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...

Full description

Saved in:
Bibliographic Details
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/9036/1/02_Hamidan_Omar.pdf
http://journalarticle.ukm.my/9036/
http://www.ukm.my/jsm/english_journals/vol44num8_2015/contentsVol44num8_2015.html
Tags: Add Tag
No Tags, Be the first to tag this record!
id my-ukm.journal.9036
record_format eprints
spelling my-ukm.journal.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
institution Universiti Kebangsaan Malaysia
building Perpustakaan Tun Sri Lanang Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Kebangsaan Malaysia
content_source UKM Journal Article Repository
url_provider http://journalarticle.ukm.my/
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/9036/1/02_Hamidan_Omar.pdf
http://journalarticle.ukm.my/9036/
http://www.ukm.my/jsm/english_journals/vol44num8_2015/contentsVol44num8_2015.html
_version_ 1643737657965019136
score 13.214268