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Multi-temporal remote sensing data to monitor terrestrial ecosystem responses to climate variations in Ghana / Ram Avtar in Geocarto international, vol 37 n° 2 ([15/01/2022])
[article]
Titre : Multi-temporal remote sensing data to monitor terrestrial ecosystem responses to climate variations in Ghana Type de document : Article/Communication Auteurs : Ram Avtar, Auteur ; Ali P. Yunus, Auteur ; Osamu Saito, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 396 - 412 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] changement climatique
[Termes IGN] données multitemporelles
[Termes IGN] écosystème
[Termes IGN] Ghana
[Termes IGN] image Landsat
[Termes IGN] image SPOT
[Termes IGN] image Terra-MODIS
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] phénologie
[Termes IGN] variation temporelleRésumé : (auteur) Operational monitoring of vegetation and its response to climate change involves the use of vegetation indices (VIs) in relation to relevant climatic data. This study analyses the temporal variations of vegetation indices in response to climatic data (temperature and precipitation) to better understand the phenological changes in the Wa-West and Tolon districts of Ghana during 1999–2011. This study also examines the inter-annual variation of vegetation indices and lag effects of climate variables (temperature and precipitation) using simple regression and correlation approaches. Results indicate that the mean Normalized Difference Vegetation Index (NDVI) and Normalized Difference Soil Index (NDSI) were significantly correlated with the mean temperature, whereby the value of NDVI increases with a decrease in temperature and value of NDSI increases with an increase in temperature. On examining seasonal variations, our findings indicated that the months of August and September have the highest mean NDVI values. This study confirms that consistently rising temperature and altered precipitation patterns have exerted a strong influence on temporal distributions and productivities of the terrestrial ecosystems of the Tolon and Wa-West districts of Ghana. Furthermore, this research demonstrates how vegetation indices can be used as an indicator to monitor phenological changes in the terrestrial ecosystem. Numéro de notice : A2022-050 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2020.1723716 Date de publication en ligne : 11/02/2020 En ligne : https://doi.org/10.1080/10106049.2020.1723716 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99442
in Geocarto international > vol 37 n° 2 [15/01/2022] . - pp 396 - 412[article]Use of remotely sensed data to estimate tree species diversity as an indicator of biodiversity in Blouberg Nature Reserve, South Africa / Mangana Rampheri in Geocarto international, vol 37 n° 2 ([15/01/2022])
[article]
Titre : Use of remotely sensed data to estimate tree species diversity as an indicator of biodiversity in Blouberg Nature Reserve, South Africa Type de document : Article/Communication Auteurs : Mangana Rampheri, Auteur ; Timothy Dube, Auteur ; Inos Dhau, Auteur Année de publication : 2022 Article en page(s) : pp 526 - 542 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Afrique du sud (état)
[Termes IGN] arbre (flore)
[Termes IGN] bande spectrale
[Termes IGN] biodiversité végétale
[Termes IGN] conservation de la flore
[Termes IGN] détection de changement
[Termes IGN] espèce végétale
[Termes IGN] image Landsat-OLI
[Termes IGN] image Landsat-TM
[Termes IGN] indice de végétation
[Termes IGN] régression
[Termes IGN] réserve naturelleRésumé : (auteur) We use remotely sensed data to estimate species diversity in Blouberg Nature Reserve (BNR) in the Limpopo province, South Africa to understand the state of biodiversity since communities’ involvement in conservation initiatives. To achieve this objective, Landsat series data collected before and after community involvement in biodiversity conservation were used in conjunction with selected diversity indices i.e., Shannon-Wiener Index (H’) and Simpson Index (D). Thirty 15 m × 15 m field plots were selected and all trees within each plot were identified, with the help of Botanists. Further, we applied regression analysis to determine the relationship between satellite derived tree species diversity and field observations. The results of the study demonstrated a significant (p Numéro de notice : A2022-052 Affiliation des auteurs : non IGN Thématique : BIODIVERSITE/FORET/IMAGERIE Nature : Article DOI : 10.1080/10106049.2020.1723717 Date de publication en ligne : 16/04/2020 En ligne : https://doi.org/10.1080/10106049.2020.1723717 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99443
in Geocarto international > vol 37 n° 2 [15/01/2022] . - pp 526 - 542[article]Variable selection for estimating individual tree height using genetic algorithm and random forest / Evandro Nunes Miranda in Forest ecology and management, vol 504 (January-15 2022)
[article]
Titre : Variable selection for estimating individual tree height using genetic algorithm and random forest Type de document : Article/Communication Auteurs : Evandro Nunes Miranda, Auteur ; Bruno Henrique Groenner Barbosa, Auteur ; Sergio Henrique Godinho Silva, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 119828 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] apprentissage automatique
[Termes IGN] Brésil
[Termes IGN] classification par algorithme génétique
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] diamètre à hauteur de poitrine
[Termes IGN] hauteur des arbres
[Termes IGN] modélisation de la forêt
[Termes IGN] optimisation (mathématiques)
[Vedettes matières IGN] ForesterieRésumé : (auteur) Tree height is an important trait in forest science and is highly associated with the site quality from which the trees are measured. However, other factors, such as competition and species interaction, may yield better estimates for individual tree height when taken into account, but these variables have so far been challenging in model fitting. We propose a hybrid approach using genetic algorithms for variables selection and a machine learning algorithm (random forest) for fitting models of individual tree heights. We compare our proposed hybrid method with a mixed-effects model and random forest model using a dataset of 5,608 trees and 189 environmental variables (forest inventory-based variables, soil, topographic, climate, spectral, and geographic) from sites in southeastern Brazil. The tree height models were evaluated using the coefficient of determination, absolute bias, and root means square error (RMSE) based on the validation of dataset performance. The optimal set of variables of the proposed method include the ratio of diameter at breast height to quadratic mean diameter, distance independent competition index, dominant height, the soil silt and boron content. Our findings showed that the proposed hybrid method achieved an accuracy comparable with other methodologies in estimating the total height of the individual trees, and such a modelling approach could have broader applications in forestry and ecological science where a studied response trait has a large number of potential explanatory variables. Numéro de notice : A2022-021 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1016/j.foreco.2021.119828 Date de publication en ligne : 06/11/2021 En ligne : https://doi.org/10.1016/j.foreco.2021.119828 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99216
in Forest ecology and management > vol 504 (January-15 2022) . - n° 119828[article]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 Above-ground biomass estimation in a Mediterranean sparse coppice oak forest using Sentinel-2 data / Fardin Moradi in Annals of forest research, vol 65 n° 1 (January - June 2022)
[article]
Titre : Above-ground biomass estimation in a Mediterranean sparse coppice oak forest using Sentinel-2 data Type de document : Article/Communication Auteurs : Fardin Moradi, Auteur ; Seyed Mohammad Moein Sadeghi, Auteur ; Hadi Beygi Heidarlou, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 165 - 182 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] allométrie
[Termes IGN] biomasse aérienne
[Termes IGN] classification barycentrique
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] classification par Perceptron multicouche
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] forêt méditerranéenne
[Termes IGN] image proche infrarouge
[Termes IGN] image Sentinel-MSI
[Termes IGN] indice de végétation
[Termes IGN] Iran
[Termes IGN] Quercus brantii
[Termes IGN] taillisRésumé : (auteur) Implementing a scheduled and reliable estimation of forest characteristics is important for the sustainable management of forests. This study aimed at evaluating the capability of Sentinel-2 satellite data to estimate above-ground biomass (AGB) in coppice forests of Persian oak (Quercus brantii var. persica) located in Western Iran. To estimate the AGB, field data collection was implemented in 80 square plots (40×40 m, area of 1600 m2). Two diameters of the crown were measured and used to calculate the AGB of each tree based on allometric equations. Then, the performance of satellite data in estimating the AGB was evaluated for the area of study using the field-based AGB (dependent variable) as well as the spectral band values, spectrally-derived vegetation indices (independent variables) and four machine learning (ML) algorithms: MultiLayer Perceptron Artificial Neural Network (MLPNN), k-Nearest Neighbor (kNN), Random Forest (RF), and Support Vector Regression (SVR). A five-fold cross-validation was used to verify the effectiveness of models. Examination of the Pearson’s correlation coefficient between AGB and the extracted values showed that IPVI and NDVI vegetation indices had the highest correlation with AGB (r = 0.897). The results indicated that the MLPNN algorithm was the best ML option (RMSE = 1.71 t ha-1; MAE = 1.37 t ha-1; relative RMSE = 24.75%; R2 = 0.87) in estimating the AGB, providing new insights on the capability of remotely sensed-based AGB modeling of sparse Mediterranean forest ecosystems in an area with limited number of field sample plots. Numéro de notice : A2022-876 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.15287/afr.2022.2390 Date de publication en ligne : 29/06/2022 En ligne : https://doi.org/10.15287/afr.2022.2390 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102180
in Annals of forest research > vol 65 n° 1 (January - June 2022) . - pp 165 - 182[article]Adaptation of the standardized vegetation optical depth index for satellite-based soil moisture / Juliette Raabe (2022)PermalinkAirborne LiDAR and high resolution multispectral data integration in Eucalyptus tree species mapping in an Australian farmscape / Niva Kiran Verma in Geocarto international, vol 37 n° 1 ([01/01/2022])PermalinkAn assessment of forest loss and its drivers in protected areas on the Copperbelt province of Zambia: 1972–2016 / Darius Phiri in Geomatics, Natural Hazards and Risk, vol 13 (2022)PermalinkApplication of deep learning with stratified K-fold for vegetation species discrimation in a protected mountainous region using Sentinel-2 image / Efosa Gbenga Adagbasa in Geocarto international, vol 37 n° 1 ([01/01/2022])PermalinkApport de la télédétection et des variables auxiliaires dans l'étude de l'évolution des périodes de sécheresse / Nesrine Farhani (2022)PermalinkBeech and hornbeam dominate oak 20 years after the creation of storm-induced gaps / Lucie Dietz in Forest ecology and management, vol 503 (January-1 2022)PermalinkPermalinkCharacteristics of taiga and tundra snowpack in development and validation of remote sensing of snow / Henna-Reetta Hannula (2022)PermalinkClassification of mediterranean shrub species from UAV point clouds / Juan Pedro Carbonell-Rivera in Remote sensing, vol 14 n° 1 (January-1 2022)PermalinkA comparison of linear-mode and single-photon airborne LiDAR in species-specific forest inventories / Janne Raty in IEEE Transactions on geoscience and remote sensing, vol 60 n° 1 (January 2022)Permalink