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Mapping temperate forest tree species using dense Sentinel-2 time series / Jan Hemmerling in Remote sensing of environment, vol 267 (December-15 2021)  

Public [article]  inRemote sensing of environment > vol 267 (December-15 2021) . - n° 112743 Titre : Mapping temperate forest tree species using dense Sentinel-2 time series Type de document : Article/Communication Auteurs : Jan Hemmerling, Auteur ; Dirk Pflugmacher, Auteur ; Patrick Hostert, Auteur Année de publication : 2021 Article en page(s) : n° 112743 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] carte de la végétation [Termes IGN] espèce végétale [Termes IGN] Europe centrale [Termes IGN] filtrage numérique d'image [Termes IGN] forêt tempérée [Termes IGN] image Sentinel-MSI [Termes IGN] série temporelle Résumé : (auteur) Precise information on tree species composition is critical for forest management and conservation, but mapping tree species with satellite data over large areas is still a challenge. Since 2017, Sentinel-2A/B provide multi-spectral time series with global coverage at an unprecedented spatial and temporal resolution. This is a new opportunity for mapping tree species over large areas that has not yet been fully explored. Because of the high spatial and temporal resolution, Sentinel-2 time series improve the characterization of vegetation phenology and canopy structure, parameters that are intrinsically linked to tree species. The objective of this study was to test the utility of a Sentinel-2 time-series based approach for mapping tree species in a temperate forest region in Central Europe. Using stand-wise forest inventory data for single species stands we assess how well main and minor tree species can be mapped, and if the addition of environmental variables and spatial texture metrics improves the classification accuracy. Our time series approach utilizes all available Sentinel-2 observations and an ensemble of radial basis convolution filters to build cloud-free 5-day time series for each spectral band. The time series are then used as input features to classify seventeen tree species. Our results show the potential of Sentinel-2 time-series based classification, but they also show the challenges associated with mapping a diverse portfolio of tree species. Accuracy of the nine main species, with an area proportion greater than 0.5%, ranged between 98.9% and 66.8%, which is promising for a large area. Adding detailed environmental data and texture metrics to the spectral model only marginally increased the accuracy of a few minor tree species. Overall, the eight minor tree species with area proportions less than 0.5% were most strongly affected by classification errors. Although the absolute mapped area of minor species correlated well with the estimated reference area, the small class areas of minor species lead to high classification errors in relative terms. Mapping minor tree species is challenging for statistical reasons (i.e., class imbalance, small sample size and class variance). Using all available Sentinel-2 data allows building dense time series at high spatial resolution that are mandatory for improved tree species mapping. We were able to show that the spectral time series is the prime explanatory information, even when complementing our analyses with texture information and various environmental data. The results suggest that with the applied data harmonization approach precise regional tree species mapping is feasible. Numéro de notice : A2021-939 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.rse.2021.112743 Date de publication en ligne : 13/10/2021 En ligne : https://doi.org/10.1016/j.rse.2021.112743 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99748 [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]

Estimation of individual tree stem biomass in an uneven-aged structured coniferous forest using multispectral LiDAR data / Nikos Georgopoulos in Remote sensing, vol 13 n° 23 (December-1 2021)  

Public [article]  inRemote sensing > vol 13 n° 23 (December-1 2021) . - n° 4827 Titre : Estimation of individual tree stem biomass in an uneven-aged structured coniferous forest using multispectral LiDAR data Type de document : Article/Communication Auteurs : Nikos Georgopoulos, Auteur ; Ioannis Z. Gitas, Auteur ; Alexandra Stefanidou, Auteur ; Lauri Korhonen, Auteur ; Dimitris G. Stavrakoudis, Auteur Année de publication : 2021 Article en page(s) : n° 4827 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] Abies (genre) [Termes IGN] biomasse aérienne [Termes IGN] capteur multibande [Termes IGN] classification par forêts d'arbres décisionnels [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] forêt inéquienne [Termes IGN] Grèce [Termes IGN] inventaire forestier (techniques et méthodes) [Termes IGN] montagne [Termes IGN] Pinophyta [Termes IGN] régression [Termes IGN] tronc [Termes IGN] volume en bois Résumé : (auteur) Stem biomass is a fundamental component of the global carbon cycle that is essential for forest productivity estimation. Over the last few decades, Light Detection and Ranging (LiDAR) has proven to be a useful tool for accurate carbon stock and biomass estimation in various biomes. The aim of this study was to investigate the potential of multispectral LiDAR data for the reliable estimation of single-tree total and barkless stem biomass (TSB and BSB) in an uneven-aged structured forest with complex topography. Destructive and non-destructive field measurements were collected for a total of 67 dominant and co-dominant Abies borisii-regis trees located in a mountainous area in Greece. Subsequently, two allometric equations were constructed to enrich the reference data with non-destructively sampled trees. Five different regression algorithms were tested for single-tree BSB and TSB estimation using height (height percentiles and bicentiles, max and average height) and intensity (skewness, standard deviation and average intensity) LiDAR-derived metrics: Generalized Linear Models (GLMs), Gaussian Process (GP), Random Forest (RF), Support Vector Regression (SVR) and Extreme Gradient Boosting (XGBoost). The results showcased that the RF algorithm provided the best overall predictive performance in both BSB (i.e., RMSE = 175.76 kg and R2 = 0.78) and TSB (i.e., RMSE = 211.16 kg and R2 = 0.65) cases. Our work demonstrates that BSB can be estimated with moderate to high accuracy using all the tested algorithms, contrary to the TSB, where only three algorithms (RF, SVR and GP) can adequately provide accurate TSB predictions due to bark irregularities along the stems. Overall, the multispectral LiDAR data provide accurate stem biomass estimates, the general applicability of which should be further tested in different biomes and ecosystems. Numéro de notice : A2021-953 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.3390/rs13234827 Date de publication en ligne : 27/11/2021 En ligne : https://doi.org/10.3390/rs13234827 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99955 [article]

Multi-model estimation of forest canopy closure by using red edge bands based on Sentinel-2 images / Yiying Hua in Forests, vol 12 n° 12 (December 2021)  

Public [article]  inForests > vol 12 n° 12 (December 2021) . - n° 1768 Titre : Multi-model estimation of forest canopy closure by using red edge bands based on Sentinel-2 images Type de document : Article/Communication Auteurs : Yiying Hua, Auteur ; Xuesheng Zhao, Auteur Année de publication : 2021 Article en page(s) : n° 1768 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] apprentissage automatique [Termes IGN] bande infrarouge [Termes IGN] coefficient de corrélation [Termes IGN] couvert forestier [Termes IGN] détection de contours [Termes IGN] image multibande [Termes IGN] image Sentinel-MSI [Termes IGN] indice de végétation [Termes IGN] modèle numérique de surface de la canopée [Termes IGN] modèle statistique [Termes IGN] Mongolie intérieure (Chine) [Termes IGN] régression [Termes IGN] surveillance de la végétation Résumé : (auteur) In remote sensing, red edge bands are important indicators for monitoring vegetation growth. To examine the application potential of red edge bands in forest canopy closure estimation, three types of commonly used models—empirical statistical models (multiple stepwise regression (MSR)), machine learning models (back propagation neural network (BPNN)) and physical models (Li–Strahler geometric-optical (Li–Strahler GO) models)—were constructed and verified based on Sentinel-2 data, DEM data and measured data. In addition, we set up a comparative experiment without red edge bands. The relative error (ER) values of the BPNN model, MSR model, and Li–Strahler GO model with red edge bands were 16.97%, 20.76% and 24.83%, respectively. The validation accuracy measures of these models were higher than those of comparison models. For comparative experiments, the ER values of the MSR, Li–Strahler GO and BPNN models were increased by 13.07%, 4% and 1.22%, respectively. The experimental results demonstrate that red edge bands can effectively improve the accuracy of forest canopy closure estimation models to varying degrees. These findings provide a reference for modeling and estimating forest canopy closure using red edge bands based on Sentinel-2 images. Numéro de notice : A2021-125 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.3390/f12121768 Date de publication en ligne : 14/12/2021 En ligne : https://doi.org/10.3390/f12121768 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99318 [article]

Prescribed burning as a cost-effective way to address climate change and forest management in Mediterranean countries / Renata Martins Pacheco in Annals of Forest Science, vol 78 n° 4 (December 2021)  

Public [article]  inAnnals of Forest Science > vol 78 n° 4 (December 2021) . - n° 100 Titre : Prescribed burning as a cost-effective way to address climate change and forest management in Mediterranean countries Type de document : Article/Communication Auteurs : Renata Martins Pacheco, Auteur ; Joao Claro, Auteur Année de publication : 2021 Article en page(s) : n° 100 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] brûlis [Termes IGN] changement climatique [Termes IGN] droit fiscal [Termes IGN] écologie forestière [Termes IGN] émission de gaz [Termes IGN] forêt méditerranéenne [Termes IGN] gestion forestière [Termes IGN] incendie de forêt [Termes IGN] puits de carbone [Termes IGN] service écosystémique [Vedettes matières IGN] Foresterie Résumé : (auteur) Key message: As climate change and forest management become the focus of various development agendas and the price of carbon rises in the market, the need for improving carbon sequestration and avoiding wildfires emissions increases. Prescribed burning interventions might play an important role in this context, as in some situations, it has been suggested that it can reduce overall fire emissions. In this study, the potential economic benefits associated with the practice are analyzed for five Mediterranean countries. Despite the uncertainty in the estimates, the results suggest that under some circumstances these interventions can be cost-effective from a carbon management perspective. Context: Wildland fires are becoming a major concern for many European countries and are expected to become more prevalent due to climate change, affecting societies, ecosystems, and various ecosystem services provided by forests that are not valued by traditional markets, such as carbon sequestration. Aims: The objective of this study is to evaluate the possibility of using carbon taxation to fund fire management measures in Mediterranean countries. Methods: The analysis is done by converting prescribed burning savings in carbon emissions into their economic value. This is performed for France, Greece, Italy, Spain, and Portugal, which is studied in more detail, since the country has a National Prescribed Burning Program (NPBP) and a specific tax on carbon in place. Results: The results indicate that most countries could potentially have benefits in the order of millions of euros from employing prescribed burning measures. In Portugal, NPBP has the potential to be a relevant policy instrument to reduce wildfire emissions, as well as economically since the carbon emissions savings can outweigh the prescribed burning costs in some circumstances. Also, the revenue from the country’s Addition Tax on Carbon Emissions would be able to accommodate the foreseen prescribed burning costs. Conclusion: There are still many uncertainties regarding the benefits of prescribed burning in terms of overall emission reductions, and more studies should be conducted on this topic. However, as the price of carbon rises in the markets and climate change becomes a more pressing concern, even small emissions reductions might be economically interesting. The analysis framework used in this study has the potential to be useful for other countries, especially in Mediterranean-type ecosystems. Numéro de notice : A2021-120 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-021-01115-7 Date de publication en ligne : 13/12/2021 En ligne : https://doi.org/10.1007/s13595-021-01115-7 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99297 [article]

Radiative transfer modeling in structurally complex stands: towards a better understanding of parametrization / Frédéric André in Annals of Forest Science, vol 78 n° 4 (December 2021)  

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Forest type matters: Global review about the structure of oak dominated old-growth temperate forests / Janos Bölöni in Forest ecology and management, vol 500 (November-15 2021)  

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An empirical model for forest landscape planning and its financial consequences for landowners / Goran Bostedt in Scandinavian journal of forest research, vol 36 n° 7-8 ([01/11/2021])  

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Quels besoins de connaissances pour le futur des forêts en France ? Au-delà du plan de relance / Maya Leroy in Revue forestière française, vol 73 n° 1 (2021)    

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Thinning effect of C sequestration along an elevation gradient of mediterranean pinus spp. plantations / Antonio M. Cachinero-Vivar in Forests, vol 12 n° 11 (November 2021)  

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Using LiDAR and Random Forest to improve deer habitat models in a managed forest landscape / Colin S. Shanley in Forest ecology and management, vol 499 (November-1 2021)  

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Variation in plant–soil interactions among temperate forest herbs / Jared J. Beck in Plant ecology, vol 222 n° 11 (November 2021)  

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Impact of beam diameter and scanning approach on point cloud quality of terrestrial laser scanning in forests / Meinrad Abegg in IEEE Transactions on geoscience and remote sensing, vol 59 n° 10 (October 2021)  

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Spectral reflectance estimation of UAS multispectral imagery using satellite cross-calibration method / Saket Gowravaram in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 10 (October 2021)  

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Variation in downed deadwood density, biomass, and moisture during decomposition in a natural temperate forest / Tomas Přívětivý in Forests, vol 12 n° 10 (October 2021)  

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