Correlation of spectral variables and aboveground carbon stock of agroforestry systems

被引:12
|
作者
Bolfe, Edson Luis [1 ]
Batistella, Mateus [1 ]
Ferreira, Marcos Cesar [2 ]
机构
[1] Embrapa Monitoramento Satelite, BR-13070115 Campinas, SP, Brazil
[2] Univ Estadual Campinas, BR-13083870 Campinas, SP, Brazil
关键词
crop-livestock-forest integration; Landsat; remote sensing; land use and land cover; VEGETATION; DERIVATION; INDEX; MODEL;
D O I
10.1590/S0100-204X2012000900011
中图分类号
S [农业科学];
学科分类号
09 ;
摘要
The objective of this work was to evaluate the correlation between spectral variables and aboveground carbon stock of agroforestry systems in the region of Tome-Acu, PA, Brazil. Twenty-four vegetation indices from three groups (simple ratio, normalized difference, and complex), calculated from images of the TM/Landsat-5 sensor acquired in 2008, were tested. The obtained variables were correlated, by means of simple linear regression, to carbon stock from four agroforestry systems with different ages and floristic composition. The correlations obtained among spectral variables and carbon stock were significant in 47% of the tested indices and changed according to the differences in biomass of the analyzed systems. The best correlations were obtained by the simple ratio and normalized difference indices in young agroforestry systems, and by complex vegetation indices in older agroforestry systems.
引用
收藏
页码:1261 / 1269
页数:9
相关论文
共 50 条
  • [41] Assessment of aboveground biomass and carbon stock of subtropical pine forest of Pakistan
    Ali, Nizar
    Saad, Muhammad
    Ali, Anwar
    Ahmad, Naveed
    Khan, Ishfaq Ahmad
    Ullah, Habib
    Imran, Areeba Binte
    JOURNAL OF FOREST SCIENCE, 2023, 69 (07) : 287 - 304
  • [42] Estimation of Aboveground Forest Biomass Carbon Stock by Satellite Remote Sensing
    Jung, Jaehoon
    Nguyen, Hieu Cong
    Heo, Joon
    Kim, Kyoungmin
    Im, Jungho
    KOREAN JOURNAL OF REMOTE SENSING, 2014, 30 (05) : 651 - 664
  • [43] Remote sensing and machine learning applications for aboveground biomass estimation in agroforestry systems: a review
    Bhuwan Thapa
    Sarah Lovell
    Jeffrey Wilson
    Agroforestry Systems, 2023, 97 : 1097 - 1111
  • [44] Remote sensing and machine learning applications for aboveground biomass estimation in agroforestry systems: a review
    Thapa, Bhuwan
    Lovell, Sarah
    Wilson, Jeffrey
    AGROFORESTRY SYSTEMS, 2023, 97 (06) : 1097 - 1111
  • [45] Biomass production, carbon stock and sequestration potential of prominent agroforestry systems in north-western Himalaya, India
    Saleem, Ishrat
    Mugloo, J. A.
    Pala, Nazir A.
    Bhat, G. M.
    Masoodi, T. H.
    Mughal, A. H.
    Baba, Afshan A.
    Mehraj, Basira
    FRONTIERS IN FORESTS AND GLOBAL CHANGE, 2023, 6
  • [46] Woody species diversity and carbon stock potentials in homegarden agroforestry and other land use systems, northern Ethiopia
    Maryo, Melesse
    Wolde, Addisu
    Negash, Mesele
    HELIYON, 2023, 9 (09)
  • [47] Shade canopy density variables in cocoa and coffee agroforestry systems
    Eduardo Somarriba
    Stéphane Saj
    Luis Orozco-Aguilar
    Aurelio Somarriba
    Bruno Rapidel
    Agroforestry Systems, 2024, 98 : 585 - 601
  • [48] Shade canopy density variables in cocoa and coffee agroforestry systems
    Somarriba, Eduardo
    Saj, Stephane
    Orozco-Aguilar, Luis
    Somarriba, Aurelio
    Rapidel, Bruno
    AGROFORESTRY SYSTEMS, 2024, 98 (03) : 585 - 601
  • [49] CARBON STOCKS IN AGROFORESTRY SYSTEMS WITH COFFEE PLANTATIONS
    Espinoza-Dominguez, William
    Krishnamurthy, L.
    Vazquez-Alarcon, Antonio
    Torres-Rivera, Antonio
    REVISTA CHAPINGO SERIE CIENCIAS FORESTALES Y DEL AMBIENTE, 2012, 18 (01) : 57 - 70
  • [50] Potential of agroforestry systems in carbon sequestration in India
    Dhyani, S. K.
    Ram, Asha
    Dev, Inder
    INDIAN JOURNAL OF AGRICULTURAL SCIENCES, 2016, 86 (09): : 1103 - 1112