Application of a single-tree identification algorithm to LiDAR data for the simulation of stem volume current annual increment

Journal of Applied Remote Sensing

Volumn 7, Issue 1, 2013, Pages

  Bottai, Lorenzo ^a   Arcidiaco, Lorenzo ^a   Chiesi, Marta ^b   Maselli, Fabio ^b  

^a LaMMA Consortium   (Italy)

^b CNR   (Italy)

Author keywords

Current annual increment; LiDAR; Mediterranean pine; Stem volume

Indexed keywords

DIGITAL STORAGE; OPTICAL RADAR;

ACCURACY ASSESSMENT; CONVERGENCE INDICES; CURRENT ANNUAL INCREMENTS; GROUND MEASUREMENTS; LIGHT DETECTION AND RANGING; MEDITERRANEAN PINES; STEM VOLUME; TREE IDENTIFICATION;

FORESTRY;

ALGORITHMS; ESTIMATION; FORESTRY; PINUS; RADAR;

EID: 84887478446     PISSN: None     EISSN: 19313195     Source Type: Journal    
DOI: 10.1117/1.JRS.7.073699     Document Type: Article

References (38)

1. M. A. Lefsky et al., "LiDAR remote sensing for ecosystem studies," BioScience 52(1), 19-30 (2002), http://dx.doi.org/10.1641/0006- 3568(2002)052[0019:LRSFES]2.0.CO;2. (Pubitemid 34119618)
2. S. Popescu, R. Wynne, and R. Nelson, "Measuring individual tree crown diameter with LiDAR and assessing its influence on estimating forest volume and biomass," Can. J. Remote Sens. 29(5), 564-577 (2003), http://dx.doi.org/10.5589/m03-027.
3. J. Hyyppä et al., "Review of methods of small-footprint airborne laser scanning for extracting forest inventory data in boreal forests," Int. J. Remote Sens. 29(5), 1339-1366 (2008), http://dx.doi.org/10.1080/01431160701736489. (Pubitemid 351321080)
4. M. Larsen et al., "Comparison of six individual tree crown detection algorithms evaluated under varying forest conditions," Int. J. Remote Sens. 32(20), 5827-5852 (2011), http://dx.doi.org/10.1080/01431161.2010.507790.
5. J. Vaukonen et al., "Comparative testing of single-tree detection algorithms under different types of forest," Forestry 85(1), 27-40 (2011), http://dx.doi.org/10.1093/forestry/cpr051.
6. H. Kaartinen et al., "An international comparison of individual tree detection and extraction using airborne laser scanning," Remote Sens. 4, 950-974 (2012), http://dx.doi.org/10.3390/rs4040950.
7. H. Yu et al., "Comparison of area-based and individual tree-based methods for predicting plot-level forest attributes," Remote Sens. 2, 1481-1495 (2010), http://dx.doi.org/10.3390/rs2061481.
8. R. Kiss, "Determination of drainage network in digital elevation model, utilities and limitations," J. Hung. Geomath. 2, 16-29 (2004).
9. P. Corona and L. Fattorini, "Area-based LiDAR-assisted estimation of forest standing volume," Can. J. For. Res. 38(11), 2911-2916 (2008), http://dx.doi.org/10.1139/X08-122.
10. F. Maselli et al., "Modelling the forest carbon budget of a Mediterranean region through the integration of ground and satellite data," Ecol. Modell. 220, 330-342 (2009), http://dx.doi.org/10.1016/j.ecolmodel.2008. 10.002.
11. F. Rapetti and S. Vittorini, Carta climatica della Toscana, Pacini Editore, Pisa, Italy (1995).
12. D. R. E. Am, Tenuta di San Rossore. Note illustrative della carta forestale e della fruizione turistica, S.EL.CA., Firenze, Italy (2003).
13. F. Maselli, R. Mari, and M. Chiesi, "Use of LiDAR data to simulate forest net primary production," Int. J. Remote Sens. 34(7), 2487-2501 (2013), http://dx.doi.org/10.1080/01431161.2012.745019.
14. M. Chiesi, F. Maselli, and P. Cherubini, "Adaptation of a strategy to model the NPP of evenaged pine forest stands," Eur. J. For. Res. 131(4), 1175-1184 (2012), http://dx.doi.org/10.1007/s10342-011-0588-z.
15. F. Maselli et al., "Use of ETM+ images to extend stem volume estimates obtained from LiDAR data," ISPRS J. Photogramm. Remote Sens. 66(5), 662-671 (2011), http://dx.doi.org/10.1016/j.isprsjprs.2011.04.007.
16. M. E. Hodgson, "Searching methods for rapid grid interpolation," Prof. Geogr. 41(1), 51-61 (1989), http://dx.doi.org/10. 1111/j.0033-0124.1989.00051.x.
17. J.-S. Lee, "Digital image enhancement and noise filtering by use of local statistics," IEEE Trans. Pattern Anal. Mach. Intell. PAMI-2(2), 165-168 (1980), http://dx.doi.org/10.1109/TPAMI.1980.4766994.
18. M. Unser, "Splines: a perfect fit for signal and image processing," IEEE Sig. Process. Mag. 16(6), 22-38 (1999), http://dx.doi.org/10.1109/79.799930. (Pubitemid 129604862)
19. S. Beucher, "The watershed transformation applied to image segmentation," Scann. Microsc. Int. 6, 299-314 (1992), http://dx.doi.org/ 10.1.1.24.5229.
20. Q. Chen et al., "Isolating individual trees in a savanna woodland using small footprint Lidar data," Photogramm. Eng. Rem. S. 72(8), 923-932 (2006). (Pubitemid 44156475)
21. C. Edson and M. G. Wing, "Airborne Light Detection and Ranging (LiDAR) for individual tree stem location, height, and biomass measurements," Remote Sens. 3, 2494-2528 (2011), http://dx.doi.org/10.3390/ rs3112494.
22. C. J. Willmott and K. Matsuura, "Advantages of the mean absolute error (MAE) over the root mean square error (RMSE) in assessing average model performance" Clim. Res. 30, 79-82 (2005), http://dx.doi.org/10.3354/ cr030079. (Pubitemid 43072682)
23. F. Maselli et al., "Assessment of forest net primary production through the elaboration of multisource ground and remote sensing data," J. Environ. Monit. (2010), http://dx.doi.org/10.1039/b924629k.
24. F. Veroustraete et al., "Carbon mass fluxes of forests in Belgium determined with low resolution optical sensors," Int. J. Remote Sens. 25(4), 769-792 (2004), http://dx.doi.org/10.1080/0143116031000115238. (Pubitemid 38335407)
25. F. Maselli et al., "Combining remote sensing and ancillary data to monitor the gross productivity of water-limited forest ecosystems," Remote Sens. Environ. 113(3), 657-667 (2009), http://dx.doi.org/10.1016/j.rse.2008.11. 008.
26. R. B. Myneni and D. L. Williams, "On the relationship between fAPAR and NDVI," Remote Sens. Environ. 49(3), 200-211 (1994), http://dx.doi.org/10.1016/0034-4257(94)90016-7.
27. R. H. Waring and S. W. Running, Forest Ecosystems: Analysis at Multiple Scales, 3rd ed., pp. 263-291, Academic Press, San Diego, California (2007).
28. M. Chiesi et al., "Application of BIOME-BGC to simulate Mediterranean forest processes," Ecol. Modell. 206(1-2), 179-190 (2007), http://dx.doi.org/10.1016/j.ecolmodel.2007.03.032. (Pubitemid 46977560)
29. S. Federici et al., "An approach to estimate carbon stocks change in forest carbon pools under the UNFCCC: the Italian case," iForest 1, 86-95 (2008), http://dx.doi.org/10.3832/ifor0457-0010086.
30. M. A. Lefsky et al., "LiDAR remote sensing of above-ground biomass in three biomes" Glob. Ecol. Biogeogr. 11, 393-399 (2002), http://dx.doi.org/10.1046/j.1466-822x.2002.00303.x. (Pubitemid 44769607)
31. M. A. Lefsky et al., "Geographic variability in LiDAR predictions of forest stand structure in the Pacific Northwest," Remote Sens. Environ. 95, 532-548 (2005), http://dx.doi.org/10.1016/j.rse.2005.01.010. (Pubitemid 40466320)
32. V. Thomas et al., "Mapping stand-level forest biophysical variables for a mixedwood boreal forest using lidar: an examination of scanning density," Can. J. For. Res. 36, 34-47 (2006), http://dx.doi.org/10.1139/ x05-230. (Pubitemid 43828038)
33. E. Næsset et al., "Laser scanning of forest resources: the Nordic experience," Scand. J. For. Res. 19(6), 482-499 (2004), http://dx.doi.org/10.1080/02827580410019553. (Pubitemid 40033865)
34. M. Hollaus et al., "Airborne laser scanning of forest stem volume in a mountainous environment," Sensors 7, 1559-1577 (2007), http://dx.doi.org/10.3390/s7081559.
35. F. Maselli et al., "Use of ground and LiDAR data to model the NPP of a Mediterranean pine Forest," Remote Sens. Lett. 2(4), 309-316 (2011), http://dx.doi.org/10.1080/01431161.2010.521897.
36. E. Næsset and T. Gobakken, "Estimating forest growth using canopy metrics derived from airborne laser scanner data," Remote Sens. Environ. 96(3-4), 453-465 (2005), http://dx.doi.org/10.1016/j.rse.2005.04.001. (Pubitemid 40912443)
37. X. Yu et al., "Obtaining plotwise mean height and volume growth in boreal forests using multi-temporal laser surveys and various change detection techniques," Int. J. Remote Sens. 29(5), 1367-1386 (2008), http://dx.doi.org/10.1080/01431160701736356. (Pubitemid 351321081)
38. S. Magnussen, E. Næsset, and T. Gobakken, "Reliability of LiDAR derived predictors of forest inventory attributes: a case study with Norway spruce," Remote Sens. Environ. 114(4), 700-712 (2010), http://dx.doi.org/10.1016/j.rse.2009.11.007.