Estimating stand characteristics by combining single tree pattern recognition of digital video imagery and a theoretical diameter distribution model

Forest Science

Volumn 49, Issue 1, 2003, Pages 98-109

  Maltamo, M ^a   Tokola, T ^b   Lehikoinen, M ^c  

^a UNIVERSITY OF EASTERN FINLAND   (Finland)

^b UNIVERSITY OF HELSINKI   (Finland)

^c Oy Arboreal Ltd   (Finland)

Author keywords

Diameter distribution; Optical flow; Stand characteristics estimation; Super resolution; Weibull distribution

Indexed keywords

COMPUTER SIMULATION; COMPUTER SOFTWARE; IMAGE PROCESSING; OPTICAL RESOLVING POWER; PATTERN RECOGNITION; REMOTE SENSING; WEIBULL DISTRIBUTION; COMPUTER GRAPHICS; FORESTRY; IMAGE ENHANCEMENT; OPTICAL REMOTE SENSING;

DIGITAL VIDEO IMAGERY; CROWN AREA; DIAMETER DISTRIBUTION MODELS; DIAMETER DISTRIBUTIONS; DIGITAL VIDEOS; REMOTE-SENSING; STAND CHARACTERISTIC ESTIMATION; STAND CHARACTERISTICS; SUPERRESOLUTION; TREE PATTERN; VIDEO IMAGERY;

FORESTRY; OPTICAL FLOWS;

COMPUTER PROGRAMS; FORESTRY; IMAGE ANALYSIS; PATTERN RECOGNITION; REMOTE SENSING; RESOLUTION; SIMULATION; STATISTICAL DISTRIBUTION; CHARACTERISTICS; DIAMETER; STEMS; TREES;

EID: 0037311872     PISSN: 0015749X     EISSN: None     Source Type: Journal    
DOI: 10.1093/forestscience/49.1.98     Document Type: Article

References (50)

1. BAILEY, R.L., AND T.R. DELL. 1973. Quantifying diameter distribution with the Weibull-function. For. Sci. 19:97-104.
2. BEAUCHEMIN, S.S., AND J.L BARRON. 1995. The computation of optical flow. ACM Comput. Surveys 27: 433-466.
3. BORDERS, B.E., R.A. SOUTER, R.L. BAILEY, AND K.D. WARE. 1987. Percentile-based distributions characterize forest stand tables. For. Sci. 33:570-576.
4. BRANDTSERG, T. 1997. Towards structure-based classification of tree crowns in high spatial resolution aerial images. Scand. J. For. Res. 12:89-96.
5. BRANDTBERG, T., AND F. WALTER. 1998. Automated delineation of individual tree crowns in high spatial resolution aerial images by multiple-scale analysis. Mach. Vision Appl. 11:64-73.
6. CAJANDER, A. K. 1926. The theory of forest types. Acta For. Fenn. 29:1-108.
7. DRALLE, K., AND M. RUDEMO. 1996. Stem number estimation by kernel smoothing in aerial photos. Can. J. For. Res. 26:1228-1236.
8. ELAD, M., AND A. FEUER. 1996. Restoration of single super-resolution image from several blurred, noisy and down-sampled measured images. Dep. of Elect. Eng./Israel Inst. of Tech. EDICS number-IP 1.4. 29 p.
9. FRANKLIN, S.E., W.W. BOWERS, AND G. GHITTER. 1995. Discrimination of adelgid-damage on single Balsam fir trees with aerial remote sensing data. Int. J. Rem. Sens. 16:2779-2794.
10. GOUGEON, F.A. 1995. A crown-following approach to the automatic delineation of individual tree crowns in high spatial resolution aerial images. Can. J. Rem. Sens. 21:274-284.
11. GOUGEON, F.A. 1997. Recognizing the forest from the trees: Individual tree crown delineation, classification and regrouping for inventory purposes. Airborne Remote Sensing Conf. and Exhib., Copengagen, Denmark. Vol. II: 807-815.
12. HÄME, T., AND M. RANTASUO. 1988. Shuttered camera - aerial color video imaging in the visible and near infrared. Photogram. Eng. Rem. Sens. 54:1735-1738.
13. HEIKKILÄ, J. 1998. Monitoring boreal coniferous forest health in Finland using the reference sample plot method with multisource and multitemporal data. Thesis for the Licentiate Degree, For. Mensur., Fac. of For., Univ. of Joensuu. 57 p.
14. HOLOPAINEN, M., AND E. LUKKARINEN. 1994. Digitaalisten ilmakuvien käyttö metsävarojen inventoinnissa. Univ. of Helsinki, Dep. of For. Resour. Manage., Publications 4. 33 p. (In Finnish.)
15. HOLOPAINEN, M., AND G. WANG. 1998. Accuracy of digitized aerial photographs for assessing forest habitats at plot level. Scand. J. For. Res. 13:500-509.
16. HYPPÄNEN, H. 1996. Spatial autocorrelation and optimal spatial resolution of optical remote sensing data in boreal forest environment. Int. J. Rem. Sens. 17:3441-3452.
17. HYYPPÄ, J. 1997. Uudet menetelmät metsien kaukokartoituksessa. Väliraportti. Teknillinen korkeakoulu, avaruustekniikan laboratorio. 23 p. (In Finnish.)
18. HYYPPÄ, J., AND H. HYYPPÄ. 1999. Comparing the accuracy of laser scanner with optical remote sensing data sources for stand attribute retrieval. Photogramm. J. Fin. 16:5-15.
19. HYYPPÄ, J., AND M. INKINEN. 1999. Detecting and estimating attributes for single trees using laser scanner. Photogramm. J. Finland 16:27-42.
20. ILVESSALO, Y. 1950. On the correlation between the crown diameter and the stem of trees. Commun. Inst. For. Fenn. 38. 32 p.
21. JAKOBSONS, A. 1970. Sambandet mellan trädkronans diameter och andra trädfaktorer, främst brösthöjdsdiametern. Analyser grundade på riksskogstaxeringens provträdsmaterial. Stockholms skogshögskolan, institutionen för skogstaxering. Raporter och Uppsatser Nr 14. 75 p. (In Swedish.)
22. KILKKI, P., M. MALTAMO, R. MYKKÄNEN, AND R. PÄIVINEN. 1989. Use of the Weibull function in estimating the basal-area diameter distribution. Silva Fenn. 23: 311-318.
23. LAASASENAHO, J. 1982. Taper curve and volume function for pine, spruce and birch. Commun. Inst. For. Fenn. 108:1-74.
24. LEHIKOINEN, M. 1999. Metsikkötunnusten arvioiminen Optical flow-menetelmällä tarkennetulta videokuvalta hahmontunnistus-menetelmää käyttäen. Thesis for the Master of Science Degree, Forest Mensuration, Faculty of Forestry, University of Joensuu. 67 p. (In Finnish).
25. MALTAMO, M., AND A. KANGAS. 1998. Methods based on k-nearest neighbor regression in the estimation of basal area diameter distribution. Can. J. For. Res. 28:1107-1115.
26. MUINONEN, E. 1995. Metsikön heijastussuhteen ennustaminen geometrisella latvustomallilla. Thesis for the Licentiate Degree, For. Mensur., Fac. of For., Univ. of Joensuu. 52 p. (In Finnish.)
27. NÄSLUND, M. 1936. Skogsfösöksanstaltens gallringförsök i tallskog. Primiärbearbetning. Meddelanden från Statens Skogsförsöksanstalt 29. 169 p. (In Swedish.)
28. NEEDHAM, T., AND J. SMITH. 1987. Stem count accuracy and species determination in loblolly pine plantations using 35-mm aerial photography. Photogramm. Eng. Rem. Sens. 53:1675-1678.
29. NIBLACK, W. 1986. An introduction to digital image processing. Prentice Hall, NJ. 215 p.
30. PELLIKKA, P. 1998. Development of correction chain for multi-spectral airborne video camera data for natural resource assessment. Fennia 176:1. Suomen Maantieteellinen Seura. 110 p. (In Finnish.)
31. POSO, S. 1983. Basic features of forest inventory by compartments. Silva Fenn. 17:313-349.
32. POSO, S., T. HÄME, AND R. PAANANEN. 1984. 1984. A method of estimating the stand characteristics of a forest compartment using satellite imagery. Silva Fenn. 18:261-292.
33. POSO, S., R. PAANANEN, AND M. SIMILÄ. 1987. Forest inventory by compartments using satellite imagery. Silva Fenn. 21:69-94.
34. PRATT, W.K. 1991. Digital image processing. Ed. 2. Sun Microsystems, Inc. Mountain View, CA. Wiley, Inc. 698 p.
35. PUKKALA, T. 1989. Predicting diameter growth in even-aged Scots pine stands with a spatial and non-spatial model. Silva Fenn. 23:101-116.
36. PUKKALA, T., AND T. KOLSTRÖM. 1991. Effect of spatial pattern of trees on the growth of a Norway spruce stand. A simulation model. Silva Fenn. 25:117-131.
37. PUSSINEN, A. 1992. Ilmakuvat ja Landsat TM-satelliittikuva välialueiden kuvioittaisessa arvioinnissa. Thesis for the Master of Science. University of Joensuu, Faculty of Forestry. 48 p. (In Finnish.)
38. RANTASUO, M., AND B. BRAAM. 1992. Color infrared airborne video system development in Finland, VTT (Technical Research Centre of Finland). Surv. Sci. Finland 10:59-69.
39. ROE, P., AND D. SIDILKOVER. 1992. Optimum positive linear schemes for advection in two or three dimensions. SIAM J. Num. Analysis 29:1542-1568.
40. SAASTAMOINEN, J. 1997. Explicit feature enhancement in visual quality inspection. Thesis for the Licentiate Degree, For. Mensur., Fac. of For., Univ. of Joensuu. 102 p.
41. SIIPILEHTO, J. 1999. Improving the accuracy of predicted basal-area diameter distribution in advanced stands by determining stem number. Silva Fenn. 33:281-301.
42. STÅHL, G. 1992. A study on the quality of compartmentwise forest stand data acquired by subjective inventory methods. Dep. of Biometry and For. Manage., Section of For. Mensuration and Manage., Swedish Univ. of Agric. Sci., Umeå, Rep. 24. P. 5-87. ISSN 0349-21333.
43. TOKOLA, T., J. PITKÄNEN, S. PARTINEN, AND E. MUINONEN. 1996. Point accuracy of a non-parametric method in estimation of forest characteristics with different satellite materials. Int. J. Rem. Sens. 17:2333-2351.
44. TOKOLA, T., AND J. HEIKKILÄ. 1997. A priori site quality information in satellite image based forest inventory. Silva Fenn. 31:67-78.
45. TOMPPO, E. 1993. Multi-source national forest inventory of Finland. Finn. For. Res. Inst. Res. Pap. 444:52-60.
46. TROTTER, C.M, J.R. DYMOND, AND C.J. COULDING. 1997. Estimation of timber volume in a coniferous plantation forest using Landsat TM. Int. J. Rem. Sens. 18:2209-2223.
47. SIITONEN, M. 1993. Experiences in the use of forest management planning models. Silva Fenn. 27: 167-178.
48. UUTTERA, J., T. TOKOLA, A. HAARA, AND M. MALTAMO. 1998. Determination of the spatialdistribution of trees from digital aerial photographs. For. Ecol. Manage. 110:275-282.
49. VELTHEIM, T. 1987. Pituusmallit männylle, kuuselle ja koivulle. In: Mäkelä, H. and Salminen, H. (Eds.) 1991. Metsän tilaa ja muutoksia kuvaavia puu-ja puustotunnusmalleja. Metsäntutkimuslaitoksen tiedonantoja 398. 265 p. (In Finnish.) ISBN 951-40-1188-0.
50. ZUTTER, B.R., R.G. ODERWALD, P.A. MURPHY, AND R.M. FARRAR, JR. 1986. Characterizing diameter distributions with modified data types and forms of the Weibull distribution. For. Sci. 32:37-48.