Development of Merchantable Timber Volume Estimation of Pinus caribaea Plantations using Multi-Spectral Satellite Images

The use of the multi- spectral remote sensing in relation to determination of parameters in the forestry is increasing globally. According to that, remote sensing is widely used to estimate above ground biomass, merchantable volume, carbon content and leaf area index in different vegetation systems.

Though there are many ways to estimate merchantable volume of plantation forest species, and filed inventory data is the most common. However, field inventory methods are more costly field consuming methods. Therefore, this study was initiated to develop merchantable volume prediction models using satellite image spectral response techniques for Pinus caribaea plantation at Mid-country wet zone of Sri Lanka.

P. caribaea is lightwood plantation species introduced to Sri Lanka and it was planted in marginal tea lands in mid and hill country. Initial site verification was done by ground truth GPS data with overlaying on unsupervised Landsat ETM+ image and demarcated the pine plantations at the Hantana region. Selected pine plantation was further classified into three different strata and six to nine plots were (15 m x 15 m) established in each stratum to estimate volume. The total tree height (m) and diameter at breast height (DBH in cm) of individual trees inside the plot were taken and allometric equations (Forest Inventory Manual, 1996) were used to estimate merchantable volume in 23 plots.

Three vegetation indices Normalized Difference Vegetation Index was developed for research site using Landsat ETM+ satellite image and correlated with the estimated merchantable volume and develop linear regression model.

Results showed that the vegetation index of NDVI derived from satellite images is significantly correlated with calculated above-ground merchantable volume of P. caribaea. Finally, merchantable volume map was prepared for the P. caribaea plantation using the Satellite Image Processing and GIS based Software. The highest volume was observed in plot number 2 (12.24m³/plot) and the lowest (4.972m³/plot) and average volume is 400.646 m³/ha.