Estimating Biomass in Logged Tropical Forest Using L-Band SAR (PALSAR) Data and GIS

被引:2
|
作者
Omar, Hamdan [1 ]
Ismail, Mohd Hasmadi [2 ]
Hamzah, Khali Aziz [1 ]
Shafri, Helmi Zulhaidi Mohd [2 ]
Kamarudin, Norizah [2 ]
机构
[1] Forest Res Inst Malaysia, Kepong 52109, Selangor Darul, Malaysia
[2] Univ Putra Malaysia, Serdang 43400, Selangor Darul, Malaysia
来源
SAINS MALAYSIANA | 2015年 / 44卷 / 08期
关键词
Biomass estimate; GIS; L-band SAR; tropical forest; SPATIAL VARIABILITY; RADAR; TEXTURE; IMPACTS;
D O I
10.17576/jsm-2015-4408-02
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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 30x30 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.
引用
收藏
页码:1085 / 1093
页数:9
相关论文
共 50 条
  • [41] Forest Growing Stock Volume Estimation in Subtropical Mountain Areas Using PALSAR-2 L-Band PolSAR Data
    Zhang, Haibo
    Zhu, Jianjun
    Wang, Changcheng
    Lin, Hui
    Long, Jiangping
    Zhao, Lei
    Fu, Haiqiang
    Liu, Zhiwei
    FORESTS, 2019, 10 (03):
  • [42] RICE AREAS MAPPING USING ALOS PALSAR FBD DATA CONSIDERING THE BRAGG SCATTERING IN L-BAND SAR IMAGES OF RICE FIELDS
    Ling, Feilong
    Li, Zengyuan
    Chen, Erxue
    Tian, Xin
    Bai, Lina
    Wang, Fengyu
    2010 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, 2010, : 1461 - 1464
  • [43] Verification of a method for estimating building damage in extensive tsunami affected areas using L-band SAR data
    Gokon H.
    Koshimura S.
    Megur K.
    Gokon, Hideomi (gokon@iis.u-tokyo.ac.jp), 1600, Fuji Technology Press (12): : 251 - 258
  • [44] Exploring the Capability of ALOS PALSAR L-Band Fully Polarimetric Data for Land Cover Classification in Tropical Environments
    Negri, Rogerio Galante
    Dutra, Luciano Vieira
    Freitas, Corina da Costa
    Lu, Dengsheng
    IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2016, 9 (12) : 5369 - 5384
  • [45] Forest Structure Characterization From SAR Tomography at L-Band
    Tello, Marivi
    Cazcarra-Bes, Victor
    Pardini, Matteo
    Papathanassiou, Konstantinos
    IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2018, 11 (10) : 3402 - 3414
  • [46] Assessing L-band SAR modes for commercial forest management
    Wallington, ED
    Turner, D
    Woodhouse, IH
    Malthus, TJ
    Suárez-Minguez, JC
    IGARSS 2003: IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS I - VII, PROCEEDINGS: LEARNING FROM EARTH'S SHAPES AND SIZES, 2003, : 2541 - 2543
  • [47] Forest structure dependency analysis of L-band SAR backscatter
    Ji, Yongjie
    Huang, Jimao
    Ju, Yilin
    Guo, Shipeng
    Yue, Cairong
    PEERJ, 2020, 8
  • [48] STRUCTURAL CLASSIFICATION OF FOREST BY MEANS OF L-BAND TOMOGRAPHIC SAR
    Tello, Marivi
    Cazcarra-Bes, Victor
    Pardini, Matteo
    Papathanassiou, Kostas
    2015 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2015, : 5288 - 5291
  • [49] L-Band Synthetic Aperture Radar (SAR) Response to the Tropical Forest Stands for Carbon Stock Assessment
    Omar, Hamdan
    Mat, Nur Laila Che
    Hamzah, Khali Aziz
    Ismail, Mohd Hasmadi
    2012 NATIONAL PHYSICS CONFERENCE (PERFIK 2012), 2013, 1528 : 76 - 81
  • [50] A comparative study of coherence information by L-band and C-band SAR for detecting deforestation in tropical rain forest
    Takeuchi, S
    Suga, Y
    Yoshimura, M
    IGARSS 2001: SCANNING THE PRESENT AND RESOLVING THE FUTURE, VOLS 1-7, PROCEEDINGS, 2001, : 2259 - 2261