Mangrove Species Mapping in Kuala Sepetang Mangrove Forest, Perak using High Resolution Airborne Data

被引:0
|
作者
Beh, B. C. [1 ]
MatJafri, M. Z. [1 ]
Lim, H. S. [1 ]
机构
[1] Univ Sains Malaysia, Sch Phys, George Town 11800, Malaysia
关键词
Mangrove vegetation; airborne data; Kuala Sepetang Mangrove Forest Reserve; mangrove species mapping; retrieved surface reflectance; Geomatica 2013 software package;
D O I
10.1117/12.2195435
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Mangrove vegetation is widely employed and studied as it is a unique ecosystem which is able to provide plenty of goods and applications to our country. In this paper, high resolution airborne image data obtained the flight mission on Kuala Sepetang Mangrove Forest Reserve, Perak, Malaysia will be used for mangrove species mapping. Supervised classification using the retrieved surface reflectance will be performed to classify the airborne data using Geomatica 2013 software package. The ground truth data will be used to validate the classification accuracy. High correlation of R-2=0.873 was achieved in this study indicate that high resolution airborne data is reliable and suitable used for mangrove species mapping.
引用
收藏
页数:8
相关论文
共 50 条
  • [1] Discrimination Of Mangrove Species In Matang Mangrove Forest Reserve, Perak Using In-situ Measurement Of Hyperspectral Leaf Reflectance
    Chun, Beh Boon
    Keat, Sim Chong
    Syahreza, Saumi
    Jafri, Mohd Zubir Mat
    San, Lim Hwee
    [J]. NATIONAL PHYSICS CONFERENCE 2014 (PERFIK 2014), 2015, 1657
  • [2] MAPPING MANGROVE COMMUNITIES IN COASTAL WETLANDS USING AIRBORNE HYPERSPECTRAL DATA
    Zhou, Xiong
    Armitage, Anna R.
    Prasad, Saurabh
    [J]. 2016 8TH WORKSHOP ON HYPERSPECTRAL IMAGE AND SIGNAL PROCESSING: EVOLUTION IN REMOTE SENSING (WHISPERS), 2016,
  • [3] The assessment of mangrove areas using high resolution multispectral airborne imagery
    Green, EP
    Mumby, PJ
    Edwards, AJ
    Clark, CD
    Ellis, AC
    [J]. JOURNAL OF COASTAL RESEARCH, 1998, 14 (02) : 433 - 443
  • [4] Mapping Mangrove Species Using Hyperspectral Data: A Case Study of Pichavaram Mangrove Ecosystem, Tamil Nadu
    Salghuna N.N.
    Pillutla R.C.P.
    [J]. Earth Systems and Environment, 2017, 1 (2)
  • [5] Comparison of Different Discriminant Functions for Mangrove Species Analysis in Matang Mangrove Forest Reserve (MMFR), Perak Based on Statistical Approach
    Beh, Boon Chun
    Tan, Kok Chooi
    Jafri, Mohd. Zubir Mat
    Lim, Hwee San
    [J]. REMOTE SENSING FOR AGRICULTURE, ECOSYSTEMS, AND HYDROLOGY XIX, 2017, 10421
  • [6] Mapping the Mangrove Forest Canopy Using Spectral Unmixing of Very High Spatial Resolution Satellite Images
    Taureau, Florent
    Robin, Marc
    Proisy, Christophe
    Fromard, Francois
    Imbert, Daniel
    Debaine, Francoise
    [J]. REMOTE SENSING, 2019, 11 (03)
  • [7] Mapping mangrove changes in the Matang Mangrove Forest using multi temporal satellite imageries
    Ibharim, N. A.
    Mustapha, M. A.
    Lihan, T.
    Mazlan, A. G.
    [J]. OCEAN & COASTAL MANAGEMENT, 2015, 114 : 64 - 76
  • [8] Canopy Cover Mapping in Ratai Bay Mangrove Forests using Airborne LiDAR Data
    Mulyanto, M.
    Kamal, Muhammad
    Wijaya, Muhammad Sufwandika
    [J]. EIGHTH GEOINFORMATION SCIENCE SYMPOSIUM 2023: GEOINFORMATION SCIENCE FOR SUSTAINABLE PLANET, 2024, 12977
  • [9] Estimating leaf area index of a degraded mangrove forest using high spatial resolution satellite data
    Kovacs, JM
    Flores-Verdugo, F
    Wang, JF
    Aspden, LP
    [J]. AQUATIC BOTANY, 2004, 80 (01) : 13 - 22
  • [10] Separating Mangrove Species and Conditions Using Laboratory Hyperspectral Data: A Case Study of a Degraded Mangrove Forest of the Mexican Pacific
    Zhang, Chunhua
    Kovacs, John M.
    Liu, Yali
    Flores-Verdugo, Francisco
    Flores-de-Santiago, Francisco
    [J]. REMOTE SENSING, 2014, 6 (12) : 11673 - 11688