Variation in foliar water content and hyperspectral reflectance of pinus patula trees infested by sirex noctilio

Southern Forests

Volumn 72, Issue 1, 2010, Pages 1-7

  Mutanga, O ^a   Ismail, R ^a  

^a UNIVERSITY OF KWAZULU NATAL   (South Africa)

Author keywords

Absorption features; Continuum removed absorption features; Foliar water content; Hyperspectral; Sirex noctilio; Spectral indices

Indexed keywords

PINUS PATULA; SIREX NOCTILIO; SIRICOIDEA;

EID: 78650334641     PISSN: 20702620     EISSN: 20702639     Source Type: Journal    
DOI: 10.2989/20702620.2010.481073     Document Type: Article

References (39)

1. Analytical Spectral Devices. 2002. FieldSpec Pro users guide, Boulder: Analytical Spectral Devices.
2. Bowyer P, Danson FM. 2004. Sensitivity of spectral reflectance to variation in live fuel moisture content at leaf and canopy level. Remote Sensing of Environment 92: 297-308.
3. Carter GA. 1991. Primary and secondary effects of water concentration on the spectral reflectance of leaves. American Journal of Botany 78: 916-924.
4. Ceccato P, Flasse S, Tarantola S, Jacquemoud S, Gregoire J. 2001. Detecting vegetation leaf water content using reflectance in the optical domain. Remote Sensing of Environment 77: 22-33.
5. Clark RN. 1999. Spectroscopy of rocks and minerals, and principles of spectroscopy. In: Rencz AN (ed.), Manual of remote sensing, vol 3: remote sensing for the earth sciences. New York: John Wiley and Sons. pp 3-58.
6. Clark RN, Roush TL. 1984. Reflectance spectroscopy: quantitative analysis techniques for remote sensing applications. Journal of Geophysical Research 89: 6329-6340.
7. Cohen WB. 1991a. Response of vegetation indexes to changes in 3 measures of leaf water-stress. Photogrammetric Engineering and Remote Sensing 57: 195-202.
8. Cohen WB. 1991b. Temporal versus spatial variation in leaf reflectance under changing water-stress conditions. International Journal of Remote Sensing 12: 1865-1876.
9. Coutts MP. 1970. The physiological effects of the mucus secretion of Sirex noctilio on Pinus radiata. Australian Forest Research 4: 23-26.
10. Coutts MP. 1965. Sirex noctilio and the physiology of Pinus radiata. Some studies of interactions between the insect, the fungus, and the tree in Tasmania. Forestry and Timber Bureau 41: 79.
11. Coutts MP. 1968. Rapid physiological change in Pinus radiate following attack by Sirex noctilio and its associated fungus, Amylostereum sp. Australian Journal of Science 30: 275-277.
12. Curran PJ. 1989. Remote sensing of foliar chemistry. Remote Sensing of Environment 30: 271-287.
13. Dawson TP, Curran PJ, North PRJ, Plummer SE. 1999. The propagation of foliar biochemical absorption features in forest canopy reflectance: a theoretical analysis. Remote Sensing of Environment 67: 147-159.
14. Eitel JUH, Gessler PE, Smith AMS, Robberecht R. 2006. Suitability of existing and novel spectral indices to remotely detect water stress in Populus spp. Forest Ecology and Management 229: 170-182.
15. Gao BC, Heidebrecht KB, Goetz AFH. 1993. Derivation of scaled surface reflectances from AVIRIS data. Remote Sensing of Environment 44: 165-178.
16. Gausman HW, Allen WA, Escobar DE, Rodriguez RR, Cardenas R. 1971. Age effects of cotton leaves on light reflectance, transmittance and absorptance and on water content thickness. Agronomy Journal 63: 465-469.
17. Hardinsky MA, Klemas V, Smart M. 1983. The influence of soil salinity, growth form, and leaf moisture on the spectral radiance of Spartina alterniflora canopies. Photogrammetric Engineering and Remote Sensing 49: 77-83.
18. Huanga Z, Turnera BJ, Durya BJ, Wallis IR, Foley WJ. 2004. Estimating foliage nitrogen concentration from HYMAP data using continuum removal analysis. Remote Sensing of Environment 93: 18-29.
19. Hurley BP, Slippers B, Wingfield MJ. 2007. A comparison of control results for the alien invasive woodwasp, Sirex noctilio, in the southern hemisphere. Agricultural and Forest Entomology 9: 159-171.
20. Inoue Y, Morinaga S, Shibayama M. 1993. Non-destructive estimation of water status of intact crop leaves based on spectral reflectance measurements. Japan Journal of Crop Science 62: 462-469.
21. Ismail R, Mutanga O, Ahmed F. 2008. Discriminating Sirex noctilio attack in pine forest plantations in South Africa using high spectral resolution data. In: Kalacska M, Sanchez-Azofeifa GA (eds), Hyperspectral remote sensing of tropical and subtropical forests. Boca Raton: CRC Press. pp 161-174.
22. Ismail R, Mutanga O, Bob U. 2006. The use of high resolution airborne imagery for the detection of forest canopy damage by Sirex noctilio. In: Ackerman PA, Längin DW, Antonides MC (eds), Precision forestry in plantations, semi-natural areas and natural forest: proceedings of the International Precision Forestry Symposium, Stellenbosch University, 5-10 March 2006. Stellenbosch: Stellenbosch University. pp 119-134.
23. Ismail R, Mutanga O, Bob U. 2007. Forest health and vitality: the detection and monitoring of Pinus patula trees infected by Sirex noctilio using digital multispectral imagery (DMSI). Southern Hemisphere Forestry Journal 69: 39-47.
24. Kokaly RF, Clark RN. 1999. Spectroscopic determination of leaf biochemistry using band-depth analysis of absorption features and stepwise multiple linear regression. Remote Sensing of Environment 67: 267-287.
25. Madden JL. 1974. Oviposition behaviour of the woodwasp. Australian Journal of Zoology 22: 341-351.
26. Mutanga O, Skidmore AK. 2004. Integrating imaging spectroscopy and neural networks to map tropical grass quality in the Kruger National Park, South Africa. Remote Sensing of Environment 90: 104-115.
27. Mutanga O, Skidmore AK, van Wieren S. 2003. Discriminating tropical grass canopies (Cenchrus ciliaris) grown under different nitrogen treatments using spectroradiometry. ISPRS Photogrammetry Engineering and Remote Sensing 57: 263-272.
28. Mutanga O, van Aardt JAN, Kumar L. 2009. Imaging spectroscopy (hyperspectral remote sensing) in southern Africa: an overview. South African Journal of Science 105: 193-198.
29. Penuelas J, Pinol J, Ogaya R, Filella I. 1997. Estimation of plant water concentration by the reflectance Water Index WI (R900/ R970). International Journal of Remote Sensing 18: 2869-2875.
30. Pontius J, Hallet R, Martin M. 2005. Assessing hemlock decline using visible and near-infrared spectroscopy: indices comparison and algorithm development. Applied Spectroscopy 59: 836-843.
31. Pu R, Ge S, Kelly NM, Gong P. 2003. Spectral absorption features as indicators of water status in coast live oak (Quercus agrifolia) leaves. International Journal of Remote Sensing 24: 1799-1810.
32. Rouse JW, Haas RH, Schell JA, Deering DW. 1973. Monitoring vegetation systems in the Great Plains with ERTS. In: Proceedings of the Third ERTS-1 Symposium, vol. 1. NASA SP-351. Washington, DC: Goddard Space Flight Center, NASA. pp. 309-317.
33. Scholes B, Annamalai L. 2006. CSIR imaging expertise propels SA to a science high. Aerospace Science Scope 2006: 19-21.
34. Sims DA, Gamon JA. 2003. Estimation of vegetation water content and photosynthetic tissue area from spectral reflectance: a comparison of indices based on liquid water and chlorophyll absorption features. Remote Sensing of Environment 84: 526-537.
35. Slippers B. 2006. The sirex epidemic in KwaZulu-Natal and its control. Wood and Timber Times Southern Africa 31: 24-25.
36. Slippers B, Coutinho TA, Wingfield BD, Wingfield MJ. 2003. A review of the genus Amylostereum and its association with woodwasps. South African Journal of Science: 70-74.
37. Spradberry JP. 1977. The oviposition biology of siricid woodwasps in Europe. Ecological Entomology 2: 225-230.
38. Stimson H, Breshears D, Ustin S, Kefauver S. 2005. Spectral sensing of foliar water conditions in two co-occurring conifer species: Pinus edulis and Juniperus monosperma. Remote Sensing of Environment 96: 108-118.
39. Tucker J. 1980. Remote sensing of leaf water content in the near infrared. Remote Sensing of Environment 10: 23-32.