Prediction models for estimating the area, volume, and age of rubber (Hevea brasiliensis) plantations in Malaysia using Landsat TM data

Rubber tree (Hevea brasiliensis (Wild. ex Adr. de Juss.) Muell Arg.) plantations in Malaysia are important sources of natural rubber and wood products. Effective management and appropriate policy for these resources requires reliable forecasts of resource availability. However, to achieve these goals, effective inventories are required. This promoted research into supplementing ground-based survey methods with satellite remote sensing information. A study was conducted to investigate the relationship between Landsat Thematic Mapper (TM) data and rubber stand parameters and to develop and evaluate models for estimating area, volume, and age of rubber plantations. Statistically significant models for estimating volume and age of rubber stands were obtained. For volume models, the R-2 values were all higher than 0.70 and standard error of the estimate (SEE) values were lower than 54 m(3)/ha. R-2 and SEE values achieved from age models evaluated ranged from 0.34-0.64 and 6.4-8.2 years. A logistic regression model produced classifications with an accuracy of 87% for predicting the presence of rubber plantations. Thus, Landsat TM provides an acceptable data source for estimating wood volume and stand age, and for predicting the presence of rubber plantations.