Estimation of above ground forest biomass in Ulu Padas area, Sabah using IKONOS-2 image
Quantifying biomass loss and carbon emission from deforestation and degradation in developing countries is important to combat climate change. We developed allometric models from an IKONOS-2 image to predict DBH that leads to aboveground biomass estimation (AGB) for primary and degraded forests. The...
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| Format: | Thesis |
| Language: | English English |
| Published: |
2014
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| Online Access: | https://eprints.ums.edu.my/id/eprint/42805/1/24%20PAGES.pdf https://eprints.ums.edu.my/id/eprint/42805/2/FULLTEXT.pdf https://eprints.ums.edu.my/id/eprint/42805/ |
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| Summary: | Quantifying biomass loss and carbon emission from deforestation and degradation in developing countries is important to combat climate change. We developed allometric models from an IKONOS-2 image to predict DBH that leads to aboveground biomass estimation (AGB) for primary and degraded forests. The IKONOS image was preprocessed with dark object subtraction and topographic effect correction prior to segmentation using the watershed method. Overall, the segmentation was 64% accurate. Crown detection percent was negatively influenced by tree density. Correlation analysis showed that satellite-based crown area had the highest correlations with DBH for primary and degraded forests. We developed the DBH estimation allometric equations for primary and degraded forests. The DBH estimation models explained 76% and 66% of the variances for primary and degraded forests, respectively. Averagely, the predicted DBH was almost identical to the observed DBH for intact forest and was slightly different for degraded forest. The estimated AGB was also very similar to the observed AGB for both forest types. Overall, this method can potentially be applied to estimate AGB over a relatively large and remote tropical forest in Northern Borneo. |
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