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Forest height estimation using a single-pass airborne L-band polarimetric and interferometric SAR system and tomographic techniques / Yue Huang in Remote sensing, Vol 13 n° 3 (February 2021)
[article]
Titre : Forest height estimation using a single-pass airborne L-band polarimetric and interferometric SAR system and tomographic techniques Type de document : Article/Communication Auteurs : Yue Huang, Auteur ; Qiaoping Zhang, Auteur ; Laurent Ferro-Famil, Auteur Année de publication : 2021 Article en page(s) : n° 487 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] Alberta (Canada)
[Termes IGN] bande L
[Termes IGN] forêt boréale
[Termes IGN] hauteur des arbres
[Termes IGN] interféromètrie par radar à antenne synthétique
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] modèle numérique de surface
[Termes IGN] modèle numérique de terrain
[Termes IGN] polarimétrie radar
[Termes IGN] surveillance forestière
[Termes IGN] tomographie radarRésumé : (auteur) This paper addresses forest height estimation for boreal forests at the test site of Edson in Alberta, Canada, using dual-baseline PolInSAR dataset measured by Intermap’s single-pass system. This particular dataset is acquired by using both ping-pong and non-ping-pong modes, which permit forming a dual-baseline TomoSAR configuration, i.e., an extreme configuration for tomographic processing. A tomographic approach, based on polarimetric Capon and MUSIC estimators, is proposed to estimate the elevation of tree top and of underlying ground, and hence forest height is estimated. The resulting forest DTM and DSM over the test site are validated against LiDAR-derived estimates, demonstrating the undeniable capability of the single-pass L-band PolInSAR system for forest monitoring. Numéro de notice : A2021-200 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.3390/rs13030487 Date de publication en ligne : 30/01/2021 En ligne : https://doi.org/10.3390/rs13030487 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97153
in Remote sensing > Vol 13 n° 3 (February 2021) . - n° 487[article]Long-term tree species population dynamics in Swiss forest reserves influenced by forest structure and climate / Amanda S. Mathys in Forest ecology and management, vol 481 (February 2021)
[article]
Titre : Long-term tree species population dynamics in Swiss forest reserves influenced by forest structure and climate Type de document : Article/Communication Auteurs : Amanda S. Mathys, Auteur ; P. Brang, Auteur ; J. Stillhard, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 118666 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] Abies alba
[Termes IGN] Acer pseudoplatanus
[Termes IGN] analyse diachronique
[Termes IGN] changement climatique
[Termes IGN] diamètre à hauteur de poitrine
[Termes IGN] dynamique de la végétation
[Termes IGN] écosystème forestier
[Termes IGN] Fagus sylvatica
[Termes IGN] Fraxinus excelsior
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] mortalité
[Termes IGN] Pinus sylvestris
[Termes IGN] Quercus (genre)
[Termes IGN] réserve forestière
[Termes IGN] structure d'un peuplement forestier
[Termes IGN] Suisse
[Vedettes matières IGN] Végétation et changement climatiqueRésumé : (auteur) Changes in tree species composition can have strong effects on ecosystem functioning and the services provided by forests. Empirical observations can provide an improved understanding of the drivers of species population dynamics, yet long-term datasets are scarce in natural forests. This study used inventory data of the Swiss forest reserve network to assess tree population dynamics over the past 60 years. Tree status, species and dbh were repeatedly measured between 1956 and 2018 in 211 permanent plots of 34 forest reserves that covered a wide environmental gradient. Differences in species richness and tree density were compared between the first and last inventory. Furthermore, we used generalized linear mixed effect models to estimate the processes of ingrowth and tree mortality of seven abundant species (Abies alba, Acer pseudoplatanus, Fagus sylvatica, Fraxinus excelsior, Picea abies, Pinus sylvestris and Quercus spp.) separately as a function of stand structural attributes and climate. We found a general decline in the density of the dominant species, with a low recruitment of light-demanding species and an increase in species richness, particularly in the colline vegetation zone. Both species-specific ingrowth and tree mortality were influenced by stand density and climate variables. Tree mortality increased with live tree density and increasing temperature. Ingrowth increased with tree density and decreased with higher temperature. Therefore, forest structural properties and climate have a strong influence on species population dynamics, and both are essential for predicting ingrowth and tree mortality in forest ecosystems. Numéro de notice : A2021-224 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1016/j.foreco.2020.118666 Date de publication en ligne : 28/10/2020 En ligne : https://doi.org/10.1016/j.foreco.2020.118666 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97199
in Forest ecology and management > vol 481 (February 2021) . - n° 118666[article]A quantitative assessment of rockfall influence on forest structure in the Swiss Alps / Christine Moos in European Journal of Forest Research, vol 140 n° 1 (February 2021)
[article]
Titre : A quantitative assessment of rockfall influence on forest structure in the Swiss Alps Type de document : Article/Communication Auteurs : Christine Moos, Auteur ; Nora Khelidj, Auteur ; Antoine Guisan, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 91 - 104 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Végétation
[Termes IGN] Alpes
[Termes IGN] croissance végétale
[Termes IGN] diamètre à hauteur de poitrine
[Termes IGN] dynamique de la végétation
[Termes IGN] éboulement
[Termes IGN] modèle de simulation
[Termes IGN] structure d'un peuplement forestier
[Termes IGN] SuisseRésumé : (auteur) Forests below rocky cliffs often play a very important role in protecting settlements against rockfall. The structure and development of these forests are expected to be substantially affected by the disturbance of the falling rocks. Knowing about this effect is important to predict the development of protection forests and consider potential effects of the falling blocks in management strategies. The goal of this study is to quantify differences in forest structure depending on rockfall activity in four different sites in the Swiss Alps. For this, we collected data on forest structure in zones of different rockfall activity and derived rockfall impact probabilities based on rockfall simulations. We assessed whether differences in forest structure and signs of rockfall disturbance could be observed between the rockfall zones. We additionally built mixed-effects models to identify the key variables explaining the forest characteristics described by diameter (DBH) and basal area (bA). The forest structure differs between the rockfall zones, however, with varying effects amongst the sites. DBH tends to decrease with increasing rockfall activity, whereas tree density appears to be little impacted by rockfall. For most sites, the number of deposited blocks and the simulated tree impact probability have a significant effect in the models along with the species, whereas for one site, hardly any effect of rockfall was found. Our results, obtained either from direct measurements or modelling, show that rockfall can locally influence the structure of forests, whereas the influence depends on the frequency and intensity of the rockfall disturbance. Impact probabilities obtained by simulations can serve as a good proxy for rockfall disturbances. Numéro de notice : A2021-256 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10342-020-01317-0 Date de publication en ligne : 18/09/2020 En ligne : https://doi.org/10.1007/s10342-020-01317-0 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97290
in European Journal of Forest Research > vol 140 n° 1 (February 2021) . - pp 91 - 104[article]A regional spatiotemporal analysis of large magnitude snow avalanches using tree rings / Erich Peitzsch in Natural Hazards and Earth System Sciences, Vol 21 n° 2 (February 2021)
[article]
Titre : A regional spatiotemporal analysis of large magnitude snow avalanches using tree rings Type de document : Article/Communication Auteurs : Erich Peitzsch, Auteur ; Jordi Hendrikx, Auteur ; Daniel Stahle, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 533 - 557 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse diachronique
[Termes IGN] avalanche
[Termes IGN] Canada
[Termes IGN] cerne
[Termes IGN] croissance des arbres
[Termes IGN] dendrochronologie
[Termes IGN] données topographiques
[Termes IGN] échantillonnage
[Termes IGN] Etats-Unis
[Termes IGN] géomorphologie locale
[Termes IGN] magnitude
[Termes IGN] montagneRésumé : (auteur) Snow avalanches affect transportation corridors and settlements worldwide. In many mountainous regions, robust records of avalanche frequency and magnitude are sparse or non-existent. However, dendrochronological methods can be used to fill this gap and infer historical avalanche patterns. In this study, we developed a tree-ring-based avalanche chronology for large magnitude avalanche events (size ≥∼D3) using dendrochronological techniques for a portion of the US northern Rocky Mountains. We used a strategic sampling design to examine avalanche activity through time and across nested spatial scales (i.e., from individual paths, four distinct subregions, and the region). We analyzed 673 samples in total from 647 suitable trees collected from 12 avalanche paths from which 2134 growth disturbances were identified over the years 1636 to 2017 CE. Using existing indexing approaches, we developed a regional avalanche activity index to discriminate avalanche events from noise in the tree-ring record. Large magnitude avalanches, common across the region, occurred in 30 individual years and exhibited a median return interval of approximately 3 years (mean = 5.21 years). The median large magnitude avalanche return interval (3–8 years) and the total number of avalanche years (12–18) varies throughout the four subregions, suggesting the important influence of local terrain and weather factors. We tested subsampling routines for regional representation, finding that sampling 8 random paths out of a total of 12 avalanche paths in the region captures up to 83 % of the regional chronology, whereas four paths capture only 43 % to 73 %. The greatest value probability of detection for any given path in our dataset is 40 %, suggesting that sampling a single path would capture no more than 40 % of the regional avalanche activity. Results emphasize the importance of sample size, scale, and spatial extent when attempting to derive a regional large magnitude avalanche event chronology from tree-ring records. Numéro de notice : A2021-169 Affiliation des auteurs : non IGN Thématique : FORET/GEOMATIQUE Nature : Article DOI : 10.5194/nhess-21-533-2021 Date de publication en ligne : 05/02/2021 En ligne : https://doi.org/10.5194/nhess-21-533-2021 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97108
in Natural Hazards and Earth System Sciences > Vol 21 n° 2 (February 2021) . - pp 533 - 557[article]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)
[article]
Titre : Tropical forest canopy height estimation from combined polarimetric SAR and LiDAR using machine-learning Type de document : Article/Communication Auteurs : Maryam Pourshamsi, Auteur ; Junshi Xia, Auteur ; Naoto Yokoya, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 79 - 94 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] apprentissage automatique
[Termes IGN] bande L
[Termes IGN] canopée
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] données lidar
[Termes IGN] données polarimétriques
[Termes IGN] forêt tropicale
[Termes IGN] Gabon
[Termes IGN] hauteur des arbres
[Termes IGN] image captée par drone
[Termes IGN] image radar moirée
[Termes IGN] Rotation Forest classification
[Termes IGN] semis de pointsRésumé : (auteur) Forest height is an important forest biophysical parameter which is used to derive important information about forest ecosystems, such as forest above ground biomass. In this paper, the potential of combining Polarimetric Synthetic Aperture Radar (PolSAR) variables with LiDAR measurements for forest height estimation is investigated. This will be conducted using different machine learning algorithms including Random Forest (RFs), Rotation Forest (RoFs), Canonical Correlation Forest (CCFs) and Support Vector Machine (SVMs). Various PolSAR parameters are required as input variables to ensure a successful height retrieval across different forest heights ranges. The algorithms are trained with 5000 LiDAR samples (less than 1% of the full scene) and different polarimetric variables. To examine the dependency of the algorithm on input training samples, three different subsets are identified which each includes different features: subset 1 is quiet diverse and includes non-vegetated region, short/sparse vegetation (0–20 m), vegetation with mid-range height (20–40 m) to tall/dense ones (40–60 m); subset 2 covers mostly the dense vegetated area with height ranges 40–60 m; and subset 3 mostly covers the non-vegetated to short/sparse vegetation (0–20 m) .The trained algorithms were used to estimate the height for the areas outside the identified subset. The results were validated with independent samples of LiDAR-derived height showing high accuracy (with the average R2 = 0.70 and RMSE = 10 m between all the algorithms and different training samples). The results confirm that it is possible to estimate forest canopy height using PolSAR parameters together with a small coverage of LiDAR height as training data. Numéro de notice : A2021-086 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.11.008 Date de publication en ligne : 19/12/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.11.008 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96846
in ISPRS Journal of photogrammetry and remote sensing > vol 172 (February 2021) . - pp 79 - 94[article]Réservation
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