Linear regression modelling for the estimation of oil palm age from Landsat TM
This paper investigates the accuracy with which the age since field planting of oil palm (Elaeis guineensis Jacq.) can be estimated from Landsat Thematic Mapper (TM) radiance at pixel and stand scales. The study site, a commercial plantation 30 km south-east of Kuala Lumpur in Selangor, Malaysia, consisted of even-aged blocks from 4 to 21 years old. Spectral data were the six reflective TM bands and three spectral indices. Nonlinear negative relationships between spectral variables and age are compared to published trends in leaf area, stem height and per cent canopy cover for oil palm and other tree plantations. Correlation coefficients between log age and log radiance are moderate and highly significant (p<0.01) for bands 2-5 and 7 (-0.214 to-0.776) at the pixel scale, and increase at the stand scale (r2=0.985 for log band 5, p<0.01). Relationships are strongest for the mid-infrared bands, especially band 5 (r2=0.585, p <0.01) and the infrared index (IRI), a normalized difference index of bands 4 and 5 (r2= 0.48, p<0.01). Direct and inverse linear regression models for log age with log band and log age with IRI squared (IRIsq) were constructed at both scales. Equivalent age was estimated from the models using independent test sets for differing scales and degrees of aggregation of the age classes. Single age classes cannot be estimated accurately at the pixel or stand scales; the lowest RMS error was obtained from the direct model using all bands (RMS error=3.9 years at pixel scale, 2.7 at stand scale). A posteriori aggregation into generalized age classes (<5, 6-10, 11-15, 16-21 years) improved the RMS error but the results were still unacceptably high (2.2, 2.3, 2.7, 6.0 years respectively for direct model 3 using all bands). Acceptable RMS errors down to 0.58 years were obtained for models using IRIsq with generalized age classes developed and applied at the stand scale when variations in ground cover and other variables were averaged out. The spatial pattern of error in equivalent age deserves investigation for precision crop management.