Spectral characterization of forest plantations with Landsat 8/OLI images for forest planning and management

Alba, Elisiane; Mello, Eliziane Pivotto; Marchesan, Juliana; Silva, Emanuel Araújo; Tramontina, Juliana; Pereira, Rudiney Soares

doi:10.1590/S0100-204X2017001100013

Acessibilidade / Reportar erro

Brasil

Pesquisa Agropecuária Brasileira

Español English

Brasil

Español English

sumário « anterior atual seguinte »

Sumário

REMOTE SENSING • Pesq. agropec. bras. 52 (11) • Nov 2017 • https://doi.org/10.1590/S0100-204X2017001100013 copy

Spectral characterization of forest plantations with Landsat 8/OLI images for forest planning and management

Caracterização espectral de plantios florestais com imagens Landsat 8/OLI para planejamento e manejo florestal

Authorship SCIMAGO INSTITUTIONS RANKINGS

Abstract:

The objective of this work was to evaluate the use of Landsat 8/OLI images to differentiate the age and estimate the total volume of Pinus elliottii, in order to determine the applicability of these data in the planning and management of forest activity. Fifty-three sampling units were installed, and dendrometric variables of 9-and-10-year-old P. elliottii commercial stands were measured. The digital numbers of the image were converted into surface reflectance and, subsequently, vegetation indices were determined. Red and near-infrared reflectance values were used to differentiate the ages of the stands. Regression analysis of the spectral variables was used to estimate the total volume. Increase in age caused an addition in reflectance in the near-infrared band and a decrease in the red band. The general equation for estimating the total volume for P.elliottii had an R²_adj of 0.67 with a S_yx of 31.46 m³ ha^-1. Therefore, the spectral data with medium spatial resolution from the Landsat 8/OLI satellite can be used to distinguish the growth stages of the stands and can, thus, be used in the planning and proper management of forest activity on a spatial and temporal scale.

Index terms:
Pinus elliottii; remote sensing; vegetation indices; volume modeling.

Embrapa Secretaria de Pesquisa e Desenvolvimento; Pesquisa Agropecuária Brasileira Caixa Postal 040315, 70770-901 Brasília DF Brazil, Tel. +55 61 3448-1813, Fax +55 61 3340-5483 - Brasília - DF - Brazil
E-mail: pab@embrapa.br

Acompanhe os números deste periódico no seu leitor de RSS

[TFN1] ⁽¹⁾ARVI, atmospherically resistant vegetation index; DVI, difference vegetation index; GNDVI, green normalized difference vegetation index; MVI, moisture vegetation index; NDVI, normalized difference vegetation index; SAVI, soil adjusted vegetation index; SR, simple ratio vegetation index; ρ_blue, reflectance at blue; ρ_red, reflectance at red; ρ_green, reflectance at green; ρ_NIR, reflectance at near infrared; ρ_SWIR, reflectance at short wave infrared; and L, soil effect minimization constant.

Vegetation index	Formula	Author
ARVI	$\frac{ρ_{N I R} - (2 \times ρ_{r e d} + ρ_{b l u e})}{ρ_{N I R} - (2 \times ρ_{r e d} + ρ_{b l u e})}$	Kaufman & Tanré (1992KAUFMAN, Y.J.; TANRÉ, D. Atmospherically resistant vegetation index (ARVI) for EOS-MODIS. IEEE Transactions on Geoscience and Remote Sensing, v.30, p.261-270, 1992. DOI: 10.1109/36.134076. https://doi.org/10.1109/36.134076.... )
DVI	$ρ_{N I R} - ρ_{r e d}$	Clevers (1988CLEVERS, J.G.P.W. The derivation of a simplified reflectance model for the estimation of leaf area index. Remote Sensing of Environment, v.25, p.53-69, 1988. DOI: 10.1016/0034-4257(88)90041-7. https://doi.org/10.1016/0034-4257(88)900... )
GNDVI	$\frac{ρ_{N I R} - ρ_{g r e e n})}{ρ_{N I R} + ρ_{g r e e n})}$	Sousa & Ponzoni (1998SOUSA, C.L.; PONZONI, F.J. Avaliação de índices de vegetação e de bandas TM/Landsat para estimativa de volume de madeira em floresta implantada de Pinus spp. In: SIMPÓSIO BRASILEIRO DE SENSORIAMENTO REMOTO, 9., 1998, Santos. Anais. São José dos Campos: INPE, 1998.)
MVI	$\frac{ρ_{N I R} - ρ_{S W I R}}{ρ_{N I R} + ρ_{S W I R}}$	Sousa & Ponzoni (1998SOUSA, C.L.; PONZONI, F.J. Avaliação de índices de vegetação e de bandas TM/Landsat para estimativa de volume de madeira em floresta implantada de Pinus spp. In: SIMPÓSIO BRASILEIRO DE SENSORIAMENTO REMOTO, 9., 1998, Santos. Anais. São José dos Campos: INPE, 1998.)
NDVI	$\frac{ρ_{N I R} - ρ_{r e d}}{ρ_{N I R} + ρ_{r e d}}$	Rouse et al. (1974)ROUSE JR., J.W.; HAAS, R.H.; DEERING, D.W.; SCHELL, J.A. Monitoring the vernal advancement and retrogradation (green wave effect) of natural vegetation. College Station: Texas A&M University, 1974. 87p. (Progress Report RSC 1978-2).
SAVI	$\frac{(ρ_{N I R} - ρ_{r e d})}{(ρ_{N I R} + ρ_{r e d} + L)} \times (1 + L)$	Huete et al. (1985HUETE, A.R.; JACKSON, R.D.; POST, D.F. Spectral response of a plant canopy with different soil background. Remote Sensing of Environment, v.17, p.37-53, 1985. DOI: 10.1016/0034-4257(85)90111-7. https://doi.org/10.1016/0034-4257(85)901... )
SR	$\frac{ρ_{N I R}}{ρ_{r e d}}$	Jordan (1969)JORDAN, C.F. Derivation of Leaf-Area Index from Quality of Light on the Forest Floor. Ecology, v.50, p.663-666, 1969. DOI: 10.2307/1936256. https://doi.org/10.2307/1936256....

Age	Band
Age	B5	B4
9	Lower reflectance: greater effect of litter on spectral response	Higher reflectance: due to reduced canopy structure (LAI) and lower EMR absorption
10	Higher reflectance: higher canopy development, greater presence of green leaves, and lower effect of litter	Lower reflectance: higher EMR absorption by photosynthetic pigments due to larger canopy structure

Spectral variable⁽¹⁾	Stand
Spectral variable⁽¹⁾	9-year-old	10-year-old	9-and-10-year-old
B2 band	0.006±0.001	0.005±0.001	0.006±0.001
B3 band	0.023±0.001	0.021±0.001	0.022±0.001
B4 band	0.011±0.001	0.009±0.002	0.010±0.002
B5 band	0.268±0.005	0.283±0.005	0.276±0.009
B6 band	0.062±0.004	0.057±0.004	0.060±0.004
B7 band	0.024±0.002	0.021±0.002	0.023±0.002
ARVI	0.857±0.015	0.884±0.007	0.870±0.018
DVI	0.257±0.005	0.273±0.006	0.266±0.010
GNDVI	0.843±0.008	0.860±0.008	0.851±0.011
MVI	0.623±0.022	0.663±0.018	0.644±0.028
NDVI	0.920±0.009	0.936±0.005	0.928±0.011
SAVI₂₅	0.607±0.009	0.630±0.007	0.619±0.014
SAVI₅₀	0.729±0.011	0.756±0.009	0.743±0.017
SR	24.230±2.418	30.609±2.537	27.357±3.99

Equation	Model	S_yx	R²_adj	FI	F
Equation for 9-year-old stand	V = -262,636.0 + 428,721.0 × B5 - 112,296.0 × ln(B5)	29.39	0.71	44.77	23.64**
Equation for 10-year-old stand	V = -1,102.8 + 4,835.2 × DVI	18.80	0.72	29.41	54.2**
General equation	V = -1,257.1 + 5,228.0 × B5	31.46	0.67	49.21	82.4**