biomass by indirect estimation of biomass through some form of quantitative relationship regression equations between band ratio indices NDVI, GVI etc or
other measures such as direct radiance values per pixel or digital numbers per pixel, with direct measures of biomass or with parameters related directly to
biomass, e.g. leaf area index LAI. The biomass estimation over a large area by using remote sensing and
standwise forest inventory data has been conducted in many regions by using the different multispectral imagery. These regions cover arid area, boreal forest and
tropical forest. Muukkonen and Heiskanen 2006 used ASTER and MODIS satellite data to estimate biomass of boreal forests in southern Finland. Zheng et
al. 2004 used Landsat 7 ETM+ for estimating aboveground biomass of managed
landscape in northern Wisconsin, USA. Murdiyarso and Wasrin 1995 estimated carbon release from tropical forests conversion using remote sensing technique.
The different satellite data for the biomass estimation will give the different estimation result. Therefore, the different accuracy and equation model derived
from the different satellite data will give the important consideration in choosing the appropriate data used.
1.2 Objectives
The objectives of this research are: -
To estimate the above ground tree biomass and carbon stock of forest cover in Lore Lindu National Park by combination of field data
observation, allometric equation and multispectral satellite image. -
To find the equation model between parameter that determines the biomass estimation.
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1.3 Output
- Correlation and Linear Regression equation model of tree biomass and
vegetation index, remote sensing biomass and field biomass -
Normalized Difference Vegetation Index NDVI value using QuickBird satellite image
- Per hectare trees biomass derived from different forest cover type and
multispectral satellite image classification as the reference to estimate the total biomass and carbon stock in sample plot and whole area
- Total trees biomass and carbon stock of whole study area
1.4 Thesis Outline
To accomplish two preceding objectives, several steps will be taken. Firstly, a literature reviews, presented in Chapter 2. It will be conducted to
provide a context for the work performed in this study. The relevance of this work is demonstrated through the examination of several methods in estimating the tree
biomass and carbon stock. The second part of the literature review involves an examination of
biomass and carbon stock, the various method and regression model for estimating tree biomass, the use of remote sensing and different satellite images in
forestry application especially in estimating its properties. Methodology is described in Chapter 3, covering the research time, the
description of study area, technical method and instrument that will use to collect and analysis the data.
In Chapter 4 results are displayed and discussed covering: field data observation, vegetation analysis, forest cover type classification, correlation
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between parameter, model analysis, above ground tree biomass and carbon stock estimation for each forest cover type and whole study area.
Chapter 5 provides the conclusions and recommendations of this study.
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2 II. LITERATURE REVIEW
2.1 Biomass and Carbon Stock
