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Poster Session 3
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Application of optical remote sensing technology for oil palm management
Conclusions
This study has investigated the usefulness of remote sensing for estimating oil palm age and leaf area index (LAI) using Landsat TM data and its indices in the Malaysian oil palm plantation system. The following summaries can be made from this study:
Figure3.1: The magnitude of the contribution of the oil palm canopy and soil
- Middle Infrared (MIR) wavebands of Landsat TM (band 5 and 7) for both estates contained considerable discriminating power and provide stronger relationships with oil palm age classes than data acquired in visible and near infrared wavebands. Similarly, it was found that the inclusion of MIR wavebands in multiple linear regression model 1 improves statistical significance. When all Landsat TM wavebands were included in the multiple regression analysis, band 5, 7 and 1 (Balau Estate ) and band 5, 4, 3, 1 and 7 (Tuan Mee Estate) were found to be statistically significant as predictor variables for oil palm age class estimation.
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Balau Estate had less relative error in oil palm age estimates in all models (model 1, 2 and 3) than Tuan Mee Estate. The regression analysis of oil palm age classes of Tuan Mee Estate needed more predictor variables compared to Balau Estate. This is believed to be due to the wide range of oil palm planting density and the terrain complexity of Tuan Mee Estate.
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Although the main aim of this study is to estimate oil palm age classes from spectral Landsat TM wavebands it was found that spectral indices could better discriminate oil palm age classes. Multiple regression models including indices SI, BIO and AVI with Landsat TM bands produced less error in age estimates at Tuan Mee.. They are recommended for plantations with similar complex terrain and a wide range of planting densities.
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Landsat TM bands and its indices in conjunction with GIS information can provide a reasonably accurate estimation of oil palm age at estate level. The planting density predictor variable improved the error of oil palm age estimation for both estates. Planting density can influence canopy development and, especially the age at which the oil palm canopy starts to close. Higher planting density causes canopy closure at an earlier age so that the regression line (constant) suggested should be steeper. The planting density variable should be investigated by developing separate regression models for low and high density blocks.
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The approach developed in the present study agrees with the view that the all features of the biosphere cannot be measured directly from satellite data. However by using an underlying functional relationship between variable under investigation and secondary variable that can be measured by satellite sensor, a model can be developed that predicts the desired information.
References
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- CORLEY R.H.V.,(1973) Effects of plant density on growth and yeild of oil palm. Expl. Agric, 9: 169-180.
- JOHNSTON R. J., (1978), Multivariate statistic analysis in geography (London: Longman).
- MCMORROW J.M., 1995. Relation of oil palm spectral respone to stand age. International Journal of Remote Sensing, 16, 3203-3209
- GALLEGO 1995 SAMPLING PROCEDURES, FRANCE GDTA 25-65
- MCWILLIAM A. L. C., ROBERTS , J. M., BACRAL., O. M. R., LETITAO, M. V. B. R., DE COATA, A. C. L., MAITELL, G. T., AND LAMPARONI, C. A. G. P., 1993, Leaf area indices and above-ground biomass of terra firme rain forest and adjacent clearings in Amazonia. Functional Ecology, 71, 310-317
- PRICE J. C., and BAUSCH W. C., 1995 Leaf area estimation from visible and near infrared reflectance data. Remote Sensing and Environment. 52: 55-65.
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