Relationship Between Above Ground Live Biomass and Satellite Image Spectral Responses ( Landsat ETM + ) of Pinus caribaea Morelet at Lower Hantana Region in Sri Lanka

Terrestrial carbon sequestration in woody biomass has received attention as a promising adaptation mechanism in mitigating global warming. Developing countries could trade these sequestered carbon with developed countries. To facilitate this type of projects, precise quantification of sequestered carbon in vegetations is essential. Though, many attempts have already been made to estimate vegetation biomass, no precise prediction models are developed for tropical ecosystems. Therefore, this study was initiated to develop carbon sequestration models using satellite image spectral response techniques for Pinus caribaea Morelet plantation at mid-country Wet zone of Sri Lanka. Using Landsat ETM+ image, pine plantations at the Hantana region were categorized in to three spectral strata. Six to nine plots (30 m × 30 m) were demarcated from each stratum to estimate biomass. Plant height and diameter at breast height (DBH) of individual trees inside the plot were measured. Three vegetation indices, Normalized Difference Vegetation Index (NDVI), Ratio Vegetation Index (RVI) and Difference Vegetation Index (DVI)) were developed for research site using Landsat ETM+ satellite image and correlated with the estimated biomass. Results showed that the vegetation index of NDVI derived from satellite images was significantly correlated with calculated above ground biomass of P. caribaea than RVI and DVI. However, other two vegetation indices could also be used as precise carbon sequestration models to predict above ground biomass for P. caribaea. INTRODUCTION Over the years, tropical ecosystems became one of the major global crises due to continuous, indiscriminate, unprecedented and extensive deforestation all over the world. Loss of biodiversity, land degradation and global environmental changes are the major effects of deforestation. In addition, forest fragmentation and habitat degradation have further aggravated the impact on wildlife habitats, watersheds and hydrological cycle. The world is aware that carbon dioxide (CO2) emissions particularly those from fossil fuel burning and deforestation are increasing and causing global warming (NASA, 2001). 1 Department of Crop Science, Faculty of Agriculture, University of Peradeniya, Peradeniya, Sri Lanka. 2 Department of Agricultural Engineering, Faculty of Agriculture, University of Peradeniya, Peradeniya, Sri Lanka. Biomass Prediction Using Satellite Images However, terrestrial carbon sequestration in above ground woody biomass has received attention as a promising course in an immediate attempt to mitigate global warming. Among the carbon sequestration techniques identified, sequestration through vegetation plays a significant role. Green plants through photosynthesis fix atmospheric CO2 back to biomass. In this manner, plantation forests are playing a major role to carbon stocking while reducing the global warming. Biomass estimates provide means of calculating the amount of carbon dioxide that could be removed/fixed from the atmosphere by re-growing vegetation. There are many attempts made to estimate vegetation biomass, such as the use of existing forest inventory, which is the key method. Many researchers have developed various methods for the quantification of sequestered carbon. Traditional inventory of forest parameters based on fieldworks is often difficult, costly and time consuming to conduct in large areas. Remote sensing may be the only feasible way to acquire forest stand parameter information at a reasonable cost with acceptable accuracy. Advanced new remote sensing techniques such as, multi-sensor data fusion, increase spatial and spectral resolution and integration with Geographical Information Systems (GIS) make remotely sensed data, the primary source for many forestry applications. Among them, extraction of forest stands parameters through correlation or regression analysis to examine relationship between spectral response and structural factors of forest such as basal area, biomass, crown closer and vegetation density (Namayanga, 2002), hold more promise. Remotely sensed data are comprehensive responses of the vegetation stand structure, vegetation density and vegetation species composition. Different forest stand structures have different reflectance and texture patterns in various wavelengths. Therefore, much more remote sensing research focused on the extraction of forest stand parameters through correlation or regression analysis to examine relationship between spectral response and structural factors of forests (Dengsheng et al., 2004) are needed. The objective of this study was to identify the relationship between above ground live biomass of Pinus caribaea Morelet in Hantana foothills by using spectral responses of Landsat ETM+ satellite images. MATERIALS AND METHODS Data, materials and other information The primary data used in the study was Landsat ETM+ image acquired in 2000. Digital Elevation Model (DEM) was derived from SRTM (90 m resolutions) data and site verification was done using the 1: 50,000 scaled topographic maps. To demarcate plots and geo-rectification of satellite images, Trimble GeoXT differential Global Positioning System (GPS) was used. Base station data were also used for differential corrections of GPS coordinates to achieve a high accuracy of locations. Research site P. caribaea plantation forest of the University of Peradeniya is located in the foothills of the Hantana mountain range which lies at an altitude between 1000 and 1500 m at msl and between 7 13′ 00′′ N & 7 16′ 00′′ N and 80 36′ 00′′ E & 80 38′ 00′′ E geographical coordinates. Figure 1 shows the location of the research site. Gunawardena, Nissanka & Dayawansa Image processing and selection of sample locations Geometrical rectification and radiometric and atmospheric correction of remotely sensed data are required for many applications. The importance of accurate geometric correction is obvious due to the image data that are often related to the ground truth data (Lu et al., 2004). Acquired image was geometrically rectified into UTM (Universal Transverse Mercator) projection and datum WGS 84 (zone 44) using ground control points obtained through GPS together with 1: 50,000 topographic maps. All images that were collected had good quality and were free of clouds. Reserach Site Kandy District