Discriminating the occurrence of pitch canker infection in Pinus radiata forests using high spatial resolution QuickBird data and artificial neural networks

International Geoscience and Remote Sensing Symposium (IGARSS)

Volumn , Issue , 2012, Pages 3371-3374

  Poona, Nitesh K ^a   Ismail, Riyad ^b  

^a STELLENBOSCH UNIVERSITY   (South Africa)

^b UNIVERSITY OF KWAZULU NATAL   (South Africa)

Author keywords

forestry; Fusarium circinatum; multi layer perceptron; QuickBird

Indexed keywords

DISCRIMINATORY POWER; FUSARIUM; HIGH SPATIAL RESOLUTION; LANDSCAPE SCALE; MULTI LAYER PERCEPTRON; NAIVE BAYES CLASSIFIERS; NEURAL NETWORK MODEL; PINUS RADIATA; PITCH CANKER; PITCH CANKER DISEASE; QUICKBIRD; QUICKBIRD IMAGERIES; RADIATA; SOUTH AFRICA; SPATIAL SCALE; TASSELED CAP TRANSFORMATION; TREE CROWNS; VEGETATION INDEX;

GEOLOGY; NEURAL NETWORKS; REMOTE SENSING;

FORESTRY;

DISEASES; FORESTRY; GEOLOGY; NEURAL NETWORKS; PINUS RADIATA; PLANTS; REMOTE SENSING; SOUTH AFRICA;

EID: 84873140454     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IGARSS.2012.6350698     Document Type: Conference Paper

References (17)

1. EMPPO (European and Mediterranean Plant Protection Organization), "Gibberella circinata," OEPP/EPPO Bulletin, vol. 35, pp. 383-386, 2005.
2. S.H. Lee and H.K. Cho, "Detection of the pine trees damaged by pine wilt disease using high spatial remote sensing data," in Proceedings of the ISPRS Commission VII Symposium 'Remote Sensing: From Pixels to Processes', 8-11 May, Enschede, the Netherlands, 2006.
3. N.C. Coops, M. Johnson, M.A. Wulder, and J.C. White, "Assessment of QuickBird high spatial resolution imagery to detect red attack damage due to mountain pine beetle infestation," Remote Sensing of Environment, vol. 103, pp. 67-80, 2006.
4. D.G. Leckie, F.A. Gougeon, S. Tinis, T. Nelson, C.N. Burnett, and D. Paradine, "Automated tree recognition in old growth conifer stands with high resolution digital imagery," Remote Sensing of Environment, vol. 94, pp. 311-326, 2005.
5. ITTVIS (ITT Visual Information Solutions), ENVI 4.8, Boulder, Colorado, 2010.
6. D. Tiede and C. Hoffmann, "Process oriented object-based algorithms for single tree detection using laser scanning data," in EARSeL Proceedings of the Workshop on 3D Remote Sensing in Forestry, 14-15 February, Vienna, Austria, Hannover: European Association of Remote Sensing Laboratories, pp. 151-156, 2006.
7. Y. Ke and L.J. Quackenbush, "Forest species classification and tree crown delineation using QuickBird imagery," in Proceedings of ASPRS 2007 Annual Conference, 7-11 May, Tampa, Florida, American Society for Photogrammetry and Remote Sensing, 2007.
8. D. Tiede, S. Lang, and B. Maier, "Transferability of a tree-crown delineation approach using region-specific segmentation," in Proceedings of XIII Simpósio Brasileiro de Sensoriamento Remoto, 21-26 April, Florianópolis, Brazil, pp. 1883-1890, 2007.
9. Z. Li, R.F. Hayward, J. Zhang, and Y. Liu, "Individual tree crown delineation techniques for vegetation management in power line corridor," in Proceedings of the 10th International Conference on Digital Image Computing: Techniques and Applications (DICTA2008), 1-3 December, Canberra, Australia, IEEE Computer Society, pp. 148-154, 2008.
10. Trimble, "eCognition Developer 8," Trappentreustrasse, Munich, 2011.
11. L.D. Yarbrough, G. Easson, and J.S. Kuszmaul, "Tasseled Cap Coefficients for the QuickBird 2 sensor: A comparison of methods and development," in Proceedings of Pecora 16 'Global priorities in land remote sensing', 23-27 October, Sioux Falls, South Dakota, American Society for Photogrammetry and Remote Sensing, 2005.
12. M. Hall, E. Frank, G. Holmes, B. Pfahringer, P. Reutemann, and I.H. Witten, "The WEKA data mining software: an update. SIGKDD Explorations, vol. 11, pp. 10-18, 2009.
13. A.K. Skidmore, B.J. Turner, W. Brinkhof, and E. Knowles, "Performance of a neural network: mapping forests using GIS and remotely sensed data," Photogrammetric Engineering & Remote Sensing, vol. 63, pp. 501-514, 1997.
14. R.G. Congalton and K. Green, "Assessing the accuracy of remotely sensed data: principles and practices" (2nd edn), Boca Raton, CRC Press, 2009.
15. G.S. Boggs, "Assessment of SPOT 5 and QuickBird remotely sensed imagery for mapping tree cover in savannas," International Journal of Applied Earth Observation and Geoinformation, vol. 12, pp. 217-224, 2010.
16. N. Goodwin, N.C. Coops, and C. Stone, "Assessing plantation canopy condition from airborne imagery using spectral mixture analysis and fractional abundances," International Journal of Applied Earth Observation and Geoinformation, vol. 7, pp. 11-28, 2005.
17. A. Haywood and C. Stone, "Mapping eucalypt forest susceptible to dieback associated with bell miners (Manorina melanophys) using laser scanning, SPOT 5 and ancillary topographical data," Ecological Modelling, vol. 222, pp. 1174-1184, 2011.