Spectral discrimination of healthy and ganoderma-infected oil palms from hyperspectral data

International Journal of Remote Sensing

Volumn 32, Issue 22, 2011, Pages 7111-7129

  Shafri, Helmi Z M ^a   Anuar, Mohd I ^a   Seman, Idris A ^b   Noor, Nisfariza M ^c  

^a UNIVERSITY PUTRA MALAYSIA   (Malaysia)

^b MALAYSIAN PALM OIL BOARD   (Malaysia)

^c UNIVERSITY OF MALAYA   (Malaysia)

Author keywords

[No Author keywords available]

Indexed keywords

DAMAGE DETECTION; MAXIMUM LIKELIHOOD; REFLECTION; REMOTE SENSING;

DISEASE INFESTATION; HYPERSPECTRAL DATA; HYPERSPECTRAL REMOTE SENSING; MAXIMUM LIKELIHOOD CLASSIFIERS; REFLECTANCE SPECTRUM; SPECTRAL DIFFERENCES; SPECTRAL RESPONSE; SPECTRAL SEPARABILITY;

PALM OIL;

ACCURACY ASSESSMENT; CROP PLANT; DETECTION METHOD; INFECTIOUS DISEASE; MAXIMUM LIKELIHOOD ANALYSIS; REMOTE SENSING; SPECTRAL ANALYSIS; VARIANCE ANALYSIS; VEGETABLE OIL;

ELAEIS; GANODERMA;

EID: 82055192137     PISSN: 01431161     EISSN: 13665901     Source Type: Journal    
DOI: 10.1080/01431161.2010.519003     Document Type: Article

References (49)

1. BARANOSKI, G.V.G. and ROKNE, J.G., 2005, A practical approach for estimating the red edge position of plant leaf reflectance. International Journal of Remote Sensing, 26, pp. 503-721.
2. BRUZZONE, L. and SERPICO, S.B., 2000,Atechnique for feature selection inmulticlass problems. International Journal of Remote Sensing, 21, pp. 549-563.
3. CARTER, G.A., 1994, Ratios of leaf reflectance in narrow wavebands as indicators of plant stress. International Journal of Remote Sensing, 15, pp. 697-703.
4. CARTER, G.A. and KNAPP, A.K., 2001, Leaf optical properties in higher plants: linking spectral characteristics to stress and chlorophyll concentration. American Journal of Botany, 88, pp. 677-684.
5. CHEN, X., WARNER, T.A. and CAMPAGNA, D.J., 2007, Integrating visible, near-infrared and short wave infrared hyperspectral and multispectral thermal imagery for geologic mapping: simulated data. International Journal of Remote Sensing, 28, pp. 2415-2430.
6. CHO, M.A. and SKIDMORE, A.K., 2006, A new technique for extracting the red edge position from hyperspectral data: the linear extrapolation method. Remote Sensing of Environment, 101, pp. 181-193.
7. CIBULA, W.G., ZETKA, E.F. and RICHMAN, D.L., 1992, Response of thematic bands to plant water stress. International Journal of Remote Sensing, 13, pp. 1869-1880.
8. CLARK, M.L., ROBERTS, D.R. and CLARK, D.B., 2005, Hyperspectral discrimination of tropical rain forest trees species at leaf to crown scales. Remote Sensing of Environment, 96, pp. 375-398.
9. CORLEY, R.H.V. and TINKER, P.B., 2003, The Oil Palm, 4th ed., pp. 25-26 (Oxford: Blackwell Science).
10. DAWSON, T.P. and CURRAN, P.J., 1998, A new technique for interpolating the reflectance of red edge position. International Journal of Remote Sensing, 19, pp. 2133-2139.
11. DELALIEUX, S., AARDT, J.V., KEULEMANS, W., SCHEREVENS, E. and COPPIN, P., 2007, Detection of biotic stress (Venturia Inaequalis) in apple trees using hyperspectral data: non parametric statistical approaches and physiological implications. European Journal of Agronomy, 27, pp. 130-143.
12. Demetriades-Shah, T.H., STEVEN, M.D. and CLARK, J.A., 1990, High resolution derivative spectra in remote sensing. Remote Sensing of Environment, 33, pp. 55-64.
13. FLOOD, J., BRIDGE, P.D. and HOLDERNESS, M., Eds., 2000, Preface. In Ganoderma Disease in Perennial Crops, pp. 47-69 (Wallingford: CABI).
14. FOODY, G.M., 2002, Status of land cover classification accuracy assessment. Remote Sensing of Environment, 80, pp. 185-201.
15. FUNG, T., YAN, H.F. and SIU, W.L., 2003, Band selection using hyperspectral data of subtropical tree species. Geocarto International, 18, pp. 3-11.
16. GAGNON, P., SCHEIBLING, R.E., JONES, W. and TULLY, D., 2007, The role of digital bathymetry in mapping shallow marine vegetation from hyperspectral image data. International Journal of Remote Sensing, 29, pp. 879-904.
17. HELD, A., TICEHURST, C., LYMBURNER, L. and WILLIAMS, N., 2003, High resolution mapping of tropical mangrove ecosystems using hyperspectral and radar remote sensing. International Journal of Remote Sensing, 24, pp. 2739-2759.
18. IDRIS, A.S., KHUSAIRI, D., ARIFFIN, D. and BASRI, M.W., 2006, Technique for inoculation of oil palm germinated seeds with Ganoderma. MPOB Information Series, 314, pp. 1-4.
19. ISMAIL, R., MUTANGA, O. and AHMAD, F., 2008, Discriminating Sirex noctilio attack in pine forest plantations in South Africa using high spectral resolution data. In Hyperspectral and Remote Sensing of Tropical and Subtropical Forests, M. Kalacska and G.A. Sanchez-Azofeifa (Eds.), pp. 161-174 (New York: Taylor & Francis).
20. JENSEN, J.R., 2005, Introductory Digital Image Processing: A Remote Sensing Perspective, 3rd ed., pp. 372-373 (Upper Saddle River, NJ: Pearson Prentice Hall).
21. JOLLINEAU, M.Y. and HOWARTH, P.J., 2008, Mapping an inland wetland complex using hyperspectral imagery. International Journal of Remote Sensing, 29, pp. 3609-3631.
22. KALACSKA, M., BOHLMAN, S., Sanchez-Azofeifa, G.M., Castro-Esau, K. and CAELLI, T., 2007, Hyperspectral discrimination of tropical dry forest lianas and trees: comparative data reduction approaches at the leaf and canopy levels. Remote Sensing of Environment, 109, pp. 406-415.
23. LANDGREBE, D.A., 2003, Signal Theory Methods in Multispectral Remote Sensing, pp. 119-122 (Hoboken, NJ: Wiley-Interscience).
24. LELONG, C.C.D., LANORE, M. and CALIMAN, J.P., 2006, Evaluation of hyperspectral remote sensing relevance to estimate oil palm trees nutrition status. In Second Recent Advances in Quantitative Remote Sensing (RAQRS'II), A. Sobrino José (Ed.), Auditori de Torrent, Spain, 25-29 September 2006 (Valencia, Spain: Universitat de Valencia), pp. 147-152.
25. LI, X., HE, Y. and FANG, H., 2007, Non-destructive discrimination of Chinese bayberry varieties using Vis/NIR spectroscopy. Journal of Food Engineering, 81, pp. 357-363.
26. LIU, L., WANG, J., HUANG, W., ZHAO, C., ZHANG, B. and TONG, Q., 2004, Estimating winter wheat plant water content using red edge parameter. International Journal of Remote Sensing, 25, pp. 3331-3342.
27. LIU, Q., LIU, G., HUANG, C. and CHU, X., 2005, The primary studies on the relationships between soil properties and canopy field spectra of rice in the Liaohe River Delta, P. R. China. In Geoscience and Remote Sensing Symposium, 2005, 25-29 July 2005, pp. 4447-4450.
28. LU, S., OKI, K., SHIMIZU, Y. and OMASA, K., 2007, Comparison between several feature extraction/classification methods for mapping complicated agricultural land use patches using airborne hyperspectral data. International Journal of Remote Sensing, 28, pp. 963-984.
29. MALTHUS, T.J. and MADEIRA, A.C., 1993, High resolution spectroradiometry: spectral reflectance of field bean leaves infected by Botrytis Fabae. Remote Sensing Environment, 45, pp. 107-116.
30. MILLER, R.N.G., HOLDERNESS, M., BRIDGE, P.D. and ZAKARIA, M.H., 1999, Genetic diversity of Ganoderma on oil palm planting. Plant Pathology, 48, pp. 595-603.
31. MIRIK, M., MICHELS, G.J. JR., KASSYMZHANOVA, S., ELLIOT, N.C. and CATANA, V., 2006, Spectral sensing of aphid (Hemiptera: Aphididae) density using field spectrometry and radiometry. Turkish Journal of Agriculture and Forestry, 30, pp. 421-428.
32. MUTANGA, O., SKIDMORE, A.K. and VAN WIEREN, S., 2003, Discriminating tropical grass canopies (Cenchrus ciliaris) grown under different nitrogen treatments using spectroradiometry. ISPRS Journal of Photogrammetry and Remote Sensing, 57, pp. 263-272.
33. NAIDU, R.A., PERRY, E.M., PIERCE, F.J. and MEKURIA, T., 2009, The potential of spectral reflectance technique for the detection of Grapevine leafroll-associated virus-3 in two red-berried wine grape cultivars. Computers and Electronics in Agriculture, 66, pp. 38-45.
34. OSBORNE, S.D., JORDAN, R.B. and KUNNEMEYER, R., 1997, Method of wavelength selection for partial least squares. The Analyst, 122, pp. 1531-1537.
35. PATERSON, R.R.M., HOLDERNESS, M., KELLEY, J., MILLER, R. and O'GRADY, E., 2000, In vitro biodegradation of oil-palm stem using macroscopic fungi from South-East Asia: a preliminary investigation. In Ganoderma Diseases of Perennial Crops, J. Flood, P.D. Bridge and M. Holderness (Eds.), pp. 129-138 (Wallingford: CABI).
36. POST, C.J., DEGLORIA, S.D., CHERNEY, J.H. and MIKHAILOVA, E.A., 2007, Spectral measurements of Alfalfa/Grass fields related to forage properties and species composition. Journal of Plant Nutrition, 30, pp. 1779-1789.
37. RICHARDS, J.A. and JIA, X., 1999, Remote Sensing Digital Image Analysis (Berlin: Springer).
38. SALEM, F., KAFATOS, M., EL-GHAZAWI, T., GOMEZ, R. and YANG, R., 2005, Hyperspectral image assessment of oil-contaminated wetland. International Journal of Remote Sensing, 26, pp. 811-821.
39. SCHMIDT, K.S. and SKIDMORE, A.K., 2002, Spectral discrimination of vegetation types in a coastal wetland. Remote Sensing of Environment, 85, pp. 92-108.
40. SCHMIDT, K.S. and SKIDMORE, A.K., 2004, Smoothing vegetation spectra with wavelets. International Journal of Remote Sensing, 25, pp. 1167-1184.
41. SMITH, K.L., STEVEN, M.D. and COLLS, J.J., 2004, Use of hyperspectral derivative ratios in the red-edge region to identify plant stress responses to gas leaks. Remote Sensing of Environment, 92, pp. 207-217.
42. VAIPHASA, C., ONGSOMWANG, S., VAIPHASA, T. and SKIDMORE, A.K., 2005, Tropical mangrove species discrimination using hyperspectral data: a laboratory study. Estuarine Coastal and Shelf Science, 65, pp. 371-379.
43. VAIPHASA, C., SKIDMORE, A.K., DE BOER, W.F. and VAIPHASA, T., 2007, A hyperspectral band selector for plant species discrimination. ISPRS Journal of Photogrammetry and Remote Sensing, 62, pp. 225-235.
44. WANG, L. and SOUSA, W.P., 2009, Distinguishing mangrove species with laboratory measurements of hyperspectral leaf reflectance. International Journal of Remote Sensing, 30, pp. 1267-1281.
45. YANG, C., EVERITT, J.H. and JOHNSON, H.B., 2009, Applying image transformation and classification techniques to airborne hyperspectral imagery for mapping Ashe juniper infestations. International Journal of Remote Sensing, 30, pp. 2741-2758.
46. YANG, X. (Ed.), 2008, Remote Sensing and Geospatial Technologies for Coastal Ecosystem Assessment and Management (Berlin: Springer-Verlag).
47. Zarco-Tejada, P.J., MLLER, J.R., MORALES, A., BERJON, A. and AGUERA, J., 2004, Hyperspectral indices and model simulation for chlorophyll estimation in open-canopy tree crops. Remote Sensing of Environment, 90, pp. 463-476.
48. ZHANG, M., QIN, Z., LIU, X. and USTIN, S.L., 2003, Detection of stress in tomatoes induced by blight disease in California, USA, using hyperspectral remote sensing. International Journal of Applied Earth Observation and Geoinformation, 4, pp. 295-310.
49. Zhan-Yu, L., Jing-Feng, H. and Ring-Xiang, T., 2008, Characterizing and estimating fungal disease severity of rice brown spot with hyperspectral reflectance data. Rice Science, 15, pp. 232-242.