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All Journal Indonesian Journal of Forestry Research Jurnal Penelitian Hutan dan Konservasi Alam Forum Geografi
Tyas Mutiara Basuki
Forestry Research Institute on Watershed Management
Agriculture, Biological Sciences & Forestry Earth & Planetary Sciences

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CARBON STOCK ASSESSMENT IN PINE FOREST OF KEDUNG BULUS SUB-WATERSHED (GOMBONG DISTRICT) USING REMOTE SENSING AND FOREST INVENTORY DATA Basuki, Tyas Mutiara; Wahyuningrum, Nining
Indonesian Journal of Forestry Research Vol 10, No 1 (2013): Journal of Forestry Research
Publisher : Secretariat of Forestry Research and Development Agency

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Abstract

Carbon stock in tree biomass can be quantified directly by cutting and weighing trees. It is assumed that 50% of the dry weight of biomass consists of carbon. This direct measurement is the most accurate method, however for large areas it is considered time consuming and costly. Remote sensing has been proven to be an important tool for mapping and monitoring carbon stock from landscape to global scale in order to support forest management and policy practices. The study aimed to (1) develop regression models for estimating carbon stock of pine forests using field measurement and remotely sensed data; and (2) quantify soil carbon stock under pine forests using field measurement. The study was conducted in Kedung Bulus sub-watershed, Gombong - Central Java. The derived data from Satellite Probatoire dObservation de la Terre (SPOT) included spectral band 1, 2, 3, and 4, Normalized Differences Vegetation Index (NDVI), and Principle Component Analysis (PCA) images. These data were integrated with field measurement to develop models. Soil samples were collected by augering for every 20 cm until a depth of  100 cm. The potential of  remote sensing to estimate carbon stock was shown by the strong correlation between multiple bands of SPOT (band 2 , 3; band 1, 2, 3; band 1, 3, 4; and band 1, 2, 3, 4) and carbon stock with r = 0.76, PCA (PC1, PC2, PC3) and carbon stock with r = 0.73. The role of pine forest to reduce CO2 in the atmosphere was demonstrated by the amount of carbon in the tree and the soil. Carbon stock in the tree biomass varied from 26 to 206 Mg C ha-1 and in the soil under pine forest ranged from 85 to 194 Mg C ha-1.
LEAF AREA INDEX DERIVED FROM HEMISPHERICAL PHOTOGRAPH AND ITS CORRELATION WITH ABOVE-GROUND FOREST BIOMASS Basuki, Tyas Mutiara
Indonesian Journal of Forestry Research Vol 2, No 1 (2015): Indonesian Journal of Forestry Research
Publisher : Secretariat of Forestry Research and Development Agency

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LEAF AREA INDEX DERIVED FROM HEMISPHERICAL PHOTOGRAPH AND ITS CORRELATION WITH ABOVEGROUND FOREST BIOMASS Basuki, Tyas Mutiara
Indonesian Journal of Forestry Research Vol 2, No 1 (2015): Indonesian Journal of Forestry Research
Publisher : Secretariat of Forestry Research and Development Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20886/ijfr.2015.2.1.%p

Abstract

Leaf area index (LAI) is one of key physical factors in the energy exchange between terrestrial ecosystem and atmosphere. It determines photosynthesis process to produce biomass and plays an important role in performing forest stand reflectance, therefore building relationships between LAI and biomass from field measurement can be used to develop allometric equations for biomass estimation. The purposes of this research are: 1). To develop relationships between diameter at breast height (DBH) and crown biomass (leaves; leaves + twigs + branches;  2).To develop relationships between leaf area index (LAI) and crown biomass; LAI and Total Above-ground Biomass (TAGB). A destructive sampling was conducted to build allometric equations. The DBH measurements from 52 sample plots were used to build relationships between DBH and crown biomass, as well as LAI and crown biomass and also TAGB. A hemispherical photograph was used to record LAI. The research was carried out in East Kalimantan. The results showed that strong coefficient of determinations (r2) were found between natural logarithmic (ln) DBH and crown biomass ranging from 0.77 to 0.93. The correlations (r) between LAI and leaves; leaves+twigs+branches; TAGB were arround 0.75 and the r2 were 0.564; 0.570; and 0.572, respectivelly.  Although LAI measuremnt using hemispherical is considered tedious, however the results are useful for validation of LAI measueremnts using remote sensing techniques. Improvement of r2 between LAI and biomass can be conducted by proper time of LAI measurement, immediately after sunrise or sunset.
CARBON STOCK ASSESSMENT IN PINE FOREST OF KEDUNG BULUS SUB-WATERSHED (GOMBONG DISTRICT) USING REMOTE SENSING AND FOREST INVENTORY DATA Basuki, Tyas Mutiara; Wahyuningrum, Nining
Indonesian Journal of Forestry Research Vol 10, No 1 (2013): Journal of Forestry Research
Publisher : Secretariat of Forestry Research and Development Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20886/ijfr.2013.10.1.21-30

Abstract

Carbon stock in tree biomass can be quantified directly by cutting and weighing trees. It is assumed that 50% of the dry weight of biomass consists of carbon. This direct measurement is the most accurate method, however for large areas it is considered time consuming and costly. Remote sensing has been proven to be an important tool for mapping and monitoring carbon stock from landscape to global scale in order to support forest management and policy practices. The study aimed to (1) develop regression models for estimating carbon stock of pine forests using field measurement and remotely sensed data; and (2) quantify soil carbon stock under pine forests using field measurement. The study was conducted in Kedung Bulus sub-watershed, Gombong - Central Java. The derived data from Satellite Probatoire dObservation de la Terre (SPOT) included spectral band 1, 2, 3, and 4, Normalized Differences Vegetation Index (NDVI), and Principle Component Analysis (PCA) images. These data were integrated with field measurement to develop models. Soil samples were collected by augering for every 20 cm until a depth of  100 cm. The potential of  remote sensing to estimate carbon stock was shown by the strong correlation between multiple bands of SPOT (band 2 , 3; band 1, 2, 3; band 1, 3, 4; and band 1, 2, 3, 4) and carbon stock with r = 0.76, PCA (PC1, PC2, PC3) and carbon stock with r = 0.73. The role of pine forest to reduce CO2 in the atmosphere was demonstrated by the amount of carbon in the tree and the soil. Carbon stock in the tree biomass varied from 26 to 206 Mg C ha-1 and in the soil under pine forest ranged from 85 to 194 Mg C ha-1.
Co-Authors Diah Auliyani Heru Dwi R, Heru Nining Wahyuningrum Rahardyan Nugroho Adi, Rahardyan Nugroho Sukresno Sukresno Wahyu Wisnu Wijaya, Wahyu Wisnu