Development of allometric model for mixed and shorea tree species through synergistic analysis of remote sensing data / Nafisah Khalid

Khalid, Nafisah (2017) Development of allometric model for mixed and shorea tree species through synergistic analysis of remote sensing data / Nafisah Khalid. In: The Doctoral Research Abstracts. IGS Biannual Publication, 12 (12). Institute of Graduate Studies, Shah Alam.

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Abstract

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...

Item Type: Book Section
Creators:
CreatorsEmail
Khalid, NafisahUNSPECIFIED
Subjects: G Geography. Anthropology. Recreation > G Geography (General) > Philosophy. Relation to other topics. Methodology
G Geography. Anthropology. Recreation > GE Environmental Sciences
G Geography. Anthropology. Recreation > GE Environmental Sciences > Environmental conditions. Environmental quality. Environmental indicators
Q Science > QE Geology
Divisions: Institut Pengajian Siswazah (IPSis) : Institute of Graduate Studies (IGS)
Series Name: IGS Biannual Publication
Volume: 12
Number: 12
Item ID: 18826
Uncontrolled Keywords: Abstract; Abstract of Thesis; Newsletter; Research information; Doctoral graduates; IPSis; IGS; UiTM; Synergistic analysis; Remote sensing data
Last Modified: 25 Jan 2018 03:44
Depositing User: Admin Pendigitan 2 PTAR
URI: http://ir.uitm.edu.my/id/eprint/18826

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