Pengeluaran primer bersih kawasan hutan hujan tropika menggunakan data Aster
Rapid development in industrialisation, urbanisation and agricultural sectors have contributed to an increased in green house gases in the atmosphere, particularly carbon dioxide (CO2). An increased in CO2 concentration in the atmosphere is considered as one of the main factors that caused the pheno...
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| Main Author: | |
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| Format: | Thesis |
| Language: | English |
| Published: |
2009
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/12392/1/MohdAzahariFaidiMFKSG2009.pdf http://eprints.utm.my/id/eprint/12392/ |
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| Summary: | Rapid development in industrialisation, urbanisation and agricultural sectors have contributed to an increased in green house gases in the atmosphere, particularly carbon dioxide (CO2). An increased in CO2 concentration in the atmosphere is considered as one of the main factors that caused the phenomena of global warming and climate change. Thus, knowledge pertaining the existence, concentration and losses of CO2 in the atmosphere are very important. This is very useful for ensuring the concentrations of CO2 in the atmosphere remain in the state of balance. One of the ways to monitor the content of CO2 in the atmosphere is through the measurement of the rate of absorptions of CO2 by vegetation. This can be carried out either by determining the biomass or the Net Primary Productivity (NPP) of the vegetation. The main objective of this study is to evaluate the Eco-Physiological Approach that is one of the approaches used to determine NPP using remote sensing data. ASTER satellite data with the spatial resolution of 15 meter and the spectral range of 0.52 ?m of 0.86 ?m were used for the evaluation of four models from the Eco-Physiological approach. The evaluation of these models were based on the accuracy of the measured NPP values for three types of vegetation such as forest, oil palm and rubber in the vicinity of Pasoh Forest Reserve in Negeri Sembilan. An assessment was made by determining the Coefficient of Variation (CV) to calculate error and also through comparison with results from previous studies. This study showed that Global Production Efficiency Model (GLOPEM) gives the highest accuracy of NPP for forest and rubber with CV of 4.7% and 3.0% respectively. While Carnegie Ames Stanford Approach Model (CASA) is appropriate for oil palm with CV of 7.85%. Values of NPP for all the three vegetation types obtained using VPM and C-Fix models showed a very low accuracy. As a whole, the range of NPP obtained for forest, oil palm and rubber are within the range of 451.58 gCm-2 yr-1 to 3042.20 gCm-2 yr-1. Average values of NPP for forest, oil palm and rubber is 2812.5 gCm-2 yr-1, 2377.0 gCm-2 yr-1 and 2864.6 gCm-2 yr-1 respectively. |
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