Accuracy of forest stand volume estimation by Landsat TM imagery with different geometric and atmospheric correction methods

Accuracy of forest stand volume estimation by Landsat TM imagery with different geometric and atmospheric correction methods
Elias Fernando Berra1, Denise Cybis Fontana2 and Rudiney Soares Pereira3

1. Engenheiro Florestal, Mestrando PPG Sensoriamento Remoto, UFRGS, Av. Bento Gonçalvez, 9500, Porto Alegre, RS, Brazil. (eliasberra@yahoo.com.br)
2. Engenheira Agrônoma, Profa Dra, Fac. de Agronomia da UFRGS. Av Bento Gonçalves, 7712, Porto Alegre, RS, Brasil. Bolsista CNPq. (dfontana@ufrgs.br)
3. Engenheiro Florestal, Profº Dr, Departamento de Engenharia Rural da UFSM, Av. Roraima, 1000, Santa Maria, RS, Brasil. (rudiney.s.pereira@gmail.com)

Abstract: Stem volume of Pinus elliottii were estimated from Landsat TM data with different methods of geometric and atmospheric correction. Regressions were used to estimate the stem volume (m³/ha), where the independent variable was the value of NDVI (Normalized Difference Vegetation Index) related to the sampling unit measured in the field. The reflectance used in the NDVI calculation were obtained by four different methods: 1) geometric correction with nearest-neighbor (NN) resampling + atmospheric correction using dark object subtraction (DOS), 2) NN resampling + atmospheric correction using MODTRAN (Moderate Resolution Transmittance), 3) geometric correction with bilinear resampling + DOS, and 4) bilinear resampling + MODTRAN. The reliability of the estimates was measured by means of bias (Bias) and standard error (RMSE). Among the atmospheric correction methods, the errors were higher with DOS. Regarding the geometric correction methods, the RMSE and Bias were higher with the NN resampling. Thus, the combination of DOS + NN had the highest RMSE (62.3%) and Bias (15.9%). The best estimate was the combination of bilinear resampling + MODTRAN, with RMSE of 56.5% and Bias of 13.3%. Therefore, it was verified that different methods of geometric and atmospheric correction should be tested to improve the estimates.

Keywords: Stem volume, geometric correction, atmospheric correction, pixel level

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