The sampling protocol adopted during a field campaign at an Alpine meadow site (Shandan site), during July 2002 is
based on the so-called "Valeri" protocol (VALERI). The field campaign LAI measurements in Shandan are scaled up to
30×30 m2 raster maps based on Landsat ETM+ imagery. Regression analysis is applied to construct empirical transfer
functions for the determination of Leaf Area Index (LAI) raster imagery from ETM+ Normalized Difference Vegetation
Index (NDVI) and Simple Ratio (SR) data. Subsequently, the scaling up of the LAI raster maps is performed by the
aggregation of the 30x30 m2 data into 1×1 km2 pixels by calculating the average LAI values for the low resolution pixels.
The up-scaled data are used to validate the MODIS LAI product at the Shandan site. A power regression model
(LAI=2.3758*NDVI3.5216, R2=0.66, P<0.01), established between field measured LAI and ETM+ NDVI, elicits a high
statistical significance. A linear regression model (LAI=0.1798*SR-0.3574, R2=0.55, P<0.01) is established between
field measured LAI and ETM+ SR. The MODIS LAI product correlates best with the ETM+ LAI transfer function
obtained with NDVI data. Its R2 reaches 0.46, its slope 0.97, but the intercept is 0.7, which suggests that MODIS LAI is
systematically underestimated. The results illustrate that LAI measured with a LAI-2000 instrument at the VALERI
Shandan site leads to an underestimation of the MODIS LAI product. A plausible cause for the systematic
underestimation related with the LAI field measurements is discussed.
An accurate land cover mapping is a prerequisite to run all biospheric models. In this paper, NDVI (Normalized Difference Vegetation Index) and NDWI (Normalized Difference Water Index) time-series of data sets derived from 1-km SPOT/VEGETATION products were used to compile the land cover map of northwest China. The unsupervised classification technique of ISODATA was applied to classify the land cover classification system. With the assumption of the 1:100000 land use map of northwest China interpreted from TM images as the truth, the accuracy of the SPOT/VEGETATION land cover map was evaluated by validating 47 sampling units randomly selected in the whole mapping region. Each sample is a square unit of 25km´25km. The validation results showed an approving accuracy of the land cover map of northwest China. In addition, the combination of NDVI and NDWI vegetation indexes is an effective method on large regional land cover mapping. Meanwhile, three major problems are addressed for explaining the reasons that influence the accuracy of land cover mapping in this region
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