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...

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Main Authors:	Hamdan Omar, Mohd Hasmadi Ismail, Khali Aziz Hamzah, Helmi Zulhaidi Mohd Shafri, Norizah Kamarudin
Format:	Article
Language:	English
Published:	Universiti Kebangsaan Malaysia 2015
Online Access:	http://journalarticle.ukm.my/9036/ http://journalarticle.ukm.my/9036/ http://journalarticle.ukm.my/9036/1/02_Hamidan_Omar.pdf

id	ukm-9036
recordtype	eprints
spelling	ukm-90362016-12-14T06:48:47Z http://journalarticle.ukm.my/9036/ Estimating biomass in logged tropical forest using L-Band SAR (PALSAR) data and GIS Hamdan Omar, Mohd Hasmadi Ismail, Khali Aziz Hamzah, Helmi Zulhaidi Mohd Shafri, Norizah Kamarudin, 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. Universiti Kebangsaan Malaysia 2015-08 Article PeerReviewed application/pdf en http://journalarticle.ukm.my/9036/1/02_Hamidan_Omar.pdf Hamdan Omar, and Mohd Hasmadi Ismail, and Khali Aziz Hamzah, and Helmi Zulhaidi Mohd Shafri, and Norizah Kamarudin, (2015) Estimating biomass in logged tropical forest using L-Band SAR (PALSAR) data and GIS. Sains Malaysiana, 44 (4). pp. 1085-1093. ISSN 0126-6039 http://www.ukm.my/jsm/english_journals/vol44num8_2015/contentsVol44num8_2015.html
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Kebangasaan Malaysia
building	UKM Institutional Repository
collection	Online Access
language	English
description	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.
format	Article
author	Hamdan Omar, Mohd Hasmadi Ismail, Khali Aziz Hamzah, Helmi Zulhaidi Mohd Shafri, Norizah Kamarudin,
spellingShingle	Hamdan Omar, Mohd Hasmadi Ismail, Khali Aziz Hamzah, Helmi Zulhaidi Mohd Shafri, Norizah Kamarudin, Estimating biomass in logged tropical forest using L-Band SAR (PALSAR) data and GIS
author_facet	Hamdan Omar, Mohd Hasmadi Ismail, Khali Aziz Hamzah, Helmi Zulhaidi Mohd Shafri, Norizah Kamarudin,
author_sort	Hamdan Omar,
title	Estimating biomass in logged tropical forest using L-Band SAR (PALSAR) data and GIS
title_short	Estimating biomass in logged tropical forest using L-Band SAR (PALSAR) data and GIS
title_full	Estimating biomass in logged tropical forest using L-Band SAR (PALSAR) data and GIS
title_fullStr	Estimating biomass in logged tropical forest using L-Band SAR (PALSAR) data and GIS
title_full_unstemmed	Estimating biomass in logged tropical forest using L-Band SAR (PALSAR) data and GIS
title_sort	estimating biomass in logged tropical forest using l-band sar (palsar) data and gis
publisher	Universiti Kebangsaan Malaysia
publishDate	2015
url	http://journalarticle.ukm.my/9036/ http://journalarticle.ukm.my/9036/ http://journalarticle.ukm.my/9036/1/02_Hamidan_Omar.pdf
first_indexed	2023-09-18T19:53:49Z
last_indexed	2023-09-18T19:53:49Z
_version_	1777406395302281216

Estimating biomass in logged tropical forest using L-Band SAR (PALSAR) data and GIS

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