The assessment of forest parameters by combined LiDAR and satellite data over Alpine regions – EUFODOS Implementation in Austria / Hodnotenie parametrov lesa kombináciou LIDAR-u a satelitných údajov v alpských regiónoch – implementácia systému EUFODOS v Rakúsku

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Abstract

Regional authorities require detailed and georeferenced information on the status of forests to ensure a sustainable forest management. One of the objectives in the FP7 project EUFODOS was the development of an operational service based on airborne laser scanning and satellite data in order to derive forest parameters relevant for the management of protective forests in the Alps. The estimated parameters are forest type, stem number, height of upper layer, mean height and timber volume. RapidEye imagery was used to derive coniferous and broadleaf forest classes using a logistic regression-based method. After the generation of a normalised Digital Surface Model and a forest mask, the forest area was segmented into homogeneous polygons, tree tops were detected, and various forest parameters are calculated. The accuracy of such an assessment was comparable with some previous studies, and the R-square between the estimated and measured values was 0.69 for tree top detection, 0.82 for upper height and 0.84 for mean height. For the calculation of timber volume, the R² for modelling is 0.82, for validation with an independent set of field plots, the R² is 0.71. The results have been successfully integrated into the regional forestry GIS and are used in forest management.

Abstrakt

Regionálne plánovanie zabezpečujúce trvale udržateľný manažment lesa vyžaduje detailné a georeferencované informácie o stave lesov. Jedným z cieľov projektu EUFODOS (projekt 7. RP EÚ) bolo vyvinúť operatívnu službu využívajúcu údaje leteckého laserového skenovania v kombinácii so satelitnými údajmi, pomocou ktorých sú odvodené informácie potrebné pre obhospodarovanie ochranných lesov v Alpách. Zisťované parametre sú lesný typ, počet stromov, výška hornej korunovej vrstvy, priemerná výška a kmeňová zásoba. Použilo sa snímkovanie systémom RapidEye pre odvodenie tried ihličnanov a listnáčov s použitím logistického regresného modelu. Po vygenerovaní normalizovaného digitálneho modelu povrchu a masky lesa sa plocha lesa segmentovala do homogénnych polygónov, identifikovali sa vrcholce stromov a vypočítali sa požadované porastové charakteristiky. Presnosť uvedených odhadov bola porovnateľná s predošlými štúdiami - R2 medzi odhadovanými a meranými hodnotami pozícií vrcholcov stromov bol 0,69, pre hornú výšku 0,82 a pre priemernú výšku porastu 0,84. Pri výpočte objemu dreva bol R2 príslušného modelu 0,82. Pri validácii s nezávislým súborom plôch bola dosiahnutá hodnota R2 0,71. Prezentované výsledky sa úspešne integrovali do regionálnych lesníckych GIS sú využívané pri manažmente lesa.

References

  • BFW, Bundesforschungs- und Ausbildungszentrum für Wald, Naturgefahren und Landschaft, 2009: Die österreichische Forstinventur 2007-2009,, Seckendorff- Gudent-Weg 8, Wien, Available at: .

  • Chen, Q., Baldocchi, D., Gong, P., Kelly, M., 2006: Isolating individual trees in a savanna woodland using small footprint lidar data - Photogrammetric Engineering and Remote Sensing 72: 923-932.

  • Clementel, F., Colle, G., Farrugia, C., Floris, A., Scrinzi, G., Torresan, Ch., 2011: Estimating forest timber volume by means of “low-cost” LiDAR data - Italian Journal of Rem. Sens., 44:125-140. Available at: .

  • European Communities, 2011: EUFODOS European Forest Downstream Services - Improved Information on Forest Structure and Damages. GMES Downstream Services. Available at: .

  • Gallaun, H., Schardt, M., Linser, S., 2007: Remote Sensing based Forest Map of Austria and derived Environmental Indicators. In: Proceedings of the International Conference on Spatial Application Tools in Forestry (ForestSAT 2007). Montpellier, France.

  • Gonzalez, R.C., Woods, R. E., 2002: Digital Image Processing. Prentice Hall, Inc., Upper Saddle River, New Jersey, second edition, 793 p.

  • Hirschmugl, M., 2008: Derivation of Forest Parameters from UltracamD Data. Dissertation. Technische Universität Graz, Austria, 200 p.

  • Hirschmugl, M., Gallaun, H., Wack, R., Granica, K., Schardt, M., 2013: EUFODOS: European Forest Downstream Services - Improved Information on Forest Structure and Damage - Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-1/W1: 127-131.

  • Hollaus, M., Dorigo, W., Wagner, W., Schadauer, K., Hoefle, B., Maier, B., 2009: Operational wide-area stem volume estimation based on airborne laser scanning and national forest inventory data - Int. Journal of Rem. Sens., 30/19:5159-5175.

  • Iost, A., 2006. Untersuchung der Eignung logistischer Regressionsmodelle zur Kartierung forstlicher Merkmale mit Satelliten- Fernerkundungsdaten. Hamburg, Germany.

  • Linser, S., 2011: User Engagement in EUFODOS. EUFODOS Newsletter 1/2011. Available at: .

  • Means, J. E., Acker, S. A., Brandon, J. F., Renslow, M., Emerson, L., Hendrix, Ch. J., 2000: Predicting Forest Stand Characteristics with Airborne Scanning LiDAR - Photogr. Eng. & Rem. Sens, 66:1367-1371.

  • Sačkov, I., Bucha, T., Kiraly, G., Brolly, G., Raši, R., 2014: Individual tree and crown identification in the danube floodplain forests based on airborne laser scanning data, EARSeL 34th Symposium Proceedings, Warsaw, 16-20 June 2014, p. 6.20-6.26.

  • Schardt, M., Granica, K., 2012: Success Stories - Improved Information on Forest Structure and Damages. In: Discover what GMES can do for European regions and cities. Window on GMES. A GMES4Regions Publication. Special Issue November 2012.

  • Schardt, M., 2014: European Forest Downstream Services - Improved Information on Forest Structure and Damages. Final Report to the European Commission Research and Innovation DG.

  • Schreuder, H., Wood, G., Gregoire, T., 1993: Sampling Methods for Multiresource Forest Inventory, John Wiley & Sons, p. 117.

  • Wack, R., 2006: Assessment of Alpine Protection Forest Parameters based on LiDAR Data and SPOT V Satellite Imagery. Proceedings of the HMRSC Workshop Graz, Austria.

Central European Forestry Journal

The Journal of National Forest Centre – Forest Research Institute Zvolen

Journal Information


CiteScore 2016: 0.56

SCImago Journal Rank (SJR) 2016: 0.230
Source Normalized Impact per Paper (SNIP) 2016: 0.454

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