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Data-driven estimation of building interior plans / Julian F. Rosser in International journal of geographical information science IJGIS, vol 31 n° 7-8 (July - August 2017)
[article]
Titre : Data-driven estimation of building interior plans Type de document : Article/Communication Auteurs : Julian F. Rosser, Auteur ; Gavin Smith, Auteur ; Jeremy G. Morley, Auteur Année de publication : 2017 Article en page(s) : pp 1652 - 1674 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Termes IGN] bâtiment
[Termes IGN] carte d'intérieur
[Termes IGN] modèle de simulation
[Termes IGN] optimisation spatiale
[Termes IGN] plan
[Termes IGN] programmation par contraintesRésumé : (Auteur) This work investigates constructing plans of building interiors using learned building measurements. In particular, we address the problem of accurately estimating dimensions of rooms when measurements of the interior space have not been captured. Our approach focuses on learning the geometry, orientation and occurrence of rooms from a corpus of real-world building plan data to form a predictive model. The trained predictive model may then be queried to generate estimates of room dimensions and orientations. These estimates are then integrated with the overall building footprint and iteratively improved using a two-stage optimisation process to form complete interior plans.
The approach is presented as a semi-automatic method for constructing plans which can cope with a limited set of known information and constructs likely representations of building plans through modelling of soft and hard constraints. We evaluate the method in the context of estimating residential house plans and demonstrate that predictions can effectively be used for constructing plans given limited prior knowledge about the types of rooms and their topology.Numéro de notice : A2017-315 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2017.1313980 En ligne : http://dx.doi.org/10.1080/13658816.2017.1313980 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85369
in International journal of geographical information science IJGIS > vol 31 n° 7-8 (July - August 2017) . - pp 1652 - 1674[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2017041 RAB Revue Centre de documentation En réserve L003 Disponible 079-2017042 RAB Revue Centre de documentation En réserve L003 Disponible Fusing tree‐ring and forest inventory data to infer influences on tree growth / Margaret E.K. Evans in Ecosphere, vol 8 n° 7 (July 2017)
[article]
Titre : Fusing tree‐ring and forest inventory data to infer influences on tree growth Type de document : Article/Communication Auteurs : Margaret E.K. Evans, Auteur ; Donald A. Falk, Auteur ; et al., Auteur Année de publication : 2017 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] changement climatique
[Termes IGN] classification bayesienne
[Termes IGN] croissance des arbres
[Termes IGN] dendrochronologie
[Termes IGN] inférence statistique
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] modèle statistique
[Termes IGN] montagne
[Termes IGN] Nouveau-Mexique (Etats-Unis)
[Termes IGN] régression multiple
[Vedettes matières IGN] Végétation et changement climatiqueRésumé : (auteur) Better understanding and prediction of tree growth is important because of the many ecosystem services provided by forests and the uncertainty surrounding how forests will respond to anthropogenic climate change. With the ultimate goal of improving models of forest dynamics, here we construct a statistical model that combines complementary data sources, tree‐ring and forest inventory data. A Bayesian hierarchical model was used to gain inference on the effects of many factors on tree growth—individual tree size, climate, biophysical conditions, stand‐level competitive environment, tree‐level canopy status, and forest management treatments—using both diameter at breast height (dbh) and tree‐ring data. The model consists of two multiple regression models, one each for the two data sources, linked via a constant of proportionality between coefficients that are found in parallel in the two regressions. This model was applied to a data set of ~130 increment cores and ~500 repeat measurements of dbh at a single site in the Jemez Mountains of north‐central New Mexico, USA. The tree‐ring data serve as the only source of information on how annual growth responds to climate variation, whereas both data types inform non‐climatic effects on growth. Inferences from the model included positive effects on growth of seasonal precipitation, wetness index, and height ratio, and negative effects of dbh, seasonal temperature, southerly aspect and radiation, and plot basal area. Climatic effects inferred by the model were confirmed by a dendroclimatic analysis. Combining the two data sources substantially reduced uncertainty about non‐climate fixed effects on radial increments. This demonstrates that forest inventory data measured on many trees, combined with tree‐ring data developed for a small number of trees, can be used to quantify and parse multiple influences on absolute tree growth. We highlight the kinds of research questions that can be addressed by combining the high‐resolution information on climate effects contained in tree rings with the rich tree‐ and stand‐level information found in forest inventories, including projection of tree growth under future climate scenarios, carbon accounting, and investigation of management actions aimed at increasing forest resilience. Numéro de notice : A2017-907 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1002/ecs2.1889 Date de publication en ligne : 24/07/2017 En ligne : https://doi.org/10.1002/ecs2.1889 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93405
in Ecosphere > vol 8 n° 7 (July 2017)[article]Predicting stem total and assortment volumes in an industrial pinus taeda L. forest plantation using airborne laser scanning data and random forest / Carlos Alberto Silva in Forests, vol 8 n° 7 (July 2017)
[article]
Titre : Predicting stem total and assortment volumes in an industrial pinus taeda L. forest plantation using airborne laser scanning data and random forest Type de document : Article/Communication Auteurs : Carlos Alberto Silva, Auteur ; Carine Klauberg, Auteur ; Andrew Thomas Hudak, Auteur ; Lee Alexander Vierling, Auteur ; Wan Shafrina Wan Mohd Jaafar, Auteur ; et al., Auteur Année de publication : 2017 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] Brésil
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] modèle de simulation
[Termes IGN] Pinus taeda
[Termes IGN] plantation forestière
[Termes IGN] volume en boisRésumé : (Auteur) Improvements in the management of pine plantations result in multiple industrial and environmental benefits. Remote sensing techniques can dramatically increase the efficiency of plantation management by reducing or replacing time-consuming field sampling. We tested the utility and accuracy of combining field and airborne lidar data with Random Forest, a supervised machine learning algorithm, to estimate stem total and assortment (commercial and pulpwood) volumes in an industrial Pinus taeda L. forest plantation in southern Brazil. Random Forest was populated using field and lidar-derived forest metrics from 50 sample plots with trees ranging from three to nine years old. We found that a model defined as a function of only two metrics (height of the top of the canopy and the skewness of the vertical distribution of lidar points) has a very strong and unbiased predictive power. We found that predictions of total, commercial, and pulp volume, respectively, showed an adjusted R2 equal to 0.98, 0.98 and 0.96, with unbiased predictions of −0.17%, −0.12% and −0.23%, and Root Mean Square Error (RMSE) values of 7.83%, 7.71% and 8.63%. Our methodology makes use of commercially available airborne lidar and widely used mathematical tools to provide solutions for increasing the industry efficiency in monitoring and managing wood volume. Numéro de notice : A2017-875 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/f8070254 Date de publication en ligne : 17/07/2017 En ligne : https://doi.org/10.3390/f8070254 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91214
in Forests > vol 8 n° 7 (July 2017)[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)
[article]
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 forestierRésumé : (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
in ISPRS International journal of geo-information > vol 6 n° 6 (June 2017)[article]Forest modelling: the gamma shape mixture model and simulation of tree diameter distributions / Rafał Podlaski in Annals of Forest Science, vol 74 n° 2 (June 2017)
[article]
Titre : Forest modelling: the gamma shape mixture model and simulation of tree diameter distributions Type de document : Article/Communication Auteurs : Rafał Podlaski, Auteur Année de publication : 2017 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Végétation
[Termes IGN] arbre (flore)
[Termes IGN] densité de la végétation
[Termes IGN] diamètre à hauteur de poitrine
[Termes IGN] diamètre des arbres
[Termes IGN] dynamique de la végétation
[Termes IGN] estimation par noyau
[Termes IGN] modèle de simulation
[Termes IGN] modélisation de la forêt
[Termes IGN] surveillance de la végétationRésumé : (auteur) Key message: New types of distribution functions are needed to model the dynamics of stands where important age classes are represented by few trees. In this study, the gamma shape mixture model and two simulation methods were used for generating tree diameter data.
• Context: To analyse forest dynamics, it is necessary to know distribution of the characteristics (mainly tree diameters) of trees forming particular developmental phases. In many forest inventories, the measurement of large diameter at breast height (DBH) samples is practically impossible. In this case, DBH distributions can be generated using theoretical models.
• Aims: The aim of this study was to assess the precision of the approximation of empirical DBH data using the gamma shape mixture (GSM) model and kernel density estimation. The strengths and weaknesses of the two simulation methods were presented and discussed.
• Methods: The GSM model was adopted to approximate empirical DBH data collected in 20 near-natural stands. Two simulation methods were used: (a) the procedure based on a multimodal distribution and gamma random numbers (MDGR procedure) and (b) MCMC techniques with Metropolis–Hastings sampling (MH method).
• Results: The GSM model precisely fitted the investigated DBH distributions. The MDGR procedure was slightly more precise than the MH method, especially in the case of the samples of 250 DBHs. The level of homogeneity within the drawn DBH sets was similar for all samples.
• Conclusion: The GSM model is very flexible. The DBH random variates, generated with the use of analysed procedures, represented all tree generations being significant from a biological point of view.Numéro de notice : A2017-109 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1007/s13595-017-0629-y Date de publication en ligne : 03/04/2017 En ligne : https://doi.org/10.1007/s13595-017-0629-y Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84500
in Annals of Forest Science > vol 74 n° 2 (June 2017)[article]Performance evaluation of land change simulation models using landscape metrics / Sadeq Dezhkam in Geocarto international, vol 32 n° 6 (June 2017)PermalinkAssessing future suitability of tree species under climate change by multiple methods: a case study in southern Germany / Helge Walentowski in Annals of forest research, vol 60 n° 1 (January - June 2017)PermalinkModeling dynamic urban land-use change with geographical cellular automata and generalized pattern search-optimized rules / Yongjiu Feng in International journal of geographical information science IJGIS, vol 31 n° 5-6 (May-June 2017)PermalinkMotion priors based on goals hierarchies in pedestrian tracking applications / Francisco Madrigal in Machine Vision and Applications, vol 28 n° 3-4 (May 2017)PermalinkIntegrating cellular automata and Markov techniques to generate urban development potential surface : a study on Kolkata agglomeration / Biswajit Mondal in Geocarto international, vol 32 n° 4 (April 2017)PermalinkA GIS-based soil erosion prediction using the Revised Universal Soil Loss Equation (RUSLE) (Lebna watershed, Cap Bon, Tunisia) / I. Gaubi in Natural Hazards, Vol. 86, n° 1 (Mars 2007)PermalinkReconstructing forest canopy from the 3D triangulations of airborne laser scanning point data for the visualization and planning of forested landscapes / Jari Vauhkonen in Annals of Forest Science, vol 74 n° 1 (March 2017)PermalinkA spatial zoning approach to calibrate and validate urban growth models / Ali Kazemzadeh-Zow in International journal of geographical information science IJGIS, vol 31 n° 3-4 (March-April 2017)PermalinkCharacterizing the relationship between land use land cover change and land surface temperature / Duy X. Tran in ISPRS Journal of photogrammetry and remote sensing, vol 124 (February 2017)PermalinkTerrestrial laser scanning as a tool for assessing tree growth / Jonathan Sheppard in iForest, biogeosciences and forestry, vol 10 n° 1 (February 2017)Permalink