Development of allometric model for mixed and shorea tree species through synergistic analysis of remote sensing data / Nafisah Khalid
There are currently 153 species of Shorea listed in the International Union for Conservation of Nature and Natural Resources (IUCN) Red list 2013 where Shorea leprocula (Meranti tembaga), Shorea pauciflora king (Meranti nemesu) and Shorea resinosa (Meranti belang) that are found in the Ampang Fo...
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Format: | Book Section |
Language: | English |
Published: |
Institute of Graduate Studies
2017
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Subjects: | |
Online Access: | http://ir.uitm.edu.my/id/eprint/18826/1/ABS_NAFISAH%20KHALID%20TDRA%20VOL%2012%20IGS%2017.pdf http://ir.uitm.edu.my/id/eprint/18826/ |
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Institution: | Universiti Teknologi Mara |
Language: | English |
Summary: | There are currently 153 species of Shorea listed in the International
Union for Conservation of Nature and Natural Resources (IUCN) Red list
2013 where Shorea leprocula (Meranti tembaga), Shorea pauciflora king
(Meranti nemesu) and Shorea resinosa (Meranti belang) that are found in
the Ampang Forest Reserve are listed as endangered species. Due to the
current list, mapping and monitoring the forest inventories of this species
is necessary to provide the regular report for Reducing Emissions from
Deforestation and Degradation (REDD) program especially concerning
the accurate estimation of total aboveground biomass in calculating
the carbon stock. However, uncertainties in tropical forest remain high
because it is costly and laborious to measure the tree variables accurately
in relation to quantify the aboveground biomass. Thus, recent remote
sensing technology that allows for accurate operational and managerial
inventories in a cost effective and timely manner is constantly in demand.
In this study, the pan-sharpening Worldview-2 imagery is used to extract
the tree crown parameters using object-based image analysis. Three
image segmentation methods have examined which are image filtering,
combination of image filtering with inverse watershed and multiresolution
with local extrema image segmentation... |
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