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Scorch height and volume modeling in prescribed fires: Effects of canopy gaps in Pinus pinaster stands in Southern Europe / J.R. Molina in Forest ecology and management, vol 506 (15 February 2022)  

Public [article]  inForest ecology and management > vol 506 (15 February 2022) . - n° 119979 Titre : Scorch height and volume modeling in prescribed fires: Effects of canopy gaps in Pinus pinaster stands in Southern Europe Type de document : Article/Communication Auteurs : J.R. Molina, Auteur ; M. Ortega, Auteur ; F. Rodríguez y Silva, Auteur Année de publication : 2022 Article en page(s) : n° 119979 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] brûlis [Termes IGN] canopée [Termes IGN] échantillonnage de données [Termes IGN] Espagne [Termes IGN] gestion des risques [Termes IGN] gestion forestière [Termes IGN] incendie de forêt [Termes IGN] Pinus pinaster [Vedettes matières IGN] Foresterie Résumé : (auteur) The use of prescribed fire has been on the rise in recent years owing to its effectiveness in surface fuel reduction, its implementation cost, and the possibility of firefighter training. However, greater knowledge regarding the effects of fire on woodlands is required by forest managers. Scorch height and scorch volume are the most widely used variables for evaluating the effects of burning on trees. This study proposes a scorch height model for the prescribed fires of pine stands in Southern Europe. Although the two main variables of the existing models (fire-line intensity and air temperature) were considered, our model achieved a coefficient of determination of 89% with the incorporation of the canopy base height. A decision tree for scorch volume was also developed using the three independent variables. The presence of canopy gaps in the lower, mid-, and upper slopes resulted in significant differences in the scorch height. The scorch height increased between 0.33 m and 2.08 m because of the canopy gaps in the upper slope. These findings can play an important role in the implementation and improvement of prescribed burn windows. Numéro de notice : A2022-058 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1016/j.foreco.2021.119979 Date de publication en ligne : 24/12/2021 En ligne : https://doi.org/10.1016/j.foreco.2021.119979 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99469 [article]

Assessing the agreement of ICESat-2 terrain and canopy height with airborne lidar over US ecozones / Lonesome Malambo in Remote sensing of environment, vol 266 (December 2021)  

Public [article]  inRemote sensing of environment > vol 266 (December 2021) . - n° 112711 Titre : Assessing the agreement of ICESat-2 terrain and canopy height with airborne lidar over US ecozones Type de document : Article/Communication Auteurs : Lonesome Malambo, Auteur ; Sorin C. Popescu, Auteur Année de publication : 2021 Article en page(s) : n° 112711 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] biome [Termes IGN] canopée [Termes IGN] données altimétriques [Termes IGN] données ICEsat [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] écorégion [Termes IGN] Etats-Unis [Termes IGN] hauteur des arbres [Termes IGN] photon [Termes IGN] semis de points [Termes IGN] télémétrie laser aéroporté Résumé : (auteur) Despite its critical importance to carbon storage modeling, forest vertical structure remains poorly characterized over large areas. Canopy height estimates from current satellite missions such as ICESat-2 (Ice, Cloud, and land Elevation Satellite-2) offer promise to close this knowledge gap, but their validation is critically important to inform their measurement uncertainties and scientific utility. Using existing airborne laser scanning (ALS) data, the agreement of a variety of terrain and aboveground canopy height metrics including summary height statistics and percentiles, from ICESat-2’ Land, Water and Vegetation Elevation product (ATL08) product was assessed in 12 sites across six major biomes in the United States. The agreement between ATL08 and ALS heights was assessed using the mean bias (Bias, ATL08 – ALS), the mean absolute error (MAE) and their percent equivalents, percent bias (pBias) and percent MAE (pMAE), respectively. In general, the agreement between ATL08 and ALS terrain heights was high (Bias 0.18 m, pBias 0.1%) while canopy heights showed lower agreement (Bias −1.71 m, pBias −15.9%). Analyses by biome, time of acquisition and beam strength of the ICESat-2 photon data also showed generally higher agreement for ATL08 terrain than canopy heights. Analyses also showed the performance of ATL08 heights varied with canopy cover with ATL08 terrain heights showing the best agreement when canopy cover was between 40 and 70% while the best performance for ATL08 canopy heights was observed when canopy cover was greater than 80%. This observation, coupled with analyses by biome, indicate that ATL08 canopy heights are more suitable in relatively dense canopy environments such as conifer and broadleaf forests than relatively sparse environments such a temperate grassland and Savannas. Higher level canopy height percentiles (95th and 98th) showed higher agreement (mean Bias −12.5%) with ALS heights than lower percentiles (minimum, 25th, mean pBias ~39.2%). These findings indicate that ATL08 canopy heights show more promise for routine canopy height characterization using the 95th and 98% percentiles but is limited in characterizing intermediate vertical structure. The observed performance differences between ATL08 terrain and canopy heights are attributed to differences in photon sampling rates over terrain and canopy surfaces which, compounded with background noise in ICESat-2 photon data, led to different effectiveness for ATL08 processing routines in filtering terrain and off-terrain points. This assessment of the impact of a variety of factors provides the vegetation community with an understanding of the capabilities and limitations of height estimates from the ICESat-2 ATL08 product. Numéro de notice : A2021-922 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.rse.2021.112711 Date de publication en ligne : 24/09/2021 En ligne : https://doi.org/10.1016/j.rse.2021.112711 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99277 [article]

Forest floor alteration by canopy trees and soil wetness drive regeneration of a spruce-beech forest / Pavel Daněk in Forest ecology and management, vol 504 (15 January 2022)  

Public [article]  inForest ecology and management > vol 504 (15 January 2022) . - n° 119802 Titre : Forest floor alteration by canopy trees and soil wetness drive regeneration of a spruce-beech forest Type de document : Article/Communication Auteurs : Pavel Daněk, Auteur ; Pavel Šamonil, Auteur ; Libor Hort, Auteur Année de publication : 2021 Article en page(s) : n° 119802 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] bois mort [Termes IGN] canopée [Termes IGN] Fagus sylvatica [Termes IGN] humidité du sol [Termes IGN] litière [Termes IGN] peuplement mélangé [Termes IGN] Picea abies [Termes IGN] régénération (sylviculture) [Termes IGN] République Tchèque [Termes IGN] semis (sylviculture) [Termes IGN] sol forestier [Vedettes matières IGN] Foresterie Résumé : (auteur) Natural regeneration of European beech (Fagus sylvatica) and Norway spruce (Picea abies) plays a crucial role in the future of many European mountain forests. It is affected by various soil and stand-related factors whose relative importance, especially in mixed stands, is still not known. In this study, we assessed the importance of stand composition, soil wetness, disturbances and different microsites and seedbeds for regeneration of beech and spruce in a mixed old-growth mountain forest. We also focused on how the effects of these factors change as regeneration gets older. We sampled all regeneration in 563 plots from different microsite types (deadwood, intact soil, treethrow pits and mounds), distinguishing three seedbeds (mosses, beech litter, bare substrate) for seedlings. We used soil survey and tree census data with generalized linear mixed models and variance partitioning to identify the main factors driving tree regeneration and their relative importance. Although beech was slightly less abundant in the canopy than spruce, it strongly outnumbered spruce in regeneration. Beech regeneration showed an affinity for beech litter-rich microsites and drier soils, while spruce was more common on deadwood and moister soils and its response to the seedbed was microsite-specific. The regeneration of both species was positively related to the proportion of their own species in the canopy, but more so in seedlings than in older regeneration cohorts, where soil wetness was more important. The overall pattern of tree regeneration thus resulted from a complex interplay between site conditions and their alterations by current and former generations of canopy trees through the creation of new microsites (deadwood, uprooting mounds) or litter production. Where beech regeneration is not suppressed by excess soil wetness, it is much more successful than spruce due to its shade tolerance and ability to be established in the beech litter that dominates the forest floor. On the other hand, spruce regeneration is mostly restricted to elevated microsites with lower litter accumulation, such as deadwood and treethrow mounds. Our results indicate that both species exhibit an ability to modify their environment in favor of their own regeneration, but under current conditions, beech is more successful than spruce and can be expected to increase its dominance in the future. Numéro de notice : A2022-022 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1016/j.foreco.2021.119802 Date de publication en ligne : 04/11/2021 En ligne : https://doi.org/10.1016/j.foreco.2021.119802 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99214 [article]

Monitoring leaf phenology in moist tropical forests by applying a superpixel-based deep learning method to time-series images of tree canopies / Guangqin Song in ISPRS Journal of photogrammetry and remote sensing, vol 183 (January 2022)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 183 (January 2022) . - pp 19 - 33 Titre : Monitoring leaf phenology in moist tropical forests by applying a superpixel-based deep learning method to time-series images of tree canopies Type de document : Article/Communication Auteurs : Guangqin Song, Auteur ; Shengbiao Wu, Auteur ; Calvin K.F. Lee, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 19 - 33 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] apprentissage profond [Termes IGN] canopée [Termes IGN] classification dirigée [Termes IGN] diagnostic foliaire [Termes IGN] Enhanced vegetation index [Termes IGN] feuille (végétation) [Termes IGN] forêt tropicale [Termes IGN] Panama [Termes IGN] phénologie [Termes IGN] photosynthèse [Termes IGN] segmentation sémantique [Termes IGN] série temporelle [Termes IGN] SLIC algorithm [Termes IGN] superpixel [Termes IGN] variation saisonnière Résumé : (auteur) Tropical leaf phenology—particularly its variability at the tree-crown scale—dominates the seasonality of carbon and water fluxes. However, given enormous species diversity, accurate means of monitoring leaf phenology in tropical forests is still lacking. Time series of the Green Chromatic Coordinate (GCC) metric derived from tower-based red–greenblue (RGB) phenocams have been widely used to monitor leaf phenology in temperate forests, but its application in the tropics remains problematic. To improve monitoring of tropical phenology, we explored the use of a deep learning model (i.e. superpixel-based Residual Networks 50, SP-ResNet50) to automatically differentiate leaves from non-leaves in phenocam images and to derive leaf fraction at the tree-crown scale. To evaluate our model, we used a year of data from six phenocams in two contrasting forests in Panama. We first built a comprehensive library of leaf and non-leaf pixels across various acquisition times, exposure conditions and specific phenocams. We then divided this library into training and testing components. We evaluated the model at three levels: 1) superpixel level with a testing set, 2) crown level by comparing the model-derived leaf fractions with those derived using image-specific supervised classification, and 3) temporally using all daily images to assess the diurnal stability of the model-derived leaf fraction. Finally, we compared the model-derived leaf fraction phenology with leaf phenology derived from GCC. Our results show that: 1) the SP-ResNet50 model accurately differentiates leaves from non-leaves (overall accuracy of 93%) and is robust across all three levels of evaluations; 2) the model accurately quantifies leaf fraction phenology across tree-crowns and forest ecosystems; and 3) the combined use of leaf fraction and GCC helps infer the timing of leaf emergence, maturation and senescence, critical information for modeling photosynthetic seasonality of tropical forests. Collectively, this study offers an improved means for automated tropical phenology monitoring using phenocams. Numéro de notice : A2022-009 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2021.10.023 Date de publication en ligne : 10/11/2021 En ligne : https://doi.org/10.1016/j.isprsjprs.2021.10.023 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99057 [article]

Semantic unsupervised change detection of natural land cover with multitemporal object-based analysis on SAR images / Donato Amitrano in IEEE Transactions on geoscience and remote sensing, Vol 59 n° 7 (July 2021)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > Vol 59 n° 7 (July 2021) . - pp 5494 - 5514 Titre : Semantic unsupervised change detection of natural land cover with multitemporal object-based analysis on SAR images Type de document : Article/Communication Auteurs : Donato Amitrano, Auteur ; Raffaella Guida, Auteur ; Pasquale Lervolino, Auteur Année de publication : 2021 Article en page(s) : pp 5494 - 5514 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] analyse d'image orientée objet [Termes IGN] biomasse forestière [Termes IGN] canopée [Termes IGN] changement d'occupation du sol [Termes IGN] classification floue [Termes IGN] classification non dirigée [Termes IGN] déboisement [Termes IGN] détection de changement [Termes IGN] image multitemporelle [Termes IGN] image radar moirée [Termes IGN] image RVB [Termes IGN] image Sentinel-SAR [Termes IGN] Normalized Difference Vegetation Index [Termes IGN] segmentation d'image [Termes IGN] seuillage d'image [Termes IGN] texture d'image Résumé : (auteur) Change detection is one of the most addressed topics in the remote sensing community. When performed on synthetic aperture radar images, the most critical issues are as follows: 1) the labeling of the identified changing patterns and 2) the scarce robustness of classic pixel-based approaches based on threshold segmentation of an appropriate change index, which tend to fail when multiple changes are present in the study area. In this work, a new methodology for unsupervised change detection in vegetation canopy is presented. It overcomes these limitations by exploiting multitemporal geographical object-based image analysis with the aim to make the intrinsic semantic of data emerge and direct the processing toward the identification of precise classes of changes through dictionary-based preclassification and fuzzy combination of class-specific information layers. The proposed methodology has been tested in ten different experiments covering agriculture and clear-cut deforestation applications. The results, validated against literature methods, highlighted the superiority of the proposed approach, which was quantitatively assessed in terms of standard classification quality parameters. On agriculture experiments, it allowed for an average increase in the detection accuracy of about 11% with respect to the best performing literature method, with an increment of the false alarm rate in the order of 0.5%. In case of deforestation, the registered detection accuracy was comparable to that achieved by the literature, while the most significant benefit was the reduction, of more than one-third, of the number of detected false deforestation patterns. Overall, the main characteristics of the proposed architecture are the robustness and the lack of any supervision, which makes it very well-suited for operational scenarios. Numéro de notice : A2021-528 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.3029841 Date de publication en ligne : 22/10/2020 En ligne : https://doi.org/10.1109/TGRS.2020.3029841 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97978 [article]

Model-based estimation of forest canopy height and biomass in the Canadian boreal forest using radar, LiDAR, and optical remote sensing / Michael L. Benson in IEEE Transactions on geoscience and remote sensing, vol 59 n° 6 (June 2021)  

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Canopy openness and exclusion of wild ungulates act synergistically to improve oak natural regeneration / Julien Barrere in Forest ecology and management, Vol 487 ([01/05/2021])  

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Tree extraction and estimation of walnut structure parameters using airborne LiDAR data / Javier Estornell in International journal of applied Earth observation and geoinformation, vol 96 (April 2021)  

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Automated detection of individual Juniper tree location and forest cover changes using Google Earth Engine / Sudeera Wickramarathna in Annals of forest research, vol 64 n° 1 (2021)  

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Tropical forest canopy height estimation from combined polarimetric SAR and LiDAR using machine-learning / Maryam Pourshamsi in ISPRS Journal of photogrammetry and remote sensing, vol 172 (February 2021)  

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Reconnaissance spécifique et cartographie des arbres de la canopée en forêt tropicale en Guyane française par fusion de données lidar et hyperspectrales appliquées aux besoins de la gestion forestière / Anthony Laybros (2021)  

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Polarization of light reflected by grass: modeling using visible-sunlit areas / Bin Yang in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 12 (December 2020)  

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Comparative analysis of index and chemometric techniques-based assessment of leaf area index (LAI) in wheat through field spectroradiometer, Landsat-8, Sentinel-2 and Hyperion bands / Bappa Das in Geocarto international, vol 35 n° 13 ([01/10/2020])  

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Comparing features of single and multi-photon lidar in boreal forests / Xiaowei Yu in ISPRS Journal of photogrammetry and remote sensing, vol 168 (October 2020)  

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Ground-based remote sensing of forests exploiting GNSS signals / Leila Guerriero in IEEE Transactions on geoscience and remote sensing, vol 58 n° 10 (October 2020)  

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