Using Digital Aerial Photogrammetry and the Random Forest Approach to Model Forest Inventory Attributes in Beech-And Spruce-dominated Central European Forests

Journal of Bionanoscience

Volumn 10, Issue 3, 2016, Pages 109-123

  Straub, Christoph ^a   Stepper, Christoph ^a  

^a Bavarian State Institute of Forestry   (Germany)

Author keywords

Canopy height model; Digital aerial photographs; Forest inventory; Random forest; Semi global matching

Indexed keywords

AERIAL PHOTOGRAPHY; DECISION TREES; FORESTRY; IMAGE MATCHING; PHOTOGRAMMETRY; PHOTOGRAPHIC EQUIPMENT; PHOTOGRAPHY;

CANOPY HEIGHT MODELS; DIGITAL AERIAL PHOTOGRAPHS; FOREST INVENTORY; RANDOM FORESTS; SEMI-GLOBAL MATCHING;

FORECASTING;

EID: 84988848262     PISSN: 15577910     EISSN: 15577929     Source Type: Journal    
DOI: 10.1127/pfg/2016/0292     Document Type: Article

References (52)

1. Adler, P. & Koch, B., 1999: Digital photogrammetry for forest ecosystem monitoring. - Conference Proceedings 'Remote Sensing and Forest Monitoring', Rogów, Poland.
2. Baccini, A., Friedl, M.A., Woodcock, C.E. & Warbington, R., 2004: Forest biomass estimation over regional scales using multisource data. - Geophysical Research Letters 31: L10501.
3. BaySF, 2015: Statistikband 2015, Bayerische Staatsforsten. - http://www.baysf.de/de/publikationen.html (7.3.2016).
4. Breiman, L., 2001: Random forests. - Machine learning 45 (1): 5-32.
5. Gehrke, S., Morin, K., Downey, M., Boehrer, N. & Fuchs, T., 2010: Semi-global matching: An alternative to LIDAR for DSM generation? - The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XXXVIII, Part 1.
6. Ginzler, C. & Hobi, M., 2015: Countrywide stereoimage matching for updating digital surface models in the framework of the Swiss National Forest Inventory. - Remote Sensing 7 (4): 4343- 4370.
7. Gobakken, T., Bollandsås, O.M. & Næsset, E., 2015: Comparing biophysical forest characteristics estimated from photogrammetric matching of aerial images and airborne laser scanning data. - Scandinavian Journal of Forest Research 30 (1): 73-86.
8. Haala, N. & Rothermel, M., 2012: Dense Multi- Stereo Matching for High Quality Digital Elevation Models. - PFG - Photogrammetrie, Fernerkundung, Geoinformation 2012 (4): 331-343.
9. Hastie, T., Tibshirani, R. & Friedman, J.H., 2009: The elements of statistical learning. - Second edition, Springer, New York, NY, USA.
10. Hirsch Müll er, H., 2008: Stereo processing by semiglobal matching and mutual information. - IEEE Transactions on Pattern Analysis and Machine Intelligence 30 (2): 328-341.
11. Immitzer, M., Stepper, C., Böck, S., Straub, C. & Atzberger, C., 2016: Use of WorldView-2 stereo imagery and National Forest Inventory data for wall-to-wall mapping of growing stock. - Forest Ecology and Management 359: 232-246.
12. Joanneum Research, 2014: Remote Sensing Software Package Graz. - http://www.remotesensing.at/en/remote-sensing-software.html (7.3.2016).
13. Kätsch, C. & Stöcker, M., 2000: Untersuchungen zur automatischen Ermittlung von Bestandeshöhen auf Luftbildern mit Hilfe der Digitalen Photogrammetrie. - Allgemeine Forst- und Jagdzeitung 171: 74-80.
14. Korpela, I. & Anttila, P., 2004: Appraisal of the mean height of trees by means of image matching of digitised aerial photographs. - The Photogrammetric Journal of Finland 19 (1): 23-36.
15. Kramer, H. & Akça, A., 2008: Leitfaden zur Waldmesslehre. - J.D. Sauerländer's Verlag, Frankfurt am Main.
16. Kuhn, M. & Johnson, K., 2013: Applied Predictive Modeling. - Springer, New York, NY, USA.
17. Kuhn, M., 2015: Package 'caret'. - https://cran.rproject.org/web/packages/caret/caret.pdf (7.3.2016).
18. Lawrence, M., McRoberts, R.E., Tomppo, E., Gschwantner, T. & Gabler, K., 2010: Comparisons of National Forest Inventories. - Tomppo, E., Gschw antner T., Lawrence, M. & McRoberts, R.E. (eds.): National Forest Inventories. - Springer, 19- 32.
19. LDBV, 2015a: Digitale Geländemodelle (DGM). Product information leaflet. - http://vermessung.bayern.de/file/pdf/1614/download-faltblattdgm09.pdf (7.3.2016).
20. LDBV, 2015b: Luftbild produkte. Product information leaflet. - http://vermessung.bayern.de/file/pdf/1039/download-faltblatt-luftbilder08.pdf (7.3.2016).
21. Lewin-Koh, N., 2011: Hexagon Binning: An Overview. - https://cran.r-project.org/web/packages/hexbin/vignettes/hexagon-binning.pdf (7.3.2016).
22. Liaw, A. & Wiener, M., 2002: Classification and Regression by randomForest. - R news 2 (3): 18-22.
23. Maltamo, M. & Pack Alen, P., 2014: Species-specific management inventory in Finland. - Maltamo, M., Næss et, E. & Vauhk onen, J. (eds.): Forestry Applications of Airborne Laser Scanning. - Springer, 241-252, Dordrecht, Netherlands.
24. Means, J.E., Acker, S.A., Fitt, B.J., Rensl ow, M., Emerson, L. & Hendrix, C.J., 2000: Predictingforest stand characteristics with airborne scanning LiDAR. - Photogrammetric Engineering & Remote Sensing 66 (11): 1367-1371.
25. MVTec Software GmbH 2015: HALCON. - http://www.halcon.com/(7.3.2016).
26. Næsset, E., 2002a: Predicting forest stand characteristics with airborne scanning laser using a practical two-stage procedure and field data. - Remote Sensing of Environment 80 (1): 88-99.
27. Næsset, E., 2002b: Determination of mean tree height of forest stands by digital photogrammetry. - Scandinavian Journal of Forest Research 17 (5): 446-459.
28. Næsset, E., 2014: Area-based inventory in Norway - from innovation to an operational reality. - Maltamo, M., Næss et, E. & Vauhk onen, J. (eds.): Forestry Applications of Airborne Laser Scanning. - Springer, 215-240, Dordrecht, Netherlands.
29. Neufanger, M., 2011: Richtlinie für die mittel- und langfristige Forstbetriebsplanung in den Bayerischen Staatsforsten. - Forsteinrichtungsrichtlinie - FER 2011.
30. Niklas, K.J., 1994: Plant allometry. - University of Chicago Press, Chicago, IL, USA.
31. Nurminen, K., Karjalainen, M., Yu, X., Hyyppä, J. & Honkavaara, E., 2013: Performance of dense digital surface models based on image matching in the estimation of plot-level forest variables. - ISPRS Journal of Photogrammetry and Remote Sensing 83: 104-115.
32. Pack Alen, P. & Maltamo, M., 2007: The k-MSN method in the prediction of species specific stand attributes using airborne laser scanning and aerial photographs. - Remote Sensing of Environment 109 (3):328-341.
33. Penner, M., Pitt, D.G. & Woods, M.E., 2013: Parametric vs. nonparametric LiDAR models for operational forest inventory in boreal Ontario. - Canadian Journal of Remote Sensing 39 (5): 426-443.
34. Pitt, D.G., Woods, M. & Penner, M., 2014: A Comparison of point clouds derived from stereo imagery and airborne laser scanning for the area-based estimation of forest inventory attributes in boreal Ontario. - Canadian Journal of Remote Sensing 40 (3): 214-232.
35. Pretzsch, H., Dauber, E. & Biber, P., 2013: Species- specific and ontogeny-related stem allometry of European forest trees: Evidence from extensive stem analyses. - Forest Science 59 (3): 290-302.
36. R Core Team, 2015: The R project for statistical computing. - https://www.r-project.org/(7.3.2016).
37. Rahlf, J., Breidenbach, J., Solberg, S., Næss et, E. & Astrup, R., 2014: Comparison of four types of 3D data for timber volume estimation. - Remote Sensing of Environment 155: 325-333.
38. Rapidlass o GmbH 2015: LAStools. -http://rapidlasso.com/lastools/(7.3.2016).
39. Stepper, C., Straub, C. & Pretzsch, H., 2015: Using semi-global matching point clouds to estimate growing stock at the plot and stand levels: Application for a broadleaf-dominated forest in central Europe. - Canadian Journal of Forest Research 45 (1): 111-123.
40. St-Onge, B., Jumelet, J., Cobello, M. & Vega, C., 2004: Measuring individual tree height using a combination of stereophotogrammetry and lidar. - Canadian Journal of Forest Research 34 (10): 2122-2130.
41. St-Onge, B., Vega, C., Fournier, R.A. & Hu, Y., 2008: Mapping canopy height using a combination of digital stereo-photogrammetry and lidar. - International Journal of Remote Sensing 29 (11): 3343-3364.
42. Straub, C., Stepper, C., Seitz, R. & Waser, L.T., 2013: Potential of UltraCamX stereo images for estimating timber volume and basal area at the plot level in mixed European forests. - Canadian Journal of Forest Research 43 (8): 731-741.
43. Straub, C. & Seitz, R., 2014: Verwendungspotential von Fernerkundungsdaten in der Forsteinrichtung. - Vortrag bei der Tagung der Arbeitsgemeinschaft Forsteinrichtung am 22.10.2014 in Weimar.
44. Thünen-Institut, 2015: Dritte Bundeswaldinventur (2012). - https://bwi.info. (7.3.2016).
45. Van Laar, A. & Akça, A., 2007: Forest Mensuration. - Springer, Dordrecht, Netherlands.
46. Vanselow, K.A. & Samimi, C., 2014: Predictive mapping of dwarf shrub vegetation in an arid high mountain ecosystem using remote sensing and Random Forests. - Remote Sensing 6: 6709-6726.
47. Vastaranta, M., Wulder, M.A., White, J.C., Pekkarinen, A., Tuominen, S., Ginzler, C., Kankare, V., Holopainen, M., Hyyppä, J. & Hyyppä, H., 2013: Airborne laser scanning and digital stereo imagery measures of forest structure: comparative results and implications to forest mapping and inventory update. - Canadian Journal of Remote Sensing 39 (05): 382-395.
48. White, J.C., Wulder, M.A., Vastaranta, M., Coops, N.C., Pitt, D. & Woods, M., 2013a: The utility of image-based point clouds for forest inventory: A comparison with airborne laser scanning. - Forests 4 (3): 518-536.
49. White, J.C., Wulder, M.A., Varhola, A., Vastaranta, M., Coops, N.C., Cook, B.D., Pitt, D. & Woods, M., 2013b: A best practices guide for generating forest inventory attributes from airborne laser scanning data using an area-basedapproach. - Canadian Wood Fibre Centre, Victoria, BC, Canada. - http://cfs.nrcan.gc.ca/publications?id=34887 (7.3.2016).
50. White, J., Stepper, C., Tompalsk i, P., Coops, N. & Wulder, M., 2015: Comparing ALS and imagebased point cloud metrics and modelled forest inventory attributes in a complex coastal forest environment. - Forests 6 (10): 3704-3732.
51. Woods, M., Pitt, D., Penner, M., Lim, K., Nesbitt, D., Etheridge, D. & Treitz, P., 2011: Operational implementation of a LiDAR inventory in Boreal Ontario. - The Forestry Chronicle 87 (4): 512- 528.
52. Yu, X., Hyyppä, J., Holopainen, M. & Vastaranta, M., 2010: Comparison of area-based and individual tree-based methods for predicting plot-level forest attributes. - Remote Sensing 2 (6): 1481- 1495.