Centre dedocumentation
scientifique

Amazon forest spectral seasonality is consistent across sensor resolutions and driven by leaf demography / Nathan B. Gonçalves in ISPRS Journal of photogrammetry and remote sensing, vol 196 (February 2023)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 196 (February 2023) . - pp 93 - 104 Titre : Amazon forest spectral seasonality is consistent across sensor resolutions and driven by leaf demography Type de document : Article/Communication Auteurs : Nathan B. Gonçalves, Auteur ; Ricardo Dalagnol, Auteur ; Jin Wu, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : pp 93 - 104 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] Amazonie [Termes IGN] distribution du coefficient de réflexion bidirectionnelle BRDF [Termes IGN] forêt tropicale [Termes IGN] image Landsat-8 [Termes IGN] image Landsat-OLI [Termes IGN] image proche infrarouge [Termes IGN] image Terra-MODIS [Termes IGN] indice de végétation [Termes IGN] Leaf Area Index [Termes IGN] réflectance spectrale [Termes IGN] sécheresse [Termes IGN] variation saisonnière Résumé : (Auteur) Controversy surrounds the reported dry season greening of the Central Amazon forests based on the Enhanced Vegetation Index (EVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS). As the solar zenith angle decreases during the dry season, it affects the sub-pixel shade content and artificially increases Near-infrared (NIR) reflectance and EVI. MODIS' coarse resolution also creates a challenge for cloud and terrain filtering. To reduce these artifacts and then validate MODIS seasonal spectral patterns we use 16 years of 1 km resolution MODIS-MAIAC (Multi-Angle Implementation of Atmospheric Correction) images, corrected to a nadir view and 45° solar zenith angle, together with an improved cloud filter. Then we show that the 30 m Landsat-8 Operational Land Imager (OLI) surface reflectance over two Landsat scenes provides independent evidence supporting the MODIS-MAIAC seasonality for EVI, NIR, and GCC (an additional important vegetation index, green chromatic coordinate). Our empirical method for controlling for sun-sensor geometry effects in Landsat scenes encompasses the use of seasonally distinct images that have similar solar zenith angles and cloud-free pixels on flat uplands having the same phase angle. We extended this validation to nine Amazon sub-basins comprising ∼546 Landsat-8 images. Our study shows that the dry-season green-up pattern observed by MODIS is corroborated by Landsat-8, and is independent of satellite data artifacts. To investigate the mechanisms driving these seasonal changes we further used Central Amazon tower-mounted RGB cameras providing a 4-year record at the Amazon Tall Tower (ATTO, 2°8′36″S, 59°0′2″W) and a 7-year record at the Manaus k34 tower (2°36′33″ S, 60°12′33″W) to obtain monthly upper canopy green leaf cover (a proxy for Leaf Area Index - LAI) and monthly leaf age class abundances (based on the age since leaf flushing, by crown). These were compared to seasonal patterns of GCC and EVI in small MODIS-MAIAC windows centered on each tower. MODIS-MAIAC GCC was positively correlated with newly flushed leaves (R2 = 0.76 and 0.44 at ATTO and k34, respectively). EVI correlated strongly with the abundance of mature leaves (R2 = 0.82 and 0.80) but was poorly correlated with LAI (R2 = 0.20 and 0.41, respectively). Therefore, seasonal spectral patterns in the Central Amazon are likely controlled by leaf age variation, not quantity of leaf area. Numéro de notice : A2023-065 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2022.12.001 Date de publication en ligne : 04/01/2023 En ligne : https://doi.org/10.1016/j.isprsjprs.2022.12.001 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102423 [article]

Evaluation of growth models for mixed forests used in Swedish and Finnish decision support systems / Jorge Aldea in Forest ecology and management, vol 529 (February-1 2023)  

Public [article]  inForest ecology and management > vol 529 (February-1 2023) . - n° 120721 Titre : Evaluation of growth models for mixed forests used in Swedish and Finnish decision support systems Type de document : Article/Communication Auteurs : Jorge Aldea, Auteur ; Simone Bianchi, Auteur ; Urban Nilsson, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 120721 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] Betula (genre) [Termes IGN] Finlande [Termes IGN] forêt boréale [Termes IGN] inventaire forestier étranger (données) [Termes IGN] modèle de croissance végétale [Termes IGN] modèle de simulation [Termes IGN] peuplement mélangé [Termes IGN] Picea abies [Termes IGN] Pinus sylvestris [Termes IGN] Suède [Termes IGN] système d'aide à la décision [Vedettes matières IGN] Inventaire forestier Résumé : (auteur) Interest in mixed forests is increasing since they could provide higher benefits and positive externalities compared to monocultures, although their management is more complex and silvicultural prescriptions for them are still scarce. Growth simulations are a powerful tool for developing useful guidelines for mixed stands. Heureka and Motti are two decision support systems commonly used for forest management in Sweden and Finland respectively. They were developed mostly with data from pure stands, so how they would perform in mixed stands is currently uncertain. We compiled a large and updated common database of well-replicated experimental research sites and monitoring networks composed by 218 and 1,160 plot-level observations of mixed stands from Sweden and Finland, respectively. We aimed to evaluated the accuracy of Heureka and Motti basal area growth models in those mixed-species stands and to detect any bias in their short-term predictions. Basal area growth simulations (excluding mortality models) were compared to observed stand-level values in a period-wise process with update of the start values in each period. The residual plots were visually examined for different stand mixtures: Norway spruce (Picea abies Karst.)-birch (Betula spp), Scots pine (Pinus sylvestris L.)-birch and Scots pine-Norway spruce. We observed that the basal area growth models in both decision support systems performed quite well for all mixtures regardless of the proportion of species. Motti simulations overestimated growth in Scots pine-Norway spruce mixtures by 0.063 m2·ha−1·year−1 which may be acceptable for practical use. Therefore, we corroborated that both decision support systems can be currently utilized for short-term forest growth simulation of mixed boreal forests. Numéro de notice : A2023-107 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1016/j.foreco.2022.120721 Date de publication en ligne : 28/12/2022 En ligne : https://doi.org/10.1016/j.foreco.2022.120721 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102441 [article]

Stochastic multicriteria acceptability analysis as a forest management priority mapping approach based on airborne laser scanning and field inventory data / Parvez Rana in Landscape and Urban Planning, vol 230 (February 2023)  

Public [article]  inLandscape and Urban Planning > vol 230 (February 2023) . - n° 104637 Titre : Stochastic multicriteria acceptability analysis as a forest management priority mapping approach based on airborne laser scanning and field inventory data Type de document : Article/Communication Auteurs : Parvez Rana, Auteur ; Jari Vauhkonen, Auteur Année de publication : 2023 Article en page(s) : n° 104637 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] aide à la décision [Termes IGN] analyse multicritère [Termes IGN] classification barycentrique [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] Finlande [Termes IGN] forêt boréale [Termes IGN] gestion forestière [Termes IGN] inventaire forestier étranger (données) [Termes IGN] Picea abies [Termes IGN] Pinus sylvestris [Termes IGN] processus stochastique [Termes IGN] semis de points [Termes IGN] service écosystémique [Termes IGN] structure d'un peuplement forestier Résumé : (auteur) The mapping of ecosystem service (ES) provisioning often lacks decision-makers’ preferences on the ESs provided. Analyzing the related uncertainties can be computationally demanding for a landscape tessellated to a large number of spatial units such as pixels. We propose stochastic multicriteria acceptability analyses to incorporate (unknown or only partially known) decision-makers’ preferences into the spatial forest management prioritization in a Scandinavian boreal forest landscape. The potential of the landscape for the management alternatives was quantified by airborne laser scanning based proxies. A nearest-neighbor imputation method was applied to provide each pixel with stochastic acceptabilities on the alternatives based on decision-makers’ preferences sampled from a probability distribution. We showed that this workflow could be used to derive two types of maps for forest use prioritization: one showing the alternative that a decision-maker with given preferences should choose and another showing areas where the suitability of the forest structure suggested different alternative than the preferences. We discuss the potential of the latter approach for mapping management hotspots. The stochastic approach allows estimating the strength of the decision with respect to the uncertainty in both the proxy values and preferences. The nearest neighbor imputation of stochastic acceptabilities is a computationally feasible way to improve decisions based on ES proxy maps by accounting for uncertainties, although the need for such detailed information at the pixel level should be separately assessed. Numéro de notice : A2023-024 Affiliation des auteurs : non IGN Thématique : FORET/GEOMATIQUE Nature : Article DOI : 10.1016/j.landurbplan.2022.104637 Date de publication en ligne : 16/11/2022 En ligne : https://doi.org/10.1016/j.landurbplan.2022.104637 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102247 [article]

Testing the application of process-based forest growth model PREBAS to uneven-aged forests in Finland / Man Hu in Forest ecology and management, vol 529 (February-1 2023)  

Public [article]  inForest ecology and management > vol 529 (February-1 2023) . - n° 120702 Titre : Testing the application of process-based forest growth model PREBAS to uneven-aged forests in Finland Type de document : Article/Communication Auteurs : Man Hu, Auteur ; Francesco Minunno, Auteur ; Mikko Peltoniemi, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 120702 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] biomasse forestière [Termes IGN] croissance des arbres [Termes IGN] diamètre à hauteur de poitrine [Termes IGN] Finlande [Termes IGN] forêt boréale [Termes IGN] forêt inéquienne [Termes IGN] hauteur des arbres [Termes IGN] modèle de croissance végétale [Termes IGN] modèle de simulation [Termes IGN] modélisation de la forêt [Termes IGN] mortalité [Termes IGN] peuplement mélangé [Termes IGN] photosynthèse [Termes IGN] Picea abies [Termes IGN] structure d'un peuplement forestier [Vedettes matières IGN] Foresterie Résumé : (auteur) The challenges of applying process-based models to uneven-aged forests are the difficulties in simulating the interactions between trees and resource allocation between size classes. In this study, we focused on a process-based forest growth model PREBAS which is a mean tree model with Reineke self-thinning mortality and was originally developed for even-aged forests. The primary aim was to test the application of PREBAS model to uneven-aged forests by introducing different diameter at breast height (DBH) size classes to better represent the forest structure. Additionally, we introduced a new mortality model to PREBAS which is developed for uneven-aged stands and compared with the current PREBAS version in which a modification Reineke rule is used. The tests were conducted in 26 old Norway spruce dominated stands in southern and central Finland with three consecutive measurements (on average a 25-year study period). To evaluate the model performance, we compared the estimations of stand averaged diameter at breast height (D), stand averaged tree height (H), stand averaged crown base height (), stand basal area (B) and density (N) with measurements. Moreover, biomass estimations of each tree component (foliage, branch and stem) were compared to estimations from empirical models. Results showed that introducing size distributions can represent better stand structure and improve the model predictions compared with data. Moreover, the new mortality model showed promise with qualitatively more realistic results especially among the largest tree size classes. However, model bias still existed in the simulation although the predictions were improved. It revealed that further calibration of the PREBAS model with size classes should be done to better extend the model applicability to uneven-aged forests. Numéro de notice : A2023-022 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1016/j.foreco.2022.120702 Date de publication en ligne : 05/12/2022 En ligne : https://doi.org/10.1016/j.foreco.2022.120702 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102228 [article]

Detection of growth change of young forest based on UAV RGB images at single-tree level / Xiaocheng Zhou in Forests, vol 14 n° 1 (January 2023)  

Public [article]  inForests > vol 14 n° 1 (January 2023) . - n° 141 Titre : Detection of growth change of young forest based on UAV RGB images at single-tree level Type de document : Article/Communication Auteurs : Xiaocheng Zhou, Auteur ; Hongyu Wang, Auteur ; Chongcheng Chen, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 141 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] Abies (genre) [Termes IGN] âge du peuplement forestier [Termes IGN] Chine [Termes IGN] croissance des arbres [Termes IGN] détection de changement [Termes IGN] hauteur des arbres [Termes IGN] image captée par drone [Termes IGN] image RVB [Termes IGN] jeune arbre [Termes IGN] modèle numérique de surface de la canopée [Termes IGN] surveillance forestière Résumé : (auteur) With the rapid development of Unmanned Aerial Vehicle (UAV) technology, more and more UAVs have been used in forest survey. UAV (RGB) images are the most widely used UAV data source in forest resource management. However, there is some uncertainty as to the reliability of these data when monitoring height and growth changes of low-growing saplings in an afforestation plot via UAV RGB images. This study focuses on an artificial Chinese fir (Cunninghamia lancelota, named as Chinese Fir) young forest plot in Fujian, China. Divide-and-conquer (DAC) and the local maximum (LM) method for extracting seedling height are described in the paper, and the possibility of monitoring young forest growth based on low-cost UAV remote sensing images was explored. Two key algorithms were adopted and compared to extract the tree height and how it affects the young forest at single-tree level from multi-temporal UAV RGB images from 2019 to 2021. Compared to field survey data, the R2 of single saplings’ height extracted from digital orthophoto map (DOM) images of tree pits and original DSM information using a divide-and-conquer method reached 0.8577 in 2020 and 0.9968 in 2021, respectively. The RMSE reached 0.2141 in 2020 and 0.1609 in 2021. The R2 of tree height extracted from the canopy height model (CHM) via the LM method was 0.9462. The RMSE was 0.3354 in 2021. The results demonstrated that the survival rates of the young forest in the second year and the third year were 99.9% and 85.6%, respectively. This study shows that UAV RGB images can obtain the height of low sapling trees through a computer algorithm based on using 3D point cloud data derived from high-precision UAV images and can monitor the growth of individual trees combined with multi-stage UAV RGB images after afforestation. This research provides a fully automated method for evaluating the afforestation results provided by UAV RGB images. In the future, the universality of the method should be evaluated in more afforestation plots featuring different tree species and terrain. Numéro de notice : A2023-115 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.3390/f14010141 Date de publication en ligne : 10/01/2023 En ligne : https://doi.org/10.3390/f14010141 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102482 [article]

Mitigating the risk of wind damage at the forest landscape level by using stand neighbourhood and terrain elevation information in forest planning / Roope Ruotsalainen in Forestry, an international journal of forest research, vol 96 n° 1 (January 2023)  

Permalink

Prescribed fire after thinning increased resistance of sub-Mediterranean pine forests to drought events and wildfires / Lena Vilà-Vilardell in Forest ecology and management, vol 527 (January-1 2023)  

Permalink

Taller and slenderer trees in Swedish forests according to data from the National Forest Inventory / Alex Appiah Mensah in Forest ecology and management, vol 527 (January-1 2023)  

Permalink

Climate and ungulate browsing impair regeneration dynamics in spruce-fir-beech forests in the French Alps / Mithila Unkule in Annals of Forest Science, vol 79 n° 1 (2022)  

Permalink

Forêt amazonienne : de nouveau sous contrôle ? / Laurent Polidori in Géomètre, n° 2208 (décembre 2022)

Permalink

Identification and spatial extent of understory plant species requiring vegetation control to ensure tree regeneration in French forests / Noé Dumas in Annals of Forest Science, vol 79 n° 1 (2022)  

Permalink

The contribution of understorey vegetation to ecosystem evapotranspiration in boreal and temperate forests: a literature review and analysis / Philippe Balandier in European Journal of Forest Research, vol 141 n° 6 (December 2022)  

Permalink

The role of wood harvest from sustainably managed forests in the carbon cycle / Ernst Detlef Schulze in Annals of Forest Science, vol 79 n° 1 (2022)  

Permalink

Accompagner le rétablissement spontané de la forêt après un incendie / Jacques Hazera in Géomètre, n° 2207 (novembre 2022)

Permalink

Evaluation of softwood timber quality: A case study on two silvicultural systems in Central Germany / Kristen Höwler in Forests, vol 13 n° 11 (November 2022)  

Permalink