| Summary: | ESTIMATING ABOVE GROUND BIOMASS OF TEAK (Tectona grandis Linn.f) FOREST PANTATIONS USING DIGITAL DATA ANALYSIS OF LANDSAT 7 ETM+ IN BKPH PASARSORE, KPH CEPU, PERUM PERHUTANI UNIT I, CENTRAL JAVA
Ris Hadi Purwanto1', Imsak Sukamdi1', Agus Wuryanto2)
1}Jurusan Management Hutan, Fakultas Kehutanan, Univeritas Gadjah Mada 2)Peneliti Balai Penelitian Kehutanan Surakarta Email: risuhadi@vahoo.com.Telp. 081328269635
ABSTRACT
Estimation of forest biomass is necessary for studying carbon cycles, nutrient allocation, and fuel accumulation in terrestrial ecosystem. Forest biomass also provide the important information in anticipating the level of potency absorption of C02(gaS) and in certain age biomass can be utilized to estimate the productivity of forest area. Teak forest plantations in BKPH Pasarsore, KPH Cepu were being chosen of the research due to consider available data of Landsat 7 ETM+ and the tree represent one of the important wood commodity production both domestic and export orientation. The goal of the research is to compile the allometric equation of planted teak forest biomass using digital data analysis of Landsat 7 ETM+ and than conducted by an obstetrical estimation of planted teak forest biomass by use the equation.
Remote sensing represents the manner for estimating forest biomass and the ability of the forest to permeating carbon in wide area. The biomass estimate using analysis of image Landsat 7 ETM+ conducted by choosing mathematical transformation which having a good regression-correlation values between biomass in field with the single spectral channel value and the transformation of vegetation index at Landsat 7 ETM+ such as normalized difference vegetation index (NDVI), ratio vegetation index (RVI), transformed vegetation index (TVI), vegetation index faster (VIF), perpendicular vegetation index (PVI), and green vegetation index (GVI). In order to scale biomass estimates to the landscape level, the estimates have to be linked with various vegetation indices derived by remote sensing data.
Based on correlation regression analysis, the results showed the mathematical transformation of PVI has the strongest relation with biomass and it relevant to signalize the biomass aspect. The regression equation from the mathematical transformation is 0.000034x 7 where yrepresent the level of biomass estimation and x represent the spectral value scale. The correlation coefficient (R) from this mathematical transformation equal to 0.8301. It was showing a strong relation between PVI with the estimation of biomass. While the value of coefficient determination (R2) equal to 0.689, it was meaning 68.9% from biomass can be explained by variability of the spectral PVI value. After all the equation used in estimating planted teak forest biomass in BKPH Pasarsore, KPH Cepu. From the calculation, the biomass estimation in BKPH Pasarsore equal to 163.902 ton/ha. It means equivalent to carbon stored as 81.951 ton/ha.
Keyword: biomass, planted teak forest, remote sensing, digital data of Landsat 7 ETM+
Jurnal Manajemen Hutan
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