Aboveground Biomass Estimates of Araucaria angustifolia (Bertol.) Kuntze, Using Vegetation Indexes in Wolrdview-2 Image

Basso, Luiz Carlos Pietrowski and Pesck, Vagner Alex and Roik, Mailson and Filho, Afonso Figueiredo and Stepka, Thiago Floriani and Lisboa, Gerson dos Santos and Konkol, Ismael and Hess, André Felipe and Brandalize, Ana Paula (2019) Aboveground Biomass Estimates of Araucaria angustifolia (Bertol.) Kuntze, Using Vegetation Indexes in Wolrdview-2 Image. Journal of Agricultural Science, 11 (11). p. 93. ISSN 1916-9752

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Abstract

The present research aims to evaluate the biomass estimates of Araucaria angustifolia (Bertol.) Kuntze trees obtained by the direct method, then present results generated from a 2.0 m resolution spectral image Worldview-2 satellite. The quantification of the biomass in the field was first carried out of 29 trees of the specie of interest with DBH ≥ 40 cm and then with the image aid the crowns were delimited for analysis. From the spectral bands (B2-blue, B3-green, B4-yellow, B5-red, B6-near red, B7-near infrared 2 and B8-near infrared 2), it was possible to obtain vegetation indexes proposed by the literature (NDVI, NDVI_2, RS and SAVI_0,25) and later incorporated with dendrometric data a correlation matrix was formed. Additionally, mathematical equations were used to estimate biomass and carbon as a function of dendrometric variables and information obtained from the satellite image processing. From these equations, the ones that presented better results were those that contained independent dendrometric variables (DBH) and those that contained vegetation indices (NDVI_2 and NDVI). For the dendrometers, the relative error found was 14.42% and 14.32% for biomass and carbon respectively, while for the digital ones, NDVI_2 found a relative error of 37.82% and an adjusted coefficient of determination of 0.88 in the biomass equations. In the carbon equations, the NDVI variable presented the best results, being 38.56% the relative error and 0.87 the determination coefficient.

Item Type: Article
Subjects: OA Open Library > Agricultural and Food Science
Depositing User: Unnamed user with email support@oaopenlibrary.com
Date Deposited: 12 May 2023 06:45
Last Modified: 31 Jan 2024 04:02
URI: http://archive.sdpublishers.com/id/eprint/772

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