Mui How Phua

Estimation of biomass of a mountainous tropical forest using Landsat TM data

Estimation of biomass of a mountainous tropical forest using satellite data is an alternative approach to extensive field surveys. However, sampling of the biomass can be expensive, time-consuming, and difficult depending on the nature of field conditions. Instead of directly estimating the biomass from the satellite data when the sample size is small, it is intended to estimate the biomass of the mountainous tropical forest in Kinabalu Park, Sabah, Malaysia, using the well-established biophysical relationship between crown diameter and biomass. Landsat thematic mapper (TM) data are corrected for geometric distortion and are georeferenced to facilitate satellite data extraction. Path radiance for atmospheric correction is derived using the histogram method, and the Minnaert correction approach is employed to correct for topographic effects. Correlation and regression analyses are carried out with the six original bands and several derived satellite variables (several vegetation indices, tasseled cap transformation variables, and coefficients of pattern decomposition). When the sample size of the biomass is small, estimation using a biophysical relationship between the biomass and other structural variable such as crown diameter is more appropriate and reliable. Owing to biomass data availability, the biophysical relationship between biomass and crown diameter can only be established for closed forest. The closed forest is distinguished using percent crown cover, which is estimated from the wetness indicator. Under the closed forest condition, a significant inverse correlation between band 1 and crown diameter is found. Using the biophysical relationship, biomass is then estimated from crown diameter, which is estimated from band 1.

Estimation of Above-Ground Biomass of a Tropical Forest in Northern Borneo Using High-resolution Satellite Image

Abstract Estimating above-ground biomass is important in establishing an applicable methodology of Measurement, Reporting and Verification (MRV) System for Reducing Emissions from Deforestation and Forest Degradation-Plus (REDD+). We developed an estimation model of diameter at breast height (DBH) from IKONOS-2 image that led to above-ground biomass estimation (AGB). The IKONOS image was preprocessed with dark object subtraction and topographic effect correction prior to watershed segmentation for tree crown delineation. Compared to the field observation, the overall segmentation accuracy was 64%. Crown detection percent had a strong negative correlation to tree density. In addition, satellite-based crown area had the highest correlation with the field measured DBH. We then developed the DBH allometric model that explained 74% of the data variance. In average, the estimated DBH was very similar to the measured DBH as well as for AGB. Overall, this method can potentially be applied to estimate AGB over a relatively large and remote tropical forest in Northern Borneo.Key Words: tree crown delineation, biomass estimation, IKONOS-2

Mapping Distribution of Dipterocarpus in East Kalimantan, Indonesia

Dipterocarps (Dipterocarpaceae) is a dominant tree family of tropical rainforest in Southeast Asia. Dipterocarps have been exploited for its timber and disappearing fast in East Kalimantan. In this study, we predicted the distribution of dipterocarpus, one of the main dipterocarps genera, by evaluating its habitat suitability using logistic regression analysis with specimen collection points and environmental factors from GIS data. Current distribution of dipterocarpus was generated by combining the habitat suitability classes with an updated forest cover map. Rainfall, soil type, followed by elevation was the main factors that influence the distribution of dipterocarpus in East Kalimantan. Dipterocarpus can be found in a quarter of the current forest cover, which is highly suitable as habitat of Dipterocarpus.