Fusion of remotely sensed multispectral imagery and LiDAR data for forest structure assessment at the tree level

International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives

Volumn 37, Issue , 2008, Pages 1089-1093

  Ali, S S ^a   Dare, P ^a   Jones, S D ^b  

^a FLINDERS UNIVERSITY   (Australia)

^b RMIT UNIVERSITY   (Australia)

Author keywords

Airborne remote sensing; Classification; Digital photogrammetry; Forestry; Fusion; LiDAR; Multispectral imagery

Indexed keywords

CLASSIFICATION (OF INFORMATION); FUSION REACTIONS; IMAGE SEGMENTATION; MAXIMUM LIKELIHOOD; OPTICAL RADAR; PHOTOGRAMMETRY; REMOTE SENSING;

AIRBORNE REMOTE SENSING; DIGITAL PHOTOGRAMMETRY; LIGHT DETECTION AND RANGING; MARKER-CONTROLLED WATERSHED SEGMENTATION; MAXIMUM LIKELIHOOD CLASSIFICATIONS; MULTI-SPECTRAL IMAGERY; NEW SOUTH WALES , AUSTRALIA; PRINCIPAL COMPONENTS TRANSFORMATIONS;

FORESTRY;

EID: 85007075915     PISSN: 16821750     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (12)

1. Baltsavias, E.P. (1999) A comparison between photogrammetry and laser scanning, ISPRS Journal of Photogrammetry and Remote Sensing, Vol. 54, p. 83-94.
2. Beucher, S. and Lantuejoul, C. (1979) Use of watersheds in contour detection, Proceedings of International Workshop on Image Processing, Real-time Edge and Motion Detection/Estimation, Rennes, France.
3. Chen, Q., Balddocchi, D., Gong, P. and Maggi, K. (2006) Isolating individual trees in a Savnna Woodland using small footprint lidar data, Photogrammetric Engineering & Remote Sensing, Vol. 72, No. 8, pp. 923-932.
4. Clark, D.B., Castro, C.S., Alvarado, L.D.A. and Read, J.M. (2004) Quantifying mortality of tropical rain forest trees using high-spatial-resolution satellite data, Ecological Letters, Vol. 7, pp. 52-59.
5. Gong, P., Biging, G.S., Lee, S.M., Mei, X., Sheng, Y., Pu, R., Xu, B., Schwarz, K. and Mostafa, M. (1999) Photo ecometrics for forest inventory, Geographic Information Science, Vol. 5, pp. 9-14.
6. Kalayeh, H.W. and Landgrebe, D.A. (1983) Predicting the required number of training samples, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 5, pp. 493-504.
7. Kelly, M., Shaari, D., Guo, Q.H. and Liu, D.S (2004) A comparison of standard and hybrid classifier methods for mapping hardwood mortality in areas affected by "sudden oak death", Photogrammetric Engineering & Remote Sensing, Vol. 70, pp. 122-1239.
8. Leberl, F. and Gruber, M. (2005) Ultracam-d: understanding some noteworthy capabilities, Proceedings of Photogrammetric Week 2005, Stuttgart, Germany.
9. Leckie, D., Gougeon, F., Hill, D., Quinn, R., Armstrong, L. and Shreenan, R. (2003) Combinedhigh density LiDAR and multispectral imagery for individual tree crown analysis, Canadian Journal of Remote Sensing, Vol. 29, No. 5, p. 633-649.
10. Meyer, F. and Beucher, S. (1990) Morphological segmentation, Journal of Visual Communication and Image Representation, Vol. 1, No. 1, pp. 21-46.
11. Soille, P. (2003) Morphological image analysis: principles and applications (2nd Edition), Springer, Berlin; New York. 316 pp.
12. Suáreza, J.C., Ontiveros, C., Smith, S. and Snape, S. (2005) Use of airborne LiDAR andaerial photography in the estimation of individual tree heights in forestry, Computers & Geosciences (2005), Vol. 31, No. 2, p. 253-262.