Automated airborne LiDAR-based assessment of timber measurements for forest management

• Autorzy: Zaremba M. B. , Doyon F. , Senécal J. F.
• Języki publikacji: EN

Abstrakty

EN

This paper presents processing and analysis techniques to apply LiDAR data to estimate tree diameter at breast height (DBH) - a critical variable applied in a large number of forest management tasks. Our analysis focuses on the estimation of DBH using only LiDAR-derived tree height and tree crown dimensions, i.e., variables accessible from aerial observations. The modeling process was performed using 161 white and red pine trees from four 3850 m2 plots in the Foret de l'Aigle located in southwestern Quebec. Segments of the LiDAR data extracted for DBH estimation were obtained using the Individual Tree Crown (ITC) delineation method. Regression models were investigated using height as well as crown dimensions, which increased the precision of the model. This study demonstrates that DBH can be modeled to acceptable accuracy using altimetry data and automated data processing procedures and then be used in high-precision timber volume assessment.

Słowa kluczowe

EN

forest mensuration; lidar; remote sensing; terrain modeling; tree crown; timber volume modeling; white pine

• Wydawca: Production Engineering Committee of the Polish Academy of Sciences ; Polish Association for Production Management
• Czasopismo: Management and Production Engineering Review
• Rocznik: 2012
• Tom: Vol. 3, No. 3
• Strony: 79--85
• Opis fizyczny: Bibliogr. 27 poz., rys., tab.

Twórcy

autor

Zaremba M. B.

autor

Doyon F.

autor

Senécal J. F.

• Université du Québec en Outaouais, Department of Computer Science and Engineering, 101, rue St-Jean-Bosco, Gatineau, Quebec J8Y 3G5, Canada, phone: [phone],

Bibliografia

• [1] Lim K., Treitz P., Baldwin K., Morrison I., Green J., Lidar remote sensing of biophysical properties of tolerant hardwood forests, Canadian J. Remote Sensing, 29, 5, 658-678, 2003.
• [2] Magnussen S., Eggermont P., LaRiccia V.N., Recovering tree heights from airborne laser scanner data, Forest Science, 45, 3, 407-422, 1999.
• [3] Maltamo M., Eerik¨ainen K., Pitk¨aten J., Hyypp¨a J., Vehmas M., Estimation of timber volume and stem density based on scanning laser altimetry and expected tree size distribution functions, Remote Sensing of Environment, 90, 319-330, 2004.
• [4] Andersen H.-E., McGaughey R.J., Reutebuch S.E., Estimating forest canopy fuel parameters using LIDAR data. Remote Sensing of Environment, 94, 441-449, 2005.
• [5] Means J., Acker S., Fitt B., Renslow M., Emerson L., Hendrix C., Predicting forest stand characteristics with airborne scanning Lidar, Photogrammetric Engineering and Remote Sensing, 66, 1367-1371, 2000.
• [6] Pasher J., King D.J., Development of a forest structural complexity index based on multispectral airborne remote sensing and topographic data, Canadian J. Forestry Research, 41, 44-58, 2011.
• [7] Gougeon F.A., St-Onge B.A., Wulder M., Leckie D.G., Synergy of airborne laser altimetry and digital videography for individual tree crown delineation, Proc. 23rd Canadian Symposium on Remote Sensing (CD-ROM), Sainte-Foy, Qu´ebec, 2001.
• [8] Hyypp¨a J., Mielonen T., Hyypp¨a H., Maltamo M., Yu X., Honkavaara E., Kaartinen H., Using Individual Tree Crown approach for forest volume extraction with aerial images and laser point clouds, Proc. ISPRS Workshop “Laser scanning 2005”, Enschede, the Netherlands, pp. 144-149, 2005.
• [9] Leckie D., Gougeon F., Hill D., Quinn R.L., Shreenan R., Combined highdensity lidar and multispectral imagery for individual tree crown analysis, Can. J. of Remote Sensing, 29, 5, 633-649, 2003.
• [10] Popescu S.C., Estimating biomass of individual pine trees using airborne lidar, Biomass and Bioenergy, 31, 9, 646-655, 2007.
• [11] Kozak A., A variable-exponent taper equation, Canadian J. Forest Research, 18, 1363-1368, 1988.
• [12] Peng C., Zhang L., Huang S., Zhou X., Parton J., Woods M., Developing ecoregion-based heightdiameter models for jack pine and black spruce in Ontario, Forest Research Report No. 159, 2001, Ontario Forest Research Institute, Sault Ste. Marie, Ontario.
• [13] Kalliovirta J., Tokola T., Functions for estimating stem diameter and tree age using tree height, crown width and existing stand database information, Silva Fennica, 39, 2, 227-248, 2005.
• [14] Schroeder P., Brown S., Mo J., Birdsay R., Ciszewski C., Biomass estimation for temperate broadleaf forests in the United States using inventory data, Forest Science, 43, 424-434, 1997.
• [15] Krajicek J.E., Brinkman K.A., Gingrich S.F., Crown competition - A measure of density, Forest Science, 7, 1, 555-570, 1961.
• [16] Barbezat V., Jacot J., The CLAPA project: Automated classification of forest with aerial photographs, Proc. International Forum: Automated Interpretation of High Spatial Resolution Digital Imagery for Forestry, Victoria B.C., pp. 345-356, 1999.
• [17] Dubé P., Hay G.J., Marceau D.J., Voronoï diagrams, extended area stealing interpolation and tree crown recognition: a fuzzy approach, In: Automated Interpretation of High Spatial Resolution Digital Imagery for Forestry. Canadian Forest Service, Victoria B.C., pp. 115-125, 1998.
• [18] Wulder M., Niemann K.O., Goodenough D.G., Local maximum filtering for the extraction of tree locations and basal area from high spatial resolution imagery, Remote Sensing of Environment, 73, 103-114, 2000.
• [19] Gougeon F.A., A crown-following approach to the automatic delineation of individual tree crowns in high spatial resolution aerial images, Canadian J. of Remote Sensing, 21, 3, 274-284, 1995.
• [20] Palenichka R.M., Zaremba M.B., Multiscale Isotropic Matched Filtering for Individual Tree Detection in LiDAR Images, IEEE Trans. on Geoscience and Remote Sensing, 45, 12, 2864-2879, 2007.
• [21] Popescu S.C., Wynne R.H., Nelson R.F., Measuring individual tree crown diameter with lidar and assessing its influence on estimating forest volume and biomass, Can. J. Remote Sensing, 29, 5, 564-577, 2003.
• [22] Zhang L., Cross-validation of non-linear growth functions for modelling tree height–diameter relationships, Ann. Bot., 79, 251-257, 1997.
• [23] Huang S., Titus S.J., Wiens D.P., Comparison of nonlinear height-diameter functions for major Alberta tree species, Canadian J. Forestry Research, 22, 1297-1304, 1992.
• [24] Peng C., Nonlinear Height-Diameter Models for Nine Boreal Forest Tree Species in Ontario, Forest Research Report No. 155, Ontario Forest Research Institute, Sault Ste. Marie, Ontario, 1999.
• [25] Bozdogan H., Model selection and Akaike’s information criterion (AIC): the general theory and its analytical extensions, Psychometrika, 52, 3, 345-370, 1987.
• [26] Akaike H., Information theory and an extension of the maximum likelihood principle, In B.N. Petrov and F. Csaki (Eds.), Second Int. Symp. on Information Theory, Budapest, pp. 267-281, 1973.
• [27] Huang S., Ecoregion-based individual tree height - diameter models for lodgepole pine in Alberta, West. J. Appl. Forestry, 14, 186-193, 1999.