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Symbolic regression-based allometric model development of a mangrove forest LAI using structural variables and digital hemispherical photography / Somnath Paramanik in Applied Geography, vol 139 (February 2022)
[article]
Titre : Symbolic regression-based allometric model development of a mangrove forest LAI using structural variables and digital hemispherical photography Type de document : Article/Communication Auteurs : Somnath Paramanik, Auteur ; Mukunda Dev Behera, Auteur ; J. Dash, Auteur Année de publication : 2022 Article en page(s) : n° 102649 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] allométrie
[Termes IGN] canopée
[Termes IGN] densité de la végétation
[Termes IGN] diamètre à hauteur de poitrine
[Termes IGN] image hémisphérique
[Termes IGN] Leaf Area Index
[Termes IGN] mangrove
[Termes IGN] régressionRésumé : (auteur) The leaf area index (LAI) serves as a proxy to understand the dynamics of plant productivity, energy balance, and gas exchange. Cost-effective and accurate estimation of LAI is essential for under-assessed carbon-rich tropical forests, e.g., mangroves. Here, we developed allometric equations to estimate LAI using a combination of non-destructive, optical measurements through digital hemispherical photographs (DHP), and genetic programming-based Symbolic Regression (SR). We used three structural variables: diameter at breast height (DBH), tree density (TD), and canopy height (Ht) for a mangrove forest in the BhitarKanika Wildlife Sanctuary (BWS), located along the Eastern coast of India. Triplet combination using SR provided the best equation (R2 = 0.51) than any singlet or duplet combination of the variables, and even it was better than Partial Least Square (PLS) based regression (R2 = 0.42). To the best of our knowledge, the current study is the maiden attempt to develop an allometric model to estimate LAI for a mangrove ecosystem in India. In-situ measurements of structural variables such as DBH, Ht, and TD can be used for LAI estimates, as shown here. LAI estimates using cost-effective methods would greatly enhance our understanding of the spatial and temporal dynamics of mangrove ecosystems. Numéro de notice : A2022-456 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.apgeog.2022.102649 Date de publication en ligne : 29/01/2022 En ligne : https://doi.org/10.1016/j.apgeog.2022.102649 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101239
in Applied Geography > vol 139 (February 2022) . - n° 102649[article]3D modeling of urban area based on oblique UAS images - An end-to-end pipeline / Valeria-Ersilia Oniga in Remote sensing, vol 14 n° 2 (January-2 2022)
[article]
Titre : 3D modeling of urban area based on oblique UAS images - An end-to-end pipeline Type de document : Article/Communication Auteurs : Valeria-Ersilia Oniga, Auteur ; Ana-Ioana Breaban, Auteur ; Norbert Pfeifer, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 422 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] apprentissage automatique
[Termes IGN] Bâti-3D
[Termes IGN] CityGML
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] données lidar
[Termes IGN] image aérienne oblique
[Termes IGN] image captée par drone
[Termes IGN] indice de végétation
[Termes IGN] lasergrammétrie
[Termes IGN] modèle numérique de surface
[Termes IGN] modélisation 3D
[Termes IGN] point d'appui
[Termes IGN] Roumanie
[Termes IGN] segmentation
[Termes IGN] semis de points
[Termes IGN] zone urbaineRésumé : (auteur) 3D modelling of urban areas is an attractive and active research topic, as 3D digital models of cities are becoming increasingly common for urban management as a consequence of the constantly growing number of people living in cities. Viewed as a digital representation of the Earth’s surface, an urban area modeled in 3D includes objects such as buildings, trees, vegetation and other anthropogenic structures, highlighting the buildings as the most prominent category. A city’s 3D model can be created based on different data sources, especially LiDAR or photogrammetric point clouds. This paper’s aim is to provide an end-to-end pipeline for 3D building modeling based on oblique UAS images only, the result being a parametrized 3D model with the Open Geospatial Consortium (OGC) CityGML standard, Level of Detail 2 (LOD2). For this purpose, a flight over an urban area of about 20.6 ha has been taken with a low-cost UAS, i.e., a DJI Phantom 4 Pro Professional (P4P), at 100 m height. The resulting UAS point cloud with the best scenario, i.e., 45 Ground Control Points (GCP), has been processed as follows: filtering to extract the ground points using two algorithms, CSF and terrain-mark; classification, using two methods, based on attributes only and a random forest machine learning algorithm; segmentation using local homogeneity implemented into Opals software; plane creation based on a region-growing algorithm; and plane editing and 3D model reconstruction based on piece-wise intersection of planar faces. The classification performed with ~35% training data and 31 attributes showed that the Visible-band difference vegetation index (VDVI) is a key attribute and 77% of the data was classified using only five attributes. The global accuracy for each modeled building through the workflow proposed in this study was around 0.15 m, so it can be concluded that the proposed pipeline is reliable. Numéro de notice : A2022-101 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article DOI : 10.3390/rs14020422 Date de publication en ligne : 17/01/2022 En ligne : https://doi.org/10.3390/rs14020422 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99566
in Remote sensing > vol 14 n° 2 (January-2 2022) . - n° 422[article]
Titre : A 3D segments based algorithm for heterogeneous data registration Type de document : Article/Communication Auteurs : Rahima Djahel, Auteur ; Pascal Monasse, Auteur ; Bruno Vallet , Auteur Editeur : International Society for Photogrammetry and Remote Sensing ISPRS Année de publication : 2022 Collection : International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, ISSN 1682-1750 num. 43-B1 Projets : 1-Pas de projet / Conférence : ISPRS 2022, Commission 1, 24th ISPRS international congress, Imaging today, foreseeing tomorrow 06/06/2022 11/06/2022 Nice France OA ISPRS Archives Importance : pp 129 - 136 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] algorithme du recuit simulé
[Termes IGN] données hétérogènes
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] orthoimage
[Termes IGN] Ransac (algorithme)
[Termes IGN] reconstruction 3D
[Termes IGN] segment de droite
[Termes IGN] superposition de donnéesRésumé : (auteur) Combining image and LiDAR draws increasing interest in surface reconstruction, city and building modeling for constructing 3D virtual reality models because of their complementary nature. However, to gain from this complementarity, these data sources must be precisely registered. In this paper, we propose a new primitive based registration algorithm that takes 3D segments as features. The objective of the proposed algorithm is to register heterogeneous data. The heterogeneity is both in data type (image and LiDAR) and acquisition platform (terrestrial and aerial). Our algorithm starts by extracting 3D segments from LiDAR and image data with state of the art algorithms. Then it clusters the 3D segments of each data according to their directions. The obtained clusters are associated to find possible rotations, then 3D segments from associated clusters are matched in order to find the translation and scale factor minimizing a distance criteria between the two sets of 3D segments. Two optimizers (simulated annealing and RANSAC) are tested to minimize this distance criterion, first on synthetic data, then on real data. The experiments carried out demonstrate the robustness and speed of RANSAC compared to simulated annealing. Numéro de notice : C2022-018 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : IMAGERIE/INFORMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.5194/isprs-archives-XLIII-B1-2022-129-2022 Date de publication en ligne : 30/05/2022 En ligne : http://dx.doi.org/10.5194/isprs-archives-XLIII-B1-2022-129-2022 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100844 3D stem modelling in tropical forest: towards improved biomass and biomass change estimates / Sébastien Bauwens (2022)
Titre : 3D stem modelling in tropical forest: towards improved biomass and biomass change estimates Type de document : Thèse/HDR Auteurs : Sébastien Bauwens, Auteur Editeur : Gembloux [Belgique] : Université de Liège - Gembloux Agro-Bio Tech Année de publication : 2022 Importance : 146 p. Format : 21 x 30 cm Note générale : Bibliographie
Dissertation originale présentée en vue de l'obtention du grade de Docteur en Sciences Agronomiques et Ingénierie BiologiqueLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] analyse comparative
[Termes IGN] biomasse aérienne
[Termes IGN] cartographie et localisation simultanées
[Termes IGN] Congo
[Termes IGN] diamètre à hauteur de poitrine
[Termes IGN] dioxyde de carbone
[Termes IGN] données lidar
[Termes IGN] écosystème forestier
[Termes IGN] forêt tropicale
[Termes IGN] hauteur des arbres
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] lidar mobile
[Termes IGN] modèle de croissance végétale
[Termes IGN] modèle numérique de terrain
[Termes IGN] placette d'échantillonnage
[Termes IGN] puits de carbone
[Termes IGN] semis de points
[Termes IGN] stéréoscopie
[Termes IGN] structure-from-motion
[Termes IGN] télémétrie laser terrestreRésumé : (auteur) Tropical forests are the main contributors of CO2 emissions between the biosphere and the atmosphere in the land use sector. The deforestation and degradation of these forests are the main sources of emissions from this sector, which accounts for 15% of the world's CO2 emissions. The monitoring of CO2 emissions and removals from tropical forests requires fine measurements of their trees. These measurements are then used as inputs in allometric model to predict the tree aboveground biomass and thus indirectly their equivalent in CO2. However, a significant proportion of trees in tropical forests show morphological singularities on the stem such as buttresses or other irregularities. The height (HPOM) of the diameter measured (DPOM) is therefore commonly raised above the buttresses to reach a circular part of the stem. The standard of measuring the diameter at breast height (DBH) is then lost. In this context, this thesis aims to improve the monitoring of tropical trees with stem irregularities by using recent three-dimensional (3D) measurement tools and developing a model-based approach to harmonize height measurements of the diameterdo. First, we evaluated the potential of the close-range terrestrial photogrammetric approach (CRTP) to measure irregular shaped stems. The advantage of this 3D approach is its low cost and ease of implementation as it only requires a camera and targets. Following the convincing results of this approach, we studied the quality of the allometric relationship between variables extracted from the stem cross-section at 1.3 m height and above-ground biomass. We found that the equivalent diameter of the basal area at 1.3 m height (DBH') correlates better with aboveground tree biomass and thus its carbon content than does diameter above buttress (DPOM). Therefore, harmonization of HPOM to 1.3 m height should be further studied to improve biomass estimates. Secondly, we investigated the potential of a hand-held mobile lidar scanner (HMLS) to measure in 3D not only one tree at a time but many trees from forest plots with a 15 m radius in Belgian temperate forest. To assess the HMLS, we compared it to 3D measurements made with a more commonly used static terrestrial laser scanning (TLS) and with conventional forest inventory diameter and position measurements. The HMLS has a better 3D spatial coverage of the stems than the TLS and the precision of the stem diameter measurements is also better with the HMLS. Setting up the plot and scanning it from five locations with the TLS takes three times longer than scanning with HMLS. This pioneering work shows us the potential of using HMLS in tropical forests through its speed of execution and its important spatial coverage at the stem level, an important issue for irregular shaped tree stems. Thirdly, we developed and assessed a model-based approach for harmonizing HPOM to correct the bias induced by irregular stems in the aboveground biomass estimates of forest inventory plots. Following the estimation of DBH' using a taper model proposed in our study, we find that conventional aboveground biomass estimates (i.e. with only DPOM), compared to estimates made with DBH', show an increasing divergence with the increase of irregular stems proportion within plots and going up to -15% in our study. These results show the importance of considering HPOM when estimating aboveground biomass in tropical forests, especially in forests with many irregular stems. Estimates of the evolution of plot above-ground biomass over time should also be revised to better consider the biomass growth of irregular shaped tree stems, which has been underestimated until now. Finally, based on the results of this research, we summarize the 3D measurement tools currently available and describe their advantages and disadvantages in the case of irregular stems. Based on available human and technical resources, we also give recommendations on the harmonization method to use in permanent sampling plots to correct the bias induced by irregular stems. Improved monitoring of these tropical trees may provide a better understanding of some of the residual, i.e. unexplained, terrestrial ecosystem CO2 sink currently noted in IPCC reports. Note de contenu : 1- General introduction
2- 3D measurements of irregularly shaped stems
3- 3D stem measurements at the plot level
4- Making tropical forest plots comparable
5- DiscussionNuméro de notice : 24037 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Thèse étrangère Note de thèse : Thèse de Doctorat : Sciences Agronomiques et Ingénierie Biologique : Liège : 2022 DOI : sans En ligne : https://hdl.handle.net/2268/293900 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101855 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
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