Landscapes Forest and Global Change - ESA - Escola Superior ...

H.R. Ratsimba et al. 2010. Multi-scale analysis of carbon stocks and deforestation monitoring
400
humid forest with SPOT 5 image. Their remote sensing analysis was combined with biomass
inventory relating the difference between the carbon stocks between the two classes. It also
demonstrates that this situation was possible at small scale analysis (SPOT images cover about
60 km * 60 km area). However, it is not always possible to cover the whole country with SPOT
image (problem of cost) for the change monitoring. In this way, this research is dealing with
lower resolution image in the South East part of Madagascar as test region (see Figure 1):
- a preclassification is realized on a Landast-7 ETM+ 2005 image to have the different forest
type according an a priori classification : “low degraded forest” and “degraded forest”. The
other land use is only put in a “non forest” class including the different secondary formations,
- a biomass inventory through Rakoto Ratsimba et al. (2010) methods is realized with a local
allometric equation establishment (through tree based sampling and wood density analysis) and
a randomized plot sampling (see Figure 1),
Figure 1: Test site (left) and distribution of the biomass inventory plots (right)
Landsat 7 ETM+ 2005, composite image RGB: 4 – 2 – 1
Projection: Laborde (Hotine Mercator Oblique) – Ellipsoïde International 1924
- a correlation between the biomass plot stock and value of vegetation indices is set up. In fact,
this correlation is not possible with Landsat image because of sensor problems (black pixels
throughout the image). Thus, Normalized Difference Vegetation Index (NDVI) combined with
the Enhanced Vegetation Index (EVI) of Moderate Resolution Imaging Spectroradiometer
(MODIS) Image (see Figure 2) are derived from the same period of the biomass inventory
(2009). The Figure 2 summarizes the research approach.
3. Result
3.1. Forest biomass stock variation
The assessment of carbon stocks in the field shows that due to the accuracy of the stratification,
the biomass stock is very low (4 t/ha) but can reach over 500 t/ha (at plot scale). It shows that
the above-ground biomass estimate uncertainty is attributed to stratification error in this phase
of the methodology. It is related to the spatial resolution of Landsat and the time period
difference between the image (2005) and the biomass inventory (2009). In fact, the distribution
of the points in the Figure 4 illustrates that the vegetation indices have not significant variations
and gives the default value for the classification of NDVI and or EVI image.
Thus, assessing above-ground biomass using vegetation indices derived from MODIS image
proved that monitoring carbon at large scale is possible. The Figure 5 shows the map derived
from the combined classification from EVI and NDVI. Data from the fields indicate that this
map is corresponding to forest that has 126 ± 12 t/ha stocks of carbon.
Forest Landscapes and Global Change-New Frontiers in Management, Conservation and Restoration. Proceedings of the IUFRO Landscape Ecology
Working Group International Conference, September 21-27, 2010, Bragança, Portugal. J.C. Azevedo, M. Feliciano, J. Castro & M.A. Pinto (eds.)
2010, Instituto Politécnico de Bragança, Bragança, Portugal.