02301nab a2200337 i 4500003000900000005001700009008004100026040001800067072000800085072000800093072000800101100004100109100004300150100003700193100003200230100003500262100003000297100003400327100003700361245008500398500009400483520098200577650002101559650002501580650002701605650001601632773020701648856008101855942000801936999001901944BR-BrBNA20260427105943.0260427b2019    bl.qr|pooa||| 00| 0 eng |  aBR-BrBNAbeng  aK10  aU40  aU10  aGonçalves, Anny Francielly Ataide   aFernandes, Márcia Rodrigues de Moura  aSilva, Jeferson Pereira Martins   aSilva, Gilson Fernandes da   aAlmeida, André Quintão de   aCordeiro, Natielle Gomes   aSilva, Lucas Duarte Caldas da  aScolforo, José Roberto Soares   aWood Volume Estimation in a Semidecidual Seasonal Forest Using MSI and SRTM Data  aPublicação on-line; Bibliography p. 8-11; (50 ref.); 2 tables; 2 illus.; Summary (En)  a

ABSTRACT

The objective of this study was to evaluate the use of the MSI Sentinel-2 and SRTM data to
estimate the volume of wood in a Semidecidual Seasonal Forest. Regression equations were fitted
based on the remote sensing data, taking into consideration the individual bands and vegetation
index of the MSI, elevation values and their derivatives obtained from the SRTM mission and the
combination of the data drawn from the MSI and SRTM. RMSE and graphic analysis of residues
were used to assess the accuracy of the fitted equations. The best model revealed values of 0.6508
and RMSE of 20.41% in the fit, and of 0.5680 and RMSE of 26.61% in the validation, using the
combined MSI and SRTM data as predictors. The volume estimation using spectral data showed
satisfactory results, highlighting the importance of topography in the prediction of the volume
of wood for the area under investigation.

Keywords: atlantic forest, remote sensing, forest inventory, measurement.  aMATA ATLÂNTICA  aSENSORIAMENTO REMOTO  aINVENTÁRIO FLORESTAL  aMEDIÇÃO0 029299347954dRio de Janeiro-RJ Instituto de Florestas - UFRRJ 1994o2025-0453tFloresta e Ambiente (Brazil)x1415-0980  /  ISSN 2179-8087 0nlinegv. 26(special number n.1) p. 1-11; (2019)wBR2026001289  uhttps://www.scielo.br/j/floram/a/jTQxJvDxmVbMCx48PKVxdYN/?format=pdf&lang=en  cANA  c341574d341574