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Classification of mediterranean shrub species from UAV point clouds / Juan Pedro Carbonell-Rivera in Remote sensing, vol 14 n° 1 (January-1 2022)
[article]
Titre : Classification of mediterranean shrub species from UAV point clouds Type de document : Article/Communication Auteurs : Juan Pedro Carbonell-Rivera, Auteur ; Jesus Torralba, Auteur ; Javier Estornell, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 199 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] apprentissage automatique
[Termes IGN] arbuste
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] classification par Perceptron multicouche
[Termes IGN] Espagne
[Termes IGN] Extreme Gradient Machine
[Termes IGN] forêt méditerranéenne
[Termes IGN] image captée par drone
[Termes IGN] incendie de forêt
[Termes IGN] indice de végétation
[Termes IGN] modèle de simulation
[Termes IGN] modèle numérique de terrain
[Termes IGN] parc naturel
[Termes IGN] photogrammétrie aérienne
[Termes IGN] semis de pointsRésumé : (auteur) Modelling fire behaviour in forest fires is based on meteorological, topographical, and vegetation data, including species’ type. To accurately parameterise these models, an inventory of the area of analysis with the maximum spatial and temporal resolution is required. This study investigated the use of UAV-based digital aerial photogrammetry (UAV-DAP) point clouds to classify tree and shrub species in Mediterranean forests, and this information is key for the correct generation of wildfire models. In July 2020, two test sites located in the Natural Park of Sierra Calderona (eastern Spain) were analysed, registering 1036 vegetation individuals as reference data, corresponding to 11 shrub and one tree species. Meanwhile, photogrammetric flights were carried out over the test sites, using a UAV DJI Inspire 2 equipped with a Micasense RedEdge multispectral camera. Geometrical, spectral, and neighbour-based features were obtained from the resulting point cloud generated. Using these features, points belonging to tree and shrub species were classified using several machine learning methods, i.e., Decision Trees, Extra Trees, Gradient Boosting, Random Forest, and MultiLayer Perceptron. The best results were obtained using Gradient Boosting, with a mean cross-validation accuracy of 81.7% and 91.5% for test sites 1 and 2, respectively. Once the best classifier was selected, classified points were clustered based on their geometry and tested with evaluation data, and overall accuracies of 81.9% and 96.4% were obtained for test sites 1 and 2, respectively. Results showed that the use of UAV-DAP allows the classification of Mediterranean tree and shrub species. This technique opens a wide range of possibilities, including the identification of species as a first step for further extraction of structure and fuel variables as input for wildfire behaviour models. Numéro de notice : A2022-057 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.3390/rs14010199 En ligne : https://doi.org/10.3390/rs14010199 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99462
in Remote sensing > vol 14 n° 1 (January-1 2022) . - n° 199[article]Guidelines for the management of cultural heritage using 3D models for the insertion of heterogeneous data / Gianna Bertacchi (2022)
Titre : Guidelines for the management of cultural heritage using 3D models for the insertion of heterogeneous data Type de document : Thèse/HDR Auteurs : Gianna Bertacchi, Auteur ; Luca Cipriani, Directeur de thèse ; Francisco Juan Vidal, Directeur de thèse Editeur : Bologne [Italie] : Université de Bologne Année de publication : 2022 Autre Editeur : Valencia : Universitat politécnica de Valencia Importance : 186 p. Format : 21 x 30 cm Note générale : bibliographie
thèse de Doctorat de l'Université de Bologne, spécialité Patrimoine culturel et environnementalLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie
[Termes IGN] acquisition de données
[Termes IGN] archéologie romaine
[Termes IGN] données hétérogènes
[Termes IGN] Espagne
[Termes IGN] gestion du patrimoine
[Termes IGN] Italie
[Termes IGN] lasergrammétrie
[Termes IGN] modélisation 3D du bâti BIM
[Termes IGN] monument historique
[Termes IGN] patrimoine culturel
[Termes IGN] qualité des données
[Termes IGN] stockage de donnéesIndex. décimale : THESE Thèses et HDR Résumé : (auteur) The Management of Cultural Heritage (MCH) is a very complex operation aimed at protecting the physical integrity of Cultural Heritage assets, while promoting their historical value and development of tourism industry. Composed by distinct phases (documentation, intervention, monitoring and use), MCH implies a great effort for the project manager to coordinate the interactions among very different professional figures. In recent years, the use of digital technologies has become an essential part of the MCH delicate process, from early documentation to late intervention phases. The most commonly used methodologies for digital data acquisition, such as terrestrial laser scanning and digital photogrammetry, have become common practice in a broad range of professional activities. On the contrary, the use of 3D models for MCH is still limited to few academic research to date, often lacking continuity and wide application after the end of specific projects. Furthermore, very few supra-national standard guidelines regulating their use are available to date. As a consequence, the operator who decides to use a 3D model as a basis for management is faced with the scarcity and fragmentation of standards and guidelines. Moreover, the lack of standard on quality of acquired data and digital products negatively influences the interaction between the academic research sector, the managers and the professional world. The focus is on the use of 3D models as a valid support tool in the MCH process, highlighting their advantages in all the distinct phases of the management. As an example, 3D data can constitute themselves the basis for the digital database, gathering all available information concerning a Cultural Heritage site, exploitable for restoration works or for scientific dissemination. In particular, the aim of this PhD research is to develop guidelines to produce 3D models for MCH, with the purpose to efficiently entry, store and manage digital data. The here provided guidelines investigate every aspect of the process leading from data acquisition to cataloguing and archiving, processing and creation of a simplified information system. Each recommendation guides the user through the management of digital data, by adapting to his/her level of knowledge with respect to digital technologies and methodologies. In this way, the manager can efficiently use 3D models in MCH projects. In order to elaborate guidelines that could be suitable for as many typologies of Cultural Heritage as possible an international approach was chosen, developing the thesis in joint supervision under the University of Bologna and the Universitat Politècnica de València. We decided to apply state-of-the-art technologies and methodologies to a variety of case studies. The main ones are the early Christian monuments of Ravenna (Italy) belonging to the UNESCO World Heritage List, and a small neogothic chapel located in Castellón de la Plana (Spain). The fruitful collaboration between two different countries allowed an invaluable exchange of MCH expertise and, more broadly, contributed to the elaboration of standardized and universally applicable MCH guidelines that will allow a better interaction between managers, the academic research world and the professional one. The investigation, by highlighting the problems inherent to the MCH, made it possible to identify the main open issues that need to be explored in future lines of research, such as the application of standards to a large number of cultural assets in an iterative, continuous and automatic way, in order to perfecting the standards; the search for automatic classification of raw data; the processing of collected data for the creation of relations, strategies and methods for the classification, integration and optimisation of heterogeneous data. Note de contenu : Chapter 1 - Introduction and premises
Chapter 2- State of the art
Chapter 3- Hypotheses and objectives
Chapter 4- Methodology and development
Chapter 5- Discussions on the results: Guidelines
Chapter 6- Conclusions and future lines of researchNuméro de notice : 24073 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse étrangère Note de thèse : PhD Thesis : Cultural and Environmental Heritage : Bologne : 2022 DOI : 10.4995/Thesis/10251/182419 En ligne : https://doi.org/10.4995/Thesis/10251/182419 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102154 New insights in the modeling and simulation of tree and stand level variables in Mediterranean mixed forests in the present context of climate change / Diego Rodríguez de Prado (2022)
Titre : New insights in the modeling and simulation of tree and stand level variables in Mediterranean mixed forests in the present context of climate change Type de document : Thèse/HDR Auteurs : Diego Rodríguez de Prado, Auteur ; Celia Herrero de Aza, Directeur de thèse ; Felipe Bravo Oviedo, Directeur de thèse Editeur : Valladolid [Espagne] : Université de Valladolid Année de publication : 2022 Importance : 168 p. Format : 21 x 30 cm Note générale : bibliographie
Doctoral dissertation, Valladolid UniversityLangues : Anglais (eng) Descripteur : [Termes IGN] allométrie
[Termes IGN] climat aride
[Termes IGN] croissance des arbres
[Termes IGN] Espagne
[Termes IGN] Fagus sylvatica
[Termes IGN] forêt méditerranéenne
[Termes IGN] gestion forestière adaptative
[Termes IGN] hauteur des arbres
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] modélisation de la forêt
[Termes IGN] peuplement mélangé
[Termes IGN] Pinus nigra
[Termes IGN] Pinus pinaster
[Termes IGN] Pinus sylvestris
[Termes IGN] puits de carbone
[Termes IGN] Quercus pyrenaica
[Vedettes matières IGN] Végétation et changement climatiqueIndex. décimale : THESE Thèses et HDR Résumé : (auteur) An increase of droughts intensity and frequency episodes combined with new extreme climate events are predicted to appear in the Mediterranean Basin due to global warming. In this context, mixed forests have become a sustainable opportunity to mitigate the effects of climate change. Species mixing may lead to the provision of a greater variety of ecosystem services and products while increasing temporal stability compared to pure forests. The development of new models that explain different tree and stand level variables may be vital to better understand the structure, composition and dynamics of this type of forests. In addition, it is essential to analyze how climate may influence these variables in order to design adaptive and sustainable management guidelines for mixed forests under future climate change scenarios. In this study, we sought to advance in the modelization and simulation of different tree and stand level variables along a range of different forest and aridity conditions in Spain. To achieve that, climate-dependent models were fitted using data from the Spanish National Forest Inventory and the WorldClim databases. We focused our study on fifteen Mediterranean tree species from the Pinus, Quercus, and Fagus genus. In our first study, we analyzed how climate may potentially influence the maximum stand carrying capacity, by terms of the maximum stand carrying capacity (SDImax), for the species under study in pure stands. This variable was chosen because its importance in (1) managing density and (2) defining species mixing proportions in mixed forest stands. To do that, climate-dependent MSDR models were fitted for each species under study. 35 different climatic annual and seasonal variables (temperature, precipitation, evapotranspiration, aridity indexes) were simultaneously included into the models. In this study, climate was found to have significant influence on MSDR, and therefore on the maximum stand carrying capacity (SDImax). The best climate-dependent MSDR models indicated that climatic variables related to temperature better explained the influence of climate on MSDR. Specifically, seasonal (MXTi) and annual (MXT) maximum temperatures were the most representative climatic variables explaining changes in MSDR. Based on the selected seasonal variables, spring and summer were consistently appeared as key periods. A common trend in SDImax variation for coniferous and broadleaf species was found, with higher SDImax values negatively linked to temperature and positively linked to precipitation. This trend suggested that aridity may play a key role reducing the maximum stand 12 carrying capacity of the main Mediterranean tree species. In addition, the impact of climate on maximum stand carrying capacity was evaluated by the creation of the Q index. In general, broadleaved species presented higher values of Q indexes than coniferous species, suggesting that the maximum stand carrying capacity of the first ones would suffer more the influence of potential climate changes. Our findings highlight the importance of using specific climatic variables to better characterize how they affect MSDR. Since we saw that aridity could play a key role influencing stand level variables such as SDImax, we aimed to analyze how it may influence tree growth and tree allometry. Moreover, we aimed to analyze how species mixing effects may influence these variables on mixed forests. Thus, two more studies focused on 29 two-species Mediterranean mixtures were developed. To study the influence of aridity and species mixing on tree growth, the basal area increment within a span of five years (BAI5), was modelled based on individual tree size, stand development and other variables of site and competition. Two distance independent competition indexes were considered: total stand basal area (BA) representing size-symmetric competition, and the basal area of trees larger than the subject tree (BAL) representing size-asymmetric competition. To uncover the complex mixing effects on basal area increment at tree level, competition indexes were splitting into intraspecific and interspecific components. All possible combinations of competition structures were included and tested in the BAI models. Positive, negative or neutral mixing effects were determined by comparing the intraspecific and interspecific component of the selected models. Then, the biological interactions taking place between species were determined based on size-symmetric and sizeasymmetric competition. Finally, the influence of aridity on basal area increment was studied including the De Martonne Index into the BAI models. A common trend among mixtures was found with higher productivity in mixed than pure stands, suggesting that BAI values may increase with the increment of species diversity. Based on model parameters, a novel approach to determine potential biological interactions between species in mixed forests was also presented in this study. Competition seemed to be the most representative biological interaction in coniferconifer mixtures, since neutralism and facilitation may occur more frequently in conifer-broadleaved and broadleaved-broadleaved mixtures. Our findings also suggested that tree productivity may be significantly limited by arid conditions, excepting for Pinus halepensis and Pinus pinea [...] Note de contenu : 1- Introduction
2- Objectives
3- Data
4- Methods
5- Results
6- Discussion
ConclusionNuméro de notice : 24064 Affiliation des auteurs : non IGN Thématique : FORET Nature : Thèse étrangère Note de thèse : Thèse de Doctorat : Systemes Forestiers Durables : Valladolid : 2022 Organisme de stage : Sustainable Forest Management Research Institute (Université de Valladolid) DOI : sans En ligne : https://uvadoc.uva.es/handle/10324/55195 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102046 Towards synthetic sensing for smart cities : a machine/deep learning-based approach / Faraz Malik Awan (2022)
Titre : Towards synthetic sensing for smart cities : a machine/deep learning-based approach Type de document : Thèse/HDR Auteurs : Faraz Malik Awan, Auteur ; Noël Crespi, Directeur de thèse ; Roberto Minerva, Directeur de thèse Editeur : Courcouronnes : Télécom SudParis Année de publication : 2022 Importance : 106 p. Format : 21 x 30 cm Note générale : bibliographie
Thèse de doctorat de l’Institut Polytechnique de Paris préparée à Telecom SudParis, Spécialité InformatiqueLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Intelligence artificielle
[Termes IGN] analyse comparative
[Termes IGN] apprentissage automatique
[Termes IGN] apprentissage profond
[Termes IGN] classification par arbre de décision
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] classification par Perceptron multicouche
[Termes IGN] Espagne
[Termes IGN] parking
[Termes IGN] plus proche voisin, algorithme du
[Termes IGN] pollution acoustique
[Termes IGN] pollution atmosphérique
[Termes IGN] réseau neuronal récurrent
[Termes IGN] système de transport intelligent
[Termes IGN] trafic routier
[Termes IGN] ville intelligenteIndex. décimale : THESE Thèses et HDR Résumé : (auteur) We worked on one of the most significant research directions in Smart City, i.e., Intelligent Transportation System (ITS). ITS encapsulates several domains, such as electronic vehicles notification systems, traffic information, smart parking, and environment. However, in this thesis, we target two of its important domains; i) Smart Parking, and ii) Road Traffic. We started our research with Smart Parking use case. Performing literature review, we realized that different Machine Learning (ML) and Deep Learning (DL) approaches have been used for smart parking solutions. In most of these proposed approaches, enclosed parking areas were targeted with different feature sets to predict the "occupancy rate" in parking areas. It inspired us to conduct a comparative analysis to answer following questions; Given the parking prediction use case, how do the traditional ML models perform as compared to complex DL models? Provided big data, can less complex, traditional ML models outperform complex DL models? How well these models can perform to predict the availability of the individual on-street parking spots rather than predicting the overall occupancy rate of an enclosed parking area. To answer these questions, we choose five well-known classical ML algorithms (K-Nearest Neighbours, Random Forest, Decision Tree) and DL algorithm (Multilayer Perceptron). To take our investigation into depth, we train Ensemble Learning Model, in which we combine all the above-mentioned ML and DL models. A huge parking dataset of city of Santander, Spain, has been used which consists of around 25 million records. We also propose to recommend available parking spots based on the current location of the driver. Moving forward with our research goals, we performed literature review on road traffic and found road traffic associated with air pollution and noise pollution often. However, to the best of our knowledge, air pollution & noise pollution have never been use d in traffic prediction problem. In this part of our research, firstly we used air pollution (CO, NO, NO2, NOx, and O3) along with the atmospheric variables, such as wind speed, wind direction, temperature, and pressure to improve the traffic forecasting in the city of Madrid. This successful experiment motivated us to extend our investigation to another factor, which is also strongly correlated with road traffic i.e., noise pollution. Hence, as an extension of our previous work, in this part of our research, we use noise pollution to improve the traffic prediction in the city of Madrid. Note de contenu : 1- Introduction
2- Parking space prediction using classical ML and deep learning models
3- Road traffic prediction improvement using air pollution and atmospheric data
4- Using noise pollution to improve traffic prediction
5- Conclusion and future workNuméro de notice : 20025 Affiliation des auteurs : non IGN Thématique : INFORMATIQUE/URBANISME Nature : Thèse française Note de thèse : Thèse de Doctorat : Informatique : Telecom SudParis : 2022 Organisme de stage : SAMOVAR DOI : sans En ligne : https://tel.hal.science/tel-03722891/ Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101825 Shifting precipitation patterns drive growth variability and drought resilience of European Atlas cedar plantations / J. Julio Camarero in Forests, vol 12 n° 12 (December 2021)
[article]
Titre : Shifting precipitation patterns drive growth variability and drought resilience of European Atlas cedar plantations Type de document : Article/Communication Auteurs : J. Julio Camarero, Auteur ; Antonio Gazol, Auteur ; Michele Colangelo, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 1751 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] Cedrus atlantica
[Termes IGN] croissance des arbres
[Termes IGN] dendroécologie
[Termes IGN] Espagne
[Termes IGN] France (administrative)
[Termes IGN] précipitation
[Termes IGN] saison
[Termes IGN] sécheresse
[Termes IGN] stress hydrique
[Vedettes matières IGN] Végétation et changement climatiqueRésumé : (auteur) Tree plantations have been proposed as suitable carbon sinks to mitigate climate change. Drought may reduce their carbon uptake, increasing their vulnerability to stress and affecting their growth recovery and resilience. We investigated the recent growth rates and responses to the climate and drought in eight Atlas cedar (Cedrus atlantica) plantations located along a wide climate gradient from wetter sites in south-eastern France and north Spain to dry sites in south-eastern Spain. The cedar growth increased in response to the elevated precipitation from the prior winter to the current summer, but the influence of winter precipitation on growth gained importance in the driest sites. The growth responsiveness to climate and drought peaked in those dry sites, but the growth resilience did not show a similar gradient. The Atlas cedar growth was driven by the total precipitation during the hydrological year and this association strengthened from the 1980s onwards, a pattern related to the winter North Atlantic Oscillation (NAO). High winter NAO indices and drier conditions were associated with lower growth. At the individual level, growth resilience was related to tree age, while growth recovery and year-to-year growth variability covaried. Plantations’ resilience to drought depends on both climate and tree-level features. Numéro de notice : A2021-126 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.3390/f12121751 Date de publication en ligne : 11/12/2021 En ligne : https://doi.org/10.3390/f12121751 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99319
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