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iForest - Biogeosciences and Forestry

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Remote sensing of american maple in alluvial forests: a case study in an island complex of the Loire valley (France)

Hilaire Martin (1)   , Jean-Matthieu Monnet (2), Marie De Boisvilliers (3), Richard Chevalier (1), Marc Villar (4)

iForest - Biogeosciences and Forestry, Volume 13, Issue 5, Pages 409-416 (2020)
doi: https://doi.org/10.3832/ifor3237-013
Published: Sep 16, 2020 - Copyright © 2020 SISEF

Technical Reports


Due to their particular topographic position between land and river, riparian forests are ecosystems rich in biodiversity. In France, along the Middle Loire (from Nevers to Angers), Black poplar (Populus nigra L.) forests are often in mixtures with the American maple (Acer negundo L.), introduced into the country in the 18th century. We tested the detectability of American maple by LiDAR and very high-resolution multispectral imagery on an island complex. We found that coupling the point cloud height standard deviation with a vegetation index in the red, green and blue spectrums discriminated American maple with a success rate of more than 90%.

  Keywords


Acer negundo, American Maple, Box Elder, Populus nigra, Black Poplar, Airborne Laser Scanning, Remote Sensing, Exogenous Woody Species, Loire River

Authors’ address

(1)
Hilaire Martin
Richard Chevalier
INRAE Val de Loire, Site de Nogent-sur-Vernisson, Domaine des Barres 45290 Nogent-sur-Vernisson (France)
(2)
Jean-Matthieu Monnet 0000-0002-9948-9891
Univ. Grenoble Alpes, INRAE, UR LESSEM, F-38402 St-Martin-d’Hères (France)
(3)
Marie De Boisvilliers
L’AVION JAUNE, 1 chemin du Fescau, 34980 Montferrier-sur-Lez (France)
(4)
Marc Villar 0000-0001-9210-7072
INRAE Val de Loire, UMR 0588 INRA-ONF BioForA, 2163 Av. de la Pomme de Pin, CS 40001 Ardon, 45075 Orléans Cedex 2 (France)

Corresponding author

 
Hilaire Martin
hilaire.martin@inrae.fr

Citation

Martin H, Monnet J-M, De Boisvilliers M, Chevalier R, Villar M (2020). Remote sensing of american maple in alluvial forests: a case study in an island complex of the Loire valley (France). iForest 13: 409-416. - doi: 10.3832/ifor3237-013

Academic Editor

Matteo Garbarino

Paper history

Received: Sep 13, 2019
Accepted: Jul 08, 2020

First online: Sep 16, 2020
Publication Date: Oct 31, 2020
Publication Time: 2.33 months

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(1)
Asner GP, Knapp DE, Kennedy-Bowdoin T, Jones MO, Martin RE, Boardman J, Hughes RF (2008)
Remote sensing of native and invasive species in Hawaiian forests. Remote Sensing of Environment 112: 1942-1945.
CrossRef | Gscholar
(2)
Balenović I, Alberti G, Marjanović H (2013)
Airborne laser scanning - the status and perspectives for the application in the South-East European forestry. South-East European Forestry 4 (2): 59-79.
CrossRef | Gscholar
(3)
Berg C, Drescher A, Essl F (2017)
Using relevé-based metrics to explain invasion patterns of alien trees in temperate forests. Tuexenia 37: 127-142.
Online | Gscholar
(4)
Beslin O, Gazeau J-C (2016)
Système d’Information des Évolutions du Lit de la Loire et de ses affluents. Typologie des habitats du SIEL 2. Guide de terrain et de lecture pour la cartographie [Information System of the Evolutions of the Loire riverbed and its tributaries. SIEL Habitat Typology 2. Field and Reading Guide for Mapping]. Conservatoire National du Bassin Parisien, délégation Centre-Val de Loire, Orléans, France, pp. 1-27. [in French]
Gscholar
(5)
Campbell L, Coops N, Saunders S (2017)
LiDAR as an advanced remote sensing technology to augment ecosystem classification and mapping. Journal of Ecosystems and Management 17 (1): 1-13.
Online | Gscholar
(6)
Dalponte M, Bruzzone L, Gianelle D (2012)
Tree species classification in the Southern Alps based on the fusion of very high geometrical resolution multispectral/hyperspectral images and LiDAR data. Remote Sensing of Environment 123: 258-270.
CrossRef | Gscholar
(7)
Dalponte M, Coomes DA (2016)
Tree-centric mapping of forest carbon density from airborne laser scanning and hyperspectral data. Methods in Ecology and Evolution 7: 1236-1245.
CrossRef | Gscholar
(8)
Demarchi L, Kania A, Ciezkowski W, Piórkowski H, Oswiecimska-Piasko Z, Chormanski J (2020)
Recursive feature elimination and random forest classification of Natura 2000 grasslands in lowland river valleys of Poland based on airborne hyperspectral and LiDAR data fusion. Remote Sensing 12: 1-33.
CrossRef | Gscholar
(9)
Dufour S, Bernez I, Betbeder J, Corgne S, Hubert-Moy L, Nabucet J, Rapinel S, Sawtschuk J, Trollé C (2013)
Monitoring restored riparian vegetation: how can recent developments in remote sensing sciences help? Knowledge and Management of Aquatic Ecosystems 410 (10): 1-15.
CrossRef | Gscholar
(10)
Dumas Y (2019)
Que savons-nous de l’Erable négondo (Acer negundo L., 1753)? [What do we know about American maple (Acer negundo L., 1753)?]. Naturae (10): 257-283.
Gscholar
(11)
Dunford R, Michel K, Gagnage M, Piégay H, Trémelo M-L (2009)
Potential and constraints of unmanned aerial vehicle technology for the characterization of Mediterranean riparian forest. International Journal of Remote Sensing 30 (19): 4915-4935.
CrossRef | Gscholar
(12)
Grivel S, Gautier E (2012)
Mise en place des îles fluviales en Loire moyenne, du 19e siècle à aujourd’hui [Establishment of fluvial islands in the middle Loire, from the 19th century to today]. Cybergeo, European Journal of Geography, Document no. 615. [in French]
CrossRef | Gscholar
(13)
Gurnell A (2014)
Plants as river system engineers. Earth Surface Processes and Landforms 39 (1): 4-25.
CrossRef | Gscholar
(14)
Heinzel J, Koch B (2012)
Investigating multiple data sources for tree species classification in temperate forest and use for single tree delineation. International Journal of Applied Earth Observation and Geoinformation 18: 101-110.
CrossRef | Gscholar
(15)
Hervé J-C, Wurpillot S, Vidal C, Roman-Amat B (2014)
L’inventaire des ressources forestières en France: un nouveau regard sur de nouvelles forêts [Inventory of forest resources in France: a new look at new forests]. Revue Forestière Française 66 (3): 247-260. [in French]
CrossRef | Gscholar
(16)
Hothorn T, Hornik K, Zeileis A (2006)
Unbiased recursive partitioning: a conditional inference framework. Journal of Computational and Graphical Statistics 15 (3): 651-674.
CrossRef | Gscholar
(17)
Huylenbroeck L, Laslier M, Dufour S, Georges B, Lejeune P, Adrien M (2020)
Using remote sensing to characterize riparian vegetation: a review of available tools and perspectives for managers. Journal of Environmental Management 267: 1-19.
CrossRef | Gscholar
(18)
Jaafar WSWM, Woodhouse IH, Silva CA, Omar H, Abdul Maulud KN, Hudak AT, Klauberg C, Cardil A, Mohan M (2018)
Improving individual tree crown delineation and attributes estimation of tropical forests using airborne LiDAR data. Forests 9 (12): 1-23.
CrossRef | Gscholar
(19)
Laslier M, Hubert-Moy L, Dufour S (2019)
Mapping riparian vegetation functions using 3D bispectral LiDAR data. Water 11 (3): 483.
CrossRef | Gscholar
(20)
Lindberg E, Holmgren J (2017)
Individual tree crown methods for 3D data from remote sensing. Current Forestry Report 3: 19-31.
CrossRef | Gscholar
(21)
Li W, Guo Q, Jakubowski MK, Kelly M (2012)
A new method for segmenting individual trees from the lidar point cloud. Photogrammetric Engineering and Remote Sensing 78: 75-84.
CrossRef | Gscholar
(22)
Manfreda S, McCabe MF, Miller PE, Lucas R, Pajuelo Madrigal V, Mallinis G, Ben Dor E, Helman D, Estes L, Ciraolo G, Müllerová J, Tauro F, De Lima MI, De Lima JLMP, Maltese A, Frances F, Caylor K, Kohv M, Perks M, Ruiz-Pérez G, Su Z, Vico G, Toth B (2018)
On the use of unmanned aerial systems for environmental monitoring. Remote Sensing 10: 1-33.
CrossRef | Gscholar
(23)
Mei C, Durrieu S (2004)
Tree crown delineation from digital elevation models and high resolution imagery. In: Proceedings of the ISPRS Working Group part 8/2. Freiburg (Germany) 3-6 Oct 2004. The International Archives of the Photogrammetry, Remote Sensing, vol. 36, pp. 6.
Online | Gscholar
(24)
Michez A, Piégay H, Lisien J, Claessens H, Lejeune P (2016)
Classification on riparian forest species and health condition using muti-temporal and hyperspatial imagery from unmanned aerial system. Environmental Monitoring and Assessment 188 (146): 1-19.
Gscholar
(25)
Monnet J-M, Mermin E, Chanussot J, Berger F (2010)
Tree top detection using local maxima filtering: a parameter sensitivity analysis. In: Proceedings of “Silvilaser 2010 - 10th International Conference on LIDAR Applications for Assessing Forest Ecosystems”. Freiburg (Germany) 14 Sep 2010, pp. 9.
Online | Gscholar
(26)
Monnet J-M (2011)
Caractérisation des forêts de montagne par scanner laser aéroporté: estimation de paramètres de peuplement par régression SVM et apprentissage non supervisé pour la détection de sommets [Using airborne laser scanning for mountain forests mapping: Support vector regression for stands parameters estimation and unsupervised training for treetop detection]. PhD thesis, Grenoble Images Parole Signal Automatique Department, Université de Grenoble Alpes, France, pp. 187.
Online | Gscholar
(27)
Monnet J-M (2018)
lidaRtRee, forest analysis with airborne laser scanning (Lidar) data. Web site.
Online | Gscholar
(28)
Naiman RB, Décamps H, McClain ME (2005)
Riparia: ecology, conservation, and management of streamside communities. Elsevier Academic Press, London, UK, pp. 418.
Gscholar
(29)
Pirotti F, Kobal M, Roussel J-R (2017)
A comparison of tree segmentation methods using very high density airborne laser scanner data. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W7: 285-290.
CrossRef | Gscholar
(30)
R Development Core Team (2017)
R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna.
Online | Gscholar
(31)
Rodrigues S, Bréhéret J-G, Macaire J-J, Greulich S, Villar M (2006)
In-channel woody vegetation controls on sedimentary processes and the sedimentary record within alluvial environments: a modern example of an anabranch of the River Loire, France. Sedimentology 54 (1): 223-242.
CrossRef | Gscholar
(32)
Rouse J, Haas RH, Schell JA, Deering DW (1973)
Monitoring vegetation systems in the great plains with ERTS. In: Proceeding of the “3rd ERTS Symposium”. Washington (DC, USA) 10-14 Dec 1973. NASA SP-351 1, US Government Printing Office, Washington, DC, USA, pp. 309-317.
Gscholar
(33)
Straigyte L, Cekstere G, Laivins M, Marozas V (2015)
The spread, intensity and invasiveness of the Acer negundo in Riga and Kaunas. Dendrobiology 74: 157-168.
CrossRef | Gscholar
(34)
Wehr A, Lohr U (1999)
Airborne laser scanning an introduction and overview. ISPRS Journal of Photogrammetry and Remote Sensing 54: 68-82.
CrossRef | Gscholar
(35)
Zhen Z, Quackenbush L, Zhang L (2016)
Trends in automatic individual tree crown detection and delineation evolution of LiDAR data. Remote Sensing 8 (4): 333.
CrossRef | Gscholar
 

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