Les dégâts de tempête en forêt peuvent être estimés à l'aide de modèles numériques de hauteur de canopée photogrammétriques

Autor: Jean-Pierre Renaud, Jonathan Lisein, Meriem Fournier, Cédric Vega, Sylvie Durrieu, Steen Magnussen, Philippe Lejeune
Přispěvatelé: Office National des Forêts (ONF), Laboratoire d’Inventaire Forestier (LIF), École nationale des sciences géographiques (ENSG), Institut National de l'Information Géographique et Forestière [IGN] (IGN)-Institut National de l'Information Géographique et Forestière [IGN] (IGN), Territoires, Environnement, Télédétection et Information Spatiale (UMR TETIS), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-AgroParisTech-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Centre National de la Recherche Scientifique (CNRS), Université de Liège - Gembloux, Natural Resources Canada (NRCan), Laboratoire d'Etudes des Ressources Forêt-Bois (LERFoB), Ecole Nationale du Génie Rural, des Eaux et des Forêts (ENGREF)-Institut National de la Recherche Agronomique (INRA), ANR (ANR-10-BIOE-08-07, ANR-11-LABX-0002-01), Institut National de l'Information Géographique et Forestière [IGN] (IGN), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-AgroParisTech-Centre National de la Recherche Scientifique (CNRS), IGN LABORATOIRE DE L'INVENTAIRE FORESTIER TOULOUSE FRA, Partenaires IRSTEA, Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), CANADIAN FOREST SERVICE SAULT SAINTE MARIE CAN, AgroParisTech-Institut National de la Recherche Agronomique (INRA)
Jazyk: angličtina
Rok vydání: 2017
Předmět:
Canopy
[SDV.SA]Life Sciences [q-bio]/Agricultural sciences
010504 meteorology & atmospheric sciences
Aerial survey
Forest management
0211 other engineering and technologies
canopée
02 engineering and technology
modèle
01 natural sciences
mesure photogrammétrique
hauteur dominante
Sampling design
Wind-throw estimates
Traitement du signal et de l'image
broadleaved forests
thunderstorm
021101 geological & geomatics engineering
0105 earth and related environmental sciences
Remote sensing
canopy
dégât dû au vent
numerical models
Forest inventory
Ecology
Signal and Image processing
Forestry
Storm
wind damage
tempête
15. Life on land
Agricultural sciences
Photogrammetry
forêt feuillue
[SDE]Environmental Sciences
Environmental science
Scale (map)
cubage
[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
Sciences agricoles
impact sur le milieu
Zdroj: Annals of Forest Science
Annals of Forest Science, Springer Nature (since 2011)/EDP Science (until 2010), 2017, 74 (4), pp.1-11. ⟨10.1007/s13595-017-0669-3⟩
Annals of Forest Science, Springer Verlag/EDP Sciences, 2017, 74 (4), pp.1-11. ⟨10.1007/s13595-017-0669-3⟩
Annals of Forest Science, Springer Verlag/EDP Sciences, 2017, pp.11. ⟨https://doi.org/10.1007/s13595-017-0669-3⟩
Annals of Forest Science 4 (74), 1-11. (2017)
ISSN: 1286-4560
1297-966X
DOI: 10.1007/s13595-017-0669-3⟩
Popis: ey message Diachronic photogrammetric canopy height models can be used to quantify at a fine scale changes in dominant height and wood volume following storms. The regular renewal of aerial surveys makes this approach appealing for monitoring forest changes. Context The increasing availability of aerial photographs and the development of dense matching algorithms open up new possibilities to assess the effects of storm events on forest canopies. Aims The objective of this research is to assess the potential of diachronic canopy height models derived from photogrammetric point clouds (PCHM) to quantify changes in dominant height and wood volume of a broadleaved forest following a major storm. Methods PCHMs derived from aerial photographs acquired before and after a storm event were calibrated using 25 field plots to estimate dominant height and volume using various modeling approaches. The calibrated models were combined with a reference damage maps to estimate both the within-stand damage variability, and the amount of volume impacted. Results Dominant height was predicted with a root mean squared error (RMSE) of 4%, and volume with RMSEs ranging from 24 to 32% according to the type of model. The volume impacted by storm was in the range of 42-76%. Overall, the maps of dominant height changes provided more details about within-stand damage variability than conventional photointerpretation do. Conclusion The study suggests a promising potential for exploiting PCHM in pursuit of a rapid localization and quantification of wind-throw damages, given an adapted sampling design to calibrate models.
Databáze: OpenAIRE
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