Estimating biomass in logged tropical forest using L-Band SAR (PALSAR) data and GIS
The use of remote sensing imagery, to some extends geographic information system (GIS), have been identified as the most recent and effective technologies to assess forest biomass. Depending on the approaches and methods employed, estimating biomass by using these technologies sometimes can lead to...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Universiti Kebangsaan Malaysia
2015
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| Online Access: | http://journalarticle.ukm.my/9036/ http://journalarticle.ukm.my/9036/ http://journalarticle.ukm.my/9036/1/02_Hamidan_Omar.pdf |
| Summary: | The use of remote sensing imagery, to some extends geographic information system (GIS), have been identified as the most recent and effective technologies to assess forest biomass. Depending on the approaches and methods employed, estimating biomass by using these technologies sometimes can lead to uncertainties. The study was conducted to investigate appropriate methods for estimating aboveground biomass (AGB) by using synthetic aperture radar (SAR) data. A total of 60187 ha in Dungun Timber Complex (DTC) were selected as the study area. Thirty seven sample plots, measuring 30×30 m were established in early 2012 covering both natural and logged forests. Phase Array Type L-Band SAR (Palsar) images that were acquired in 2010 were used as primary remote sensing input and shapefile polygons comprised logging records was used as supporting information. By using these data, two estimation methods, which were ‘stratify and multiply’ (SM) and ‘direct remote sensing’ (DR) have been adopted and the results were compared. The estimated total AGB were about 20.1 and 22.3 million Mg, from SM and DR methods, respectively. The study found that the images that incorporated texture measures produced more accurate estimates as compared to the images without texture measures. The study suggests that SM method still a viable and reliable technique for quick assessment of AGB in a large area. The DR method is also relevant provided that an appropriate type and processing techniques of SAR data are utilized. |
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