis Type de document : Article/Communication Auteurs : Maria Karbon, Auteur ; Robert Heinkelmann, Auteur ; Julian Mora-Diaz, Auteur ; Minghui Xu, Auteur ; Tobias Nilsson, Auteur ; Harald Schuh, Auteur Année de publication : 2017 Article en page(s) : pp 755 - 765 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale [Termes IGN] données ITGB [Termes IGN] fonction spline [Termes IGN] interférométrie à très grande base [Termes IGN] paramètres d'orientation de la Terre [Termes IGN] régression multivariée par spline adaptative [Termes IGN] repère de référence céleste [Termes IGN] série temporelle Résumé : (Auteur) The radio sources within the most recent celestial reference frame (CRF) catalog ICRF2 are represented by a single, time-invariant coordinate pair. The datum sources were chosen mainly according to certain statistical properties of their position time series. Yet, such statistics are not applicable unconditionally, and also ambiguous. However, ignoring systematics in the source positions of the datum sources inevitably leads to a degradation of the quality of the frame and, therefore, also of the derived quantities such as the Earth orientation parameters. One possible approach to overcome these deficiencies is to extend the parametrization of the source positions, similarly to what is done for the station positions. We decided to use the multivariate adaptive regression splines algorithm to parametrize the source coordinates. It allows a great deal of automation, by combining recursive partitioning and spline fitting in an optimal way. The algorithm finds the ideal knot positions for the splines and, thus, the best number of polynomial pieces to fit the data autonomously. With that we can correct the ICRF2 a priori coordinates for our analysis and eliminate the systematics in the position estimates. This allows us to introduce also special handling sources into the datum definition, leading to on average 30 % more sources in the datum. We find that not only the CPO can be improved by more than 10 % due to the improved geometry, but also the station positions, especially in the early years of VLBI, can benefit greatly. Numéro de notice : A2017-296 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern En ligne : http://doi.org/10.1007/s00190-016-0954-1 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85331 [article]

Development and Comparison of Species Distribution Models for Forest Inventories / Óscar Rodríguez de Rivera in ISPRS International journal of geo-information, vol 6 n° 6 (June 2017)  

Public [article]  inISPRS International journal of geo-information > vol 6 n° 6 (June 2017) Titre : Development and Comparison of Species Distribution Models for Forest Inventories Type de document : Article/Communication Auteurs : Óscar Rodríguez de Rivera, Auteur ; Antonio López-Quílez, Auteur Année de publication : 2017 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse comparative [Termes IGN] analyse de données [Termes IGN] arbre (flore) [Termes IGN] classification et arbre de régression [Termes IGN] distribution spatiale [Termes IGN] entropie maximale [Termes IGN] inventaire forestier (techniques et méthodes) [Termes IGN] modèle mathématique [Termes IGN] régression multivariée par spline adaptative [Vedettes matières IGN] Inventaire forestier Résumé : (auteur) A comparison of several statistical techniques common in species distribution modeling was developed during this study to evaluate and obtain the statistical model most accurate to predict the distribution of different forest tree species (in our case presence/absence data) according environmental variables. During the process we have developed maximum entropy (MaxEnt), classification and regression trees (CART), multivariate adaptive regression splines (MARS), showing the statistical basis of each model and, at the same time, we have developed a specific additive model to compare and validate their capability. To compare different results, the area under the receiver operating characteristic (ROC) function (AUC) was used. Every AUC value obtained with those models is significant and all of the models could be useful to represent the distribution of each species. Moreover, the additive model with thin plate splines gave the best results. The worst capability was obtained with MARS. This model’s performance was below average for several species. The additive model developed obtained better results because it allowed for changes and calibrations. In this case we were aware of all of the processes that occurred during the modeling. By contrast, models obtained using specific software, in general, perform like “hermetic machines”, because it could sometimes be impossible to understand the stages that led to the final results. Numéro de notice : A2017-810 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi6060176 En ligne : https://doi.org/10.3390/ijgi6060176 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89250 [article]

Evaluating EO1-Hyperion capability for mapping conifer and broadleaved forests / Nicola Puletti in European journal of remote sensing, vol 49 (2016)  

Public [article]  inEuropean journal of remote sensing > vol 49 (2016) . - pp 157 - 169 Titre : Evaluating EO1-Hyperion capability for mapping conifer and broadleaved forests Type de document : Article/Communication Auteurs : Nicola Puletti, Auteur ; Nicola Camarretta, Auteur ; Piermaria Corona, Auteur Année de publication : 2016 Article en page(s) : pp 157 - 169 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] classification par forêts aléatoires [Termes IGN] classification par séparateurs à vaste marge [Termes IGN] feuillu [Termes IGN] forêt [Termes IGN] image EO1-Hyperion [Termes IGN] image hyperspectrale [Termes IGN] matrice de confusion [Termes IGN] Pinophyta [Termes IGN] régression multivariée par spline adaptative Résumé : (auteur) The objective of the present study is the comparison of the combined use of Earth Observation-1 (EO-1) Hyperion Hyperspectral images with the Random Forest (RF), Support Vector Machines (SVM) and Multivariate Adaptive Regression Splines (MARS) classifiers for discriminating forest cover groups, namely broadleaved and coniferous forests. Statistics derived from classification confusion matrix were used to assess the accuracy of the derived thematic maps. We demonstrated that Hyperion data can be effectively used to obtain rapid and accurate large-scale mapping of main forest types (conifers-broadleaved). We also verified higher capability of Hyperion imagery with respect to Landsat data to such an end. Results demonstrate the ability of the three tested classification methods, with small improvements given by SVM in terms of overall accuracy and kappa statistic. Numéro de notice : A2016-832 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article En ligne : http://dx.doi.org/10.5721/EuJRS20164909 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82716 [article]

Statistical learning from a regression perspective / Richard A. Berk (2016)  

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