APPLICATION OF THE MMAC ALGORITHM TO TREE HEIGHT AND CROWN DIAMETER ESTIMATION IN MOUNTAINOUS FOREST

被引:0
作者
Lin, C. [1 ]
Lo, C. S. [2 ]
Thomson, G. [3 ]
Yang, M. S. [1 ]
机构
[1] Natl Chiayi Univ, Dept Forestry & Nat Resources, 300 Univ Rd, Chiayi 60004, Taiwan
[2] Natl Formosa Univ, Dept Multimedia Design, Taipei 63201, Taiwan
[3] Natl Formosa Univ, Dept Appl Foreign Languages, Yunlin 63201, Taiwan
来源
NETWORKING THE WORLD WITH REMOTE SENSING | 2010年 / 38卷
关键词
tree height estimation; diameter estimation; multi-level morphological active contour (MMAC) algorithm; lidar remote sensing; MULTISPECTRAL DATA; AIRBORNE LIDAR; BIOMASS; FUSION; VOLUME;
D O I
暂无
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
This paper applied the multi-level morphological active contour (MMAC) algorithm to the estimation of diameter at breast height (DBH), total height, and crown width of trees in mountainous forest based on rasterized airborne lidar data. The MMAC algorithm comprises three steps: a bottom up erosion (BUE) process to identify stand candidates, a top down dilation (TDD) process to estimate the crown periphery, and an active contour model (ACM) process to delineate crown contours. The total height (LH) and crown width (LCW) can be directly calculated by the MMAC method and then used as regressors in a multiple regression model for the estimation of diameter at breast height (LDBH). The results showed that the average estimation bias of LH, LCW, and LDBH is around 0.50 m, 2.54 m, and 8.7 cm respectively.
引用
收藏
页码:700 / 704
页数:5
相关论文
共 38 条
  • [1] Estimation of Individual Tree Biomass from Airborne Lidar Data using Tree Height and Crown Diameter
    Anjin, Chang
    Yongmin, Kim
    Yongil, Kim
    Yangdam, Eo
    DISASTER ADVANCES, 2012, 5 (04): : 360 - 365
  • [2] Determining tree height and crown diameter from high-resolution UAV imagery
    Panagiotidis, Dimitrios
    Abdollahnejad, Azadeh
    Surovy, Peter
    Chiteculo, Vasco
    INTERNATIONAL JOURNAL OF REMOTE SENSING, 2017, 38 (8-10) : 2392 - 2410
  • [3] A Multi-level Morphological Active Contour Algorithm for Delineating Tree Crowns in Mountainous Forest
    Lin, Chinsu
    Thomson, Gavin
    Lo, Chien-Shun
    Yang, Ming-Shein
    PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING, 2011, 77 (03) : 241 - 249
  • [4] Estimation of Forest Canopy Height Over Mountainous Areas Using Satellite Lidar
    Fang, Zhou
    Cao, Chunxiang
    IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2014, 7 (07) : 3157 - 3166
  • [5] Tree height and tropical forest biomass estimation
    Hunter, M. O.
    Keller, M.
    Victoria, D.
    Morton, D. C.
    BIOGEOSCIENCES, 2013, 10 (12) : 8385 - 8399
  • [6] Modeling of tree height-diameter relationships in the Atlantic Forest: effect of forest type on tree allometry
    Cysneiros, Vinicius Costa
    Pelissari, Allan Libanio
    Gaui, Tatiana Dias
    Fiorentin, Luan Demarco
    de Carvalho, Daniel Costa
    Silveira Filho, Telmo Borges
    Machado, Sebastiao Amaral
    CANADIAN JOURNAL OF FOREST RESEARCH, 2020, 50 (12) : 1289 - 1298
  • [7] Accuracy of LiDAR-based tree height estimation and crown recognition in a subtropical evergreen broad-leaved forest in Okinawa, Japan
    Zawawi, Azita Ahmad
    Shiba, Masami
    Jemali, Noor Janatun Naim
    FOREST SYSTEMS, 2015, 24 (01)
  • [8] Terrestrial Laser Scanning as an Effective Tool to Retrieve Tree Level Height, Crown Width, and Stem Diameter
    Srinivasan, Shruthi
    Popescu, Sorin C.
    Eriksson, Marian
    Sheridan, Ryan D.
    Ku, Nian-Wei
    REMOTE SENSING, 2015, 7 (02) : 1877 - 1896
  • [9] Estimating Pinus palustris tree diameter and stem volume from tree height, crown area and stand-level parameters
    Gonzalez-Benecke, C. A.
    Gezan, Salvador A.
    Samuelson, Lisa J.
    Cropper, Wendell P., Jr.
    Leduc, Daniel J.
    Martin, Timothy A.
    JOURNAL OF FORESTRY RESEARCH, 2014, 25 (01) : 43 - 52
  • [10] DESIGN AND APPLICATION OF BARCODE DIAMETER-AT-BREAST-HEIGHT TAPE IN FOREST INVENTORIES
    Zhou, D. Q.
    He, X. J.
    Chen, G. W.
    APPLIED ECOLOGY AND ENVIRONMENTAL RESEARCH, 2019, 17 (06): : 13407 - 13421