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Estimating forest attributes in airborne laser scanning based inventory using calibrated predictions from external models / Ana de Lera Garrido in Silva fennica, vol 56 n° 2 (April 2022)  

Public [article]  inSilva fennica > vol 56 n° 2 (April 2022) . - n° 10695 Titre : Estimating forest attributes in airborne laser scanning based inventory using calibrated predictions from external models Type de document : Article/Communication Auteurs : Ana de Lera Garrido, Auteur ; Terje Gobakken, Auteur ; Hans Ole Ørka, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 10695 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] diamètre à hauteur de poitrine [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] étalonnage [Termes IGN] hauteur des arbres [Termes IGN] inventaire forestier étranger (données) [Termes IGN] modèle de simulation [Termes IGN] modélisation spatio-temporelle [Termes IGN] Norvège [Termes IGN] parcelle forestière [Termes IGN] placette d'échantillonnage [Termes IGN] semis de points [Termes IGN] volume en bois Résumé : (auteur) Forest management inventories assisted by airborne laser scanner data rely on predictive models traditionally constructed and applied based on data from the same area of interest. However, forest attributes can also be predicted using models constructed with data external to where the model is applied, both temporal and geographically. When external models are used, many factors influence the predictions’ accuracy and may cause systematic errors. In this study, volume, stem number, and dominant height were estimated using external model predictions calibrated using a reduced number of up-to-date local field plots or using predictions from reparametrized models. We assessed and compared the performance of three different calibration approaches for both temporally and spatially external models. Each of the three approaches was applied with different numbers of calibration plots in a simulation, and the accuracy was assessed using independent validation data. The primary findings were that local calibration reduced the relative mean difference in 89% of the cases, and the relative root mean squared error in 56% of the cases. Differences between application of temporally or spatially external models were minor, and when the number of local plots was small, calibration approaches based on the observed prediction errors on the up-to-date local field plots were better than using the reparametrized models. The results showed that the estimates resulting from calibrating external models with 20 plots were at the same level of accuracy as those resulting from a new inventory. Numéro de notice : A2022-367 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.14214/sf.10695 Date de publication en ligne : 25/04/2022 En ligne : https://doi.org/10.14214/sf.10695 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100589 [article]

Evaluation of mapped-plot variance estimators across a range of partial nonresponse in a post-stratified national forest inventory / James A. Westfall in Canadian Journal of Forest Research, Vol 52 n° 2 (February 2022)  

Public [article]  inCanadian Journal of Forest Research > Vol 52 n° 2 (February 2022) . - pp 280 - 285 Titre : Evaluation of mapped-plot variance estimators across a range of partial nonresponse in a post-stratified national forest inventory Type de document : Article/Communication Auteurs : James A. Westfall, Auteur ; Andrew J. Lister, Auteur ; Charles T. Scott, Auteur Année de publication : 2022 Article en page(s) : pp 280 - 285 Note générale : bibliographie NB Note technique et non pas article de recherche Langues : Français (fre) Anglais (eng) Descripteur : [Termes IGN] erreur systématique [Termes IGN] estimation statistique [Termes IGN] inventaire forestier (techniques et méthodes) [Termes IGN] placette d'échantillonnage [Termes IGN] variance [Vedettes matières IGN] Inventaire forestier Résumé : (auteur) When conducting a forest inventory, sometimes portions of plots cannot be measured due to inaccessibility. Two primary methods have been presented to account for partial nonresponse in the estimation phase: (i) use a ratio-to-size estimator or (ii) apply an adjustment factor to all plot observations in proportion to the missing area. Both approaches provide identical estimates of the population mean, but the estimates of variance differ when partial nonresponse is present. The performance of variance estimators was examined for a range of population forest area and partial nonresponse proportions in the sample. The ratio-to-size variance estimator performed unbiasedly with respect to simulation results, but the adjustment factor variance estimates were biased, with magnitude and direction dependent upon the forest area proportion and amount of partial nonresponse. The bias is relatively small when the partial nonresponse is small, which is often the case; however, the ratio-to-size method is preferred to ensure accurate variance estimation for a wide range of circumstances. Numéro de notice : A2022-312 Affiliation des auteurs : non IGN Autre URL associée : Draft Thématique : FORET/MATHEMATIQUE Nature : Article DOI : 10.1139/cjfr-2021-0159 Date de publication en ligne : 10/08/2021 En ligne : https://doi.org/10.1139/cjfr-2021-0159 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100409 [article]

Vegetation changes in the understory of nitrogen-sensitive temperate forests over the past 70 years / Marina Roth in Forest ecology and management, vol 503 (1 January 2022)  

Public [article]  inForest ecology and management > vol 503 (1 January 2022) . - n° 119754 Titre : Vegetation changes in the understory of nitrogen-sensitive temperate forests over the past 70 years Type de document : Article/Communication Auteurs : Marina Roth, Auteur ; Anja Müller-Meissner, Auteur ; Hans-Gerhard Michiels, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 119754 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse diachronique [Termes IGN] azote [Termes IGN] Bade-Wurtemberg (Allemagne) [Termes IGN] changement climatique [Termes IGN] détection de changement [Termes IGN] écosystème forestier [Termes IGN] forêt tempérée [Termes IGN] impact sur l'environnement [Termes IGN] placette d'échantillonnage [Termes IGN] pollution atmosphérique [Termes IGN] sous-étage [Vedettes matières IGN] Ecologie forestière Résumé : (auteur) Since the industrial revolution, atmospheric nitrogen deposition has increased strongly and has been shown to alter nitrogen cycles, species composition and diversity in many ecosystems, including forests. At the same time, nitrogen removal from forests through biomass extraction via historical management techniques has decreased considerably. A proven tool to analyze the effects of long-term environmental changes are vegetation resurveys. In this study, we tested whether environmental changes resulting from atmospheric nitrogen deposition and altered forest management are reflected in the vegetation composition of temperate forest understories in six acidophilic and oligo-mesophilic forest types in south-western Germany. We compared historical surveys from 1950 to 1976 with surveys from 2017/18 and examined changes in the vegetation using NMDS ordinations and Ellenberg indicator values. While an increase in the number of nitrophilic species was detected in all forest types, only the acidophytic and oligotrophic Vaccinio-Abietetum and Luzulo-Quercetum forests (dominated by Abies alba (Mill.) and Quercus spec., respectively) exhibited a replacement of oligotrophic species by nitrophilic species, amounting to an overall trend of eutrophication. Despite the uncertainties resulting from different plot locations and the slow dynamics of forests, we demonstrate a significant trend in the understory vegetation composition, which is likely caused by atmospheric N deposition. Differences in the sensitivity of different forest types indicate an influence of geological and climatic site characteristics and historical land use on the effects of environmental changes. Numéro de notice : A2022-013 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1016/j.foreco.2021.119754 Date de publication en ligne : 21/10/2021 En ligne : https://doi.org/10.1016/j.foreco.2021.119754 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99070 [article]

Mapping tropical forest trees across large areas with lightweight cost-effective terrestrial laser scanning / Shengli Tao in Annals of Forest Science [en ligne], vol 78 n° 4 (December 2021)  

Public [article]  inAnnals of Forest Science [en ligne] > vol 78 n° 4 (December 2021) . - n° 103 Titre : Mapping tropical forest trees across large areas with lightweight cost-effective terrestrial laser scanning Type de document : Article/Communication Auteurs : Shengli Tao, Auteur ; Nicolas Labrière, Auteur ; Kim Calders, Auteur ; Fabian Jörg Fischer, Auteur ; E. Rau, Auteur ; Laetitia Plaisance, Auteur ; Jérôme Chave, Auteur Année de publication : 2021 Article en page(s) : n° 103 Note générale : bibliographie This work has benefitted from an “Investissement d'Avenir” grant managed by Agence Nationale de la Recherche (AnaEE France ANR-11-INBS-0001; CEBA, ref. ANR-10-LABX-25–01), the CNRS Nouragues station, and a CNES postdoctoral fellowship granted to S.T. Langues : Anglais (eng) Descripteur : [Termes IGN] diamètre à hauteur de poitrine [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] forêt tropicale [Termes IGN] Guyane (département français) [Termes IGN] inventaire forestier (techniques et méthodes) [Termes IGN] placette d'échantillonnage [Termes IGN] volume en bois [Vedettes matières IGN] Inventaire forestier Résumé : (auteur) Key message : We used lightweight terrestrial laser scanning (TLS) to detect over 3000 stems per hectare across a 12-ha permanent forest plot in French Guiana, 81% of them  Context : Accurate position mapping of tropical rainforest trees is crucial for baseline studies of tropical forest ecology but is labor-intensive. Terrestrial lidar scanning (TLS) is broadly used in temperate forest inventories, but its use in rainforests is restricted to the determination of individual tree volumes within small survey areas. Aims : Mapping tree stems across one large (12-ha) rainforest plot, including trees less than 10 cm DBH, and evaluating the precision of traditional mapping approaches. Methods : We used lightweight TLS, co-registered the acquisitions, and developed a new efficient algorithm to process the TLS data. Results : We detected 36,422 stems of which 29,665 (81%) were  Conclusion : Lightweight TLS technology is a promising tool for the estimation of stem tapering and volume. Here, we show that it also facilitates the establishment of large tropical forest inventories, by improving the positioning of trees, thus increasing the accuracy of forest inventories and their cost-effectiveness. Numéro de notice : A2021-954 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1007/s13595-021-01113-9 Date de publication en ligne : 28/12/2021 En ligne : https://doi.org/10.1007/s13595-021-01113-9 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99998 [article]

Regularized regression: A new tool for investigating and predicting tree growth / Stuart I. Graham in Forests, vol 12 n° 9 (September 2021)  

Public [article]  inForests > vol 12 n° 9 (September 2021) . - n° 1283 Titre : Regularized regression: A new tool for investigating and predicting tree growth Type de document : Article/Communication Auteurs : Stuart I. Graham, Auteur ; Ariel Rokem, Auteur ; Claire Fortunel, Auteur ; Nathan J.B. Kraft, Auteur ; Janneke Hille Ris Lambers, Auteur Année de publication : 2021 Article en page(s) : n° 1283 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Statistiques [Termes IGN] croissance des arbres [Termes IGN] inférence statistique [Termes IGN] interpolation [Termes IGN] modèle de simulation [Termes IGN] modélisation de la forêt [Termes IGN] placette d'échantillonnage [Termes IGN] régression Résumé : (auteur) Neighborhood models have allowed us to test many hypotheses regarding the drivers of variation in tree growth, but require considerable computation due to the many empirically supported non-linear relationships they include. Regularized regression represents a far more efficient neighborhood modeling method, but it is unclear whether such an ecologically unrealistic model can provide accurate insights on tree growth. Rapid computation is becoming increasingly important as ecological datasets grow in size, and may be essential when using neighborhood models to predict tree growth beyond sample plots or into the future. We built a novel regularized regression model of tree growth and investigated whether it reached the same conclusions as a commonly used neighborhood model, regarding hypotheses of how tree growth is influenced by the species identity of neighboring trees. We also evaluated the ability of both models to interpolate the growth of trees not included in the model fitting dataset. Our regularized regression model replicated most of the classical model’s inferences in a fraction of the time without using high-performance computing resources. We found that both methods could interpolate out-of-sample tree growth, but the method making the most accurate predictions varied among focal species. Regularized regression is particularly efficient for comparing hypotheses because it automates the process of model selection and can handle correlated explanatory variables. This feature means that regularized regression could also be used to select among potential explanatory variables (e.g., climate variables) and thereby streamline the development of a classical neighborhood model. Both regularized regression and classical methods can interpolate out-of-sample tree growth, but future research must determine whether predictions can be extrapolated to trees experiencing novel conditions. Overall, we conclude that regularized regression methods can complement classical methods in the investigation of tree growth drivers and represent a valuable tool for advancing this field toward prediction. Numéro de notice : A2021-720 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.3390/f12091283 En ligne : https://doi.org/10.3390/f12091283 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98636 [article]

Towards an optimization of sample plot size and scanner position layout for terrestrial laser scanning in multi-scan mode / Tim Ritter in Forests, vol 11 n° 10 (October 2020)  

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Dynamique spontanée post-tempête de la végétation forestière en contexte de changement climatique / Lucie Dietz (2020)  

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Faut-il des relevés de flore exhaustifs pour caractériser et cartographier l'acidité et les propriétés nutritionnelles des sols ? / Paulina E. Pinto in Rendez-vous techniques, n° 61-62 (hiver - printemps 2019) 

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Transferability and calibration of airborne laser scanning based mixed-effects models to estimate the attributes of sawlog-sized Scots pines / Lauri Korhonen in Silva fennica, vol 53 n° 3 (2019)  

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Utilizing the density of inventory samples to define a hybrid lattice for species distribution models: DISTRIB‐II for 135 eastern U.S. trees / Matthew P. Peters in Ecology and evolution, vol 9 n° 15 (August 2019)  

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Occlusion probability in operational forest inventory field sampling with ForeStereo / Fernando Montes in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 7 (July 2019)  

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Estimating forest stand density and structure using Bayesian individual tree detection, stochastic geometry, and distribution matching / Kasper Kansanen in ISPRS Journal of photogrammetry and remote sensing, vol 152 (June 2019)  

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RegisTree: a registration algorithm to enhance forest inventory plot georeferencing / Maryem Fadili in Annals of Forest Science [en ligne], vol 76 n° 2 (June 2019)  

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Detecting and characterizing downed dead wood using terrestrial laser scanning / Tuomas Yrttimaa in ISPRS Journal of photogrammetry and remote sensing, vol 151 (May 2019)  

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Thinking outside the square: Evidence that plot shape and layout in forest inventories can bias estimates of stand metrics / Thomas S. H. Paul in Methods in ecology and evolution, vol 10 n° 3 (March 2019)  

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