BIOMASS ALLOMETRIC FUNCTION WITH SATELLITE IMAGES OF HIGH SPATIAL RESOLUTION

被引：1
|
作者：
de Macedo, Fabricio Lopes [1 ]
de Oliveira Sousa, Adelia Maria [2 ]
Goncalves, Ana Cristina [3 ]
Silva, Helio Ricardo [4 ]
Ferreira Rodrigues, Ricardo Antonio [4 ]
机构：
[1] Univ Tras Os Montes & Alto Douro, Ctr Invest & Tecnol Agroambientais & Biol, P-5000801 Vila Real, Portugal
[2] Univ Evora, Dept Engn Rural, Escola Ciencias & Tecnol, Inst Ciencias Agr & Ambientais Mediterran, Apartado 94, P-7002554 Evora, Portugal
[3] Univ Evora, Dept Engn Rural, Inst Ciencias & Tecnol, Inst Ciencias Agr & Ambientais Mediterran, Apartado 94, P-7002554 Evora, Portugal
[4] Univ Estadual Paulista Julio de Mesquita Filho Un, Dept Fitossanidade Engn Rural & Solos, Av Brasil 56, BR-15385000 Ilha Solteira, SP, Brazil
来源：
CIENCIA FLORESTAL | 2018年 / 28卷 / 03期
关键词：
Eucalyptus; pleiades; vegetation indices; FOREST; CARBON;
D O I：
10.5902/1980509833368
中图分类号：
Q94 [植物学];
学科分类号：
071001 ;
摘要：
The aim of this study was to fit functions to estimate with data derived from high spatial resolution satellite images, the total biomass of Eucalyptus at local and regional scale. For this purpose, models were fit combining values of biomass estimated from forest inventory plots and vegetation indices based on Pleiades images. The function with which presented the best performance in the estimation of the total biomass, was the one that used as an independent variable the IV-SAVI, presenting a coefficient of determination (R-2) of 64.6%, however without great difference for the NDVI and SR. The fit functions can be used in other regions for the same species, and similar climate and local characteristics. This approach can be used as a low cost tool to produce estimations of biomass at local and regional level.
引用
收藏
页码：960 / 969
页数：10
相关论文
共 50 条
  • [31] MAP GENERATION USING HIGH RESOLUTION SATELLITE IMAGES
    Ersoy, Nihat
    Yavuz, Erol
    Kartal, Fahri
    SIGMA JOURNAL OF ENGINEERING AND NATURAL SCIENCES-SIGMA MUHENDISLIK VE FEN BILIMLERI DERGISI, 2011, 29 (04): : 367 - 371
  • [32] Information extraction from high resolution satellite images
    Yang, Haiping
    Luo, Jiancheng
    Shen, Zhanfeng
    Xia, Liegang
    MULTISPECTRAL, HYPERSPECTRAL, AND ULTRASPECTRAL REMOTE SENSING TECHNOLOGY, TECHNIQUES AND APPLICATIONS V, 2014, 9263
  • [33] Research on Vehicle Detection in High Resolution Satellite Images
    Xie, Lizhu
    Wei, Liying
    2013 FOURTH GLOBAL CONGRESS ON INTELLIGENT SYSTEMS (GCIS), 2013, : 279 - 283
  • [34] Contextual Classification of High-Resolution Satellite Images
    Besbes, Olfa
    Boujemaa, Nozha
    Belhadj, Ziad
    2009 IEEE SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE FOR IMAGE PROCESSING, 2009, : 41 - +
  • [35] ROAD EXTRACTION FROM HIGH RESOLUTION SATELLITE IMAGES
    Ozkaya, M.
    XXII ISPRS CONGRESS, TECHNICAL COMMISSION IV, 2012, 39-B4 : 143 - 148
  • [36] INTERACTIVE OBJECT SEGMENTATION IN HIGH RESOLUTION SATELLITE IMAGES
    Osman, J.
    Inglada, J.
    Christophe, E.
    2009 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS 1-5, 2009, : 3473 - +
  • [37] DETECTION OF BARCHAN DUNES IN HIGH RESOLUTION SATELLITE IMAGES
    Azzaoui, M. A.
    Adnani, M.
    El Belrhiti, H.
    Chaouki, I. E.
    Masmoudi, C.
    XXIII ISPRS CONGRESS, COMMISSION VII, 2016, 41 (B7): : 153 - 160
  • [38] Airport detection in high resolution panchromatic satellite images
    Gupta, P.
    Agrawal, A.
    J Inst Eng India Part CP, 2007, MAY (3-9): : 3 - 9
  • [39] Coastal Zone of Sevastopol on High Resolution Satellite Images
    Dulov, B. A.
    Yurovskaya, M. V.
    Kozlov, I. E.
    PHYSICAL OCEANOGRAPHY, 2015, (06): : 39 - 54
  • [40] Cloud Detection in High-Resolution Satellite Images
    Baseski, Emre
    Senaras, Caglar
    2013 21ST SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU), 2013,
12345