Biomass estimation based on simultaneous use of standwise forest inventory data, ASTER and MODIS satellite data

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1 Biomass estimation based on simultaneous use of standwise forest inventory data, ASTER and satellite data Petteri Muukkonen Finnish Forest Research Institute Janne Heiskanen University of Helsinki

2 Introduction According to the IPCC GPG, remote sensing methods are especially suitable for independent verifying the national LULUCF carbon pool estimates, especially the aboveground biomass. We demonstrate the potential to integrate standwise inventory data, ASTER and satellite data for characterizing stand volume (m 3 ha 1 ) and aboveground biomass (t ha 1 ).

3 Standwise forest inventory data ASTER satellite data Regression model for stand volume (m 3 ha 1 ) satellite data Stand volume (m 3 ha 1 ) Muukkonen & Heiskanen (2005) Remote Sens. Environ. 99, Biomass conversion Häme et al. (1997) Int. J. Remote Sens. 18, Aboveground tree biomass (t ha 1 ) Aboveground biomass of all vegetation (t ha 1 ) Muukkonen & Heiskanen (2006) Manuscript.

4 Material ASTER Spectral range (µm) Band 2: , Red Band 1: , Red Band 3: , NIR Band 2: , NIR Spatial resolution (m)

5 Study area Standwise inventory data: A. Metla B. Metsähallitus

6 ASTER data & standwise forest inventory data

7 Reflectance in ASTER band Total biomass (t ha 1 )

8 Calibration of Modis data y[aster(2)] = a + b x[(1)] y[aster(3)] = a + b x[(2)] ASTER Spectral range (µm) Band 2: , Red Band 1: , Red Band 3: , NIR Band 2: , NIR Spatial resolution (m)

9 Temporal coverage of satellite data ASTER ( ) ( ) ( ) ( ) 19/5/01 8/6/01 28/6/01 18/7/01 7/8/01 27/8/01 16/9/01 ( ) ( ) ( ) ( ) 19/5/02 8/6/02 28/6/02 18/7/02 7/8/02 27/8/02 16/9/02

10 Comparison of predicted and measured stand volume Predicted stand volume (m 3 ha 1 ) (2001) (2002) 1 : Measured stand volume (m 3 ha 1 ), NFI

11 Predicted biomass (trees + understorey vegetation)

12 Conclusions High resolution (15 m 15 m) ASTER data can be used as an intermediate step between ground reference data and coarse resolution (250 m 250 m) data. Data with both higher spatial and temporal resolution will be required to address biomass estimates. The mean biomass predicted with the coarse resolution satellite data such as can be used together with the information about the forest area quantified by other data source. Especially, the NFI provides accurate information about the forest area. Coarse resolution satellite data is not proper tool to estimate forest area.

13 Conclusions (cont.) Most of the forest biomass is in the trees, but a significant part is alsoin the understorey vegetation. The understorey has only rarely been considered in modeling Various remote sensing studies concerning forest biomass estimation have used plotwise measurements as ground reference data. The locational problems of plot-level ground reference data were solved by employing the forest stand data instead of the plot-level data. It does not make a difference if biomass conversion is done before or after the computing of satellite imagery. This indicates that the stand volume can be predicted as reliably as the biomass.

14 Conclusions (cont.) Results depend on the selected image Different images provide slightly different results

15 Articles Muukkonen, P. & J. Heiskanen (2005). Estimating biomass for boreal forests using ASTER satellite data combined with standwise forest inventory data. Remote Sensing of Environment 99: 4, Muukkonen, P. & J. Heiskanen (2006). Biomass estimation based on simultaneous use of standwise forest inventory data, ASTER and satellite data. Manuscript in preparation. Thank you!

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