Development of Fast-Growing Tree Biomass Allometric Equations and Biomass Estimation Using Remote Sensing Data

Abstract

Biomass has had an essential role in the energy sector of the world due to applications in bioenergy. Eucalyptus, Acacia and Leucaena are fast-growing trees with high potential in the renewable energy system in Thailand. However, there are few studies on related topics such as biomass estimation, estimating biomass in large plantation area and analysis of energy and economic for woodchips production. The objectives of the study were as follows: (i) to study above-ground biomass dynamics accumulation and allometric equation development of Eucalyptus, Acacia and Leucaena, (ii) to study land use classification and estimating above-ground biomass models development using remote sensing data and (iii) to study energy and economic analysis of Eucalyptus plantation for woodchips production. This research study was divided into four parts. Fist, Above-ground biomass allometric equation of fast-growing tree. The study plantation area is 960 ha in Lampang and Lamphun province, Northern Thailand. The planted density is 1666 trees ha-1. A total of 291 trees for destructive sampling were randomly selected from thirteen sites. Allometric biomass equations for tree components are developed by regressing the diameter at breast height (DBH), tree height (H) and a combination of these. The results show that total AGB estimation using the combination of DBH and H was more accurate than using single variables for E. camaldulensis and A. hybrid, but DBH and H alone showed the best fit for L. leucocephala and E. camaldulensis coppice, respectively. However, using only DBH as a predictor variable was more cost-effective and less timeconsuming,while still being sufficiently accurate, with R2 adj ≥ 0.743 for all three species. The total AGB production of E. camaldulensis was higher than A. hybrid by about 28.5% and L. leucocephala by about 82.2% at 5 years of age. Moreover, for E. camaldulensis, the advantage is that it has a sprouting ability after harvest. The largest proportion of AGB for all three species is the stem, amounting to about 75-79% at mature stands, followed by bark, branches and leaves, respectively. Regarding the AGB productivity of stemwood at 3 years of age, E. camaldulensis was higher than L. leucocephala, A. hybrid and E. camaldulensis coppice, respectively, and at 5 years E. camaldulensis still exhibited greater stemwood production than A. hybrid and L. leucocephala. Second, Land use and land cover classification using remote sensing data. The THEOS MS image of Kokha district, Lampang province was investigated using supervised classification with algorithms of MLC and unsupervised classification with ISODATA were conducted under EDAS imagine. The result show that THEOS MS image can be utilized to LU/LC classification with supervised and unsupervised classification. LU/LC classification resulting from MS image with MLC algorithm indicated higher overall accuracy (OA = 78.95%) and higher kappa hat coefficient of agreement (k ̂= 72.58%) than ISODATA algorithm. Total area of LU/LC classification was approximately 513 km2 both MLC and ISODATA classification. The largest area of LU/LC classification with MLC was forest land followed by paddy field, fast-growing tree, field crops, orchard and perennial, urban and build-up area, abandoned land and water body, respectively. Abandoned land area of 12.70 km2 resulting from LU/LC classification use to predated biomass production. The prediction results of biomass production found that total AGB production of E. camaldulensis was 79,737 Mg, A. hybrid was 62,062 Mg and L. leucocephala was 43,758 Mg at 5 years of plantation age. Third, Biomass estimation using remote sensing data. This research part aims to develop a model for estimating AGB for Eucalyptus plantation located in the Sahacogen Green Co., Ltd., in Lampang province, Thailand using remotely sensed data. The AGB value was coupled which calculated from field measurement (tree height, H and diameter at breast height, DBH) using the allometric equation with various vegetation indices. The 55 sample plots and 5 vegetation indices derived from THEOS were used to develop a model for estimating AGB of Eucalyptus plantation. After discussing the results of the investigation, the Transformed Normalized Difference Vegetation Index (TNDVI) showed a robust correlation with AGB compared to other indices (r = 0.833). Based on stepwise linear regression between AGB and 5 vegetation indices demonstrated TNDVI was only selected while the other indices were eliminated because their relationship was not significant. The developed model R2 was 0.693, adjusted R2 was 0.684 and SEE was 12.41 Mg ha-1. The relationship between observed AGB and predicted AGB from the THEOS model of Eucalyptus plantation with R2 of 0.742 and RMSE of 9.63 Mg ha-1 indicated that remotely sensed data from THEOS can be useful for AGB estimation with high accuracy. Fourth, Energy and economic analysis of woodchips production. This part presents energy and economic analysis of Eucalyptus plantation for woodchips production as energy crop in North Thailand. The selected site was Sahacogen Green Co.,Ltd. plantation area covering Lamphun and Lampang province. The investigated data of energy and economy were based on the data from experimental plantation and recorded data from the company, which included seedling, soil preparation and conditioning, cultivation, stump removal and soil recovery, harvesting and transportation. Eucalyptus plantation has been established since 2008 with a 2.0 3.0 m2 spacing. It was managed as a Short Rotation Coppice (SRC) which was first harvested at the 4th year following by 3 rotations of every 3 years. Stumps were removed and soil recovery were counted at the end of 13th years. For biomass harvesting, saw cutting machine, tractor and Vermeer BC1000XL were used for woodchips production in the field at the end of each rotation period. Woodchips were transferred by truck to the steam power plant warehouse. The results of evaluation showed that woodchips production was characteristics of a highly efficient energy system with Cumulative Energy Demand (CED) 22.34 MJ/GJ of biomass and Net Energy Ratio (NER) of 44.76. The monetary values refer to cash inflows/outflow accomplished at the end of the cultivation period (2021) when assuming the woodchips price of 31.25 USD/t 40 wt% moisture, discount rate of 5.0% and inflation rate of 0.0% for 13 years on average indicating 1,828.40 USD/ha which is equivalent to 2.46 USD/GJ. The economy of woodchips production project in terms of Net Present Values (NPV) andInternal Rates of Return (IRR) was -159.18 USD/ha and 3.94%, respectively.