A digital land cover map of South America has been produced using remotely sensed satellite data acquired between 1995 and the year 2000. The mapping scale is defined by the 1 km spatial resolution of the map grid‐cell. In order to realize the product, different sources of satellite data were used, each source providing either a particular parameter of land cover characteristic required by the legend, or mapping a particular land cover class. The map legend is designed both to fit requirements for regional climate modelling and for studies on land cover change. The legend is also compatible with a wider, global, land cover mapping exercise, which seeks to characterize the world's land surface for the year 2000. As a first step, the humid forest domain has been validated using a sample of high‐resolution satellite images. The map demonstrates both the major incursions of agriculture into the remaining forest domains and the extensive areas of agriculture, which now dominate South America's grasslands.

The Joint Research Centre of the European Commission (JRC), in partnership with 30 institutions, has produced a global land cover map for the year 2000, the GLC 2000 map. The validation of the GLC2000 product has now been completed. The accuracy assessment relied on two methods: a confidence-building method (quality control based on a comparison with ancillary data) and a quantitative accuracy assessment based on a stratified random sampling of reference data. The sample site stratification used an underlying grid of Landsat data and was based on the proportion of priority land cover classes and on the landscape complexity. A total of 1265 sample sites have been interpreted. The first results indicate an overall accuracy of 68.6%. The GLC2000 validation exercise has provided important experiences. The design-based inference conforms to the CEOS Cal-Val recommendations and has proven to be successful. Both the GLC2000 legend development and reference data interpretations used the FAO Land Cover Classification System (LCCS). Problems in the validation process were identified for areas with heterogeneous land cover. This issue appears in both in the GLC2000 (neighborhood pixel variations) and in the reference data (cartographic and thematic mixed units). Another interesting outcome of the GLC2000 validation is the accuracy reporting. Error statistics are provided from both the producer and user perspective and incorporates measures of thematic similarity between land cover classes derived from LCCS

The objective of this study was to explore the use of multi-temporal Landsat TM data from the same growing season for the classification of land cover types in the south-western portion of the Argentine Pampas. Investigations were made on how many dates are necessary to obtain an accurate classification and, given a fixed number of dates, which is the particular combination of dates that yield the best results. Additionally, the effect of using the NDVI instead of all the bands available on the classification accuracy and the use of a moving window filter over the classified image were tested. Scenes acquired in spring, early summer, late summer and early fall of the 1996-1997 growing season were used. Land cover information for the same period was collected from farms and ranches and this information was included in a GIS. Supervised classifications were performed using all the 15 possible ways to combine the four dates. At least two scenes are needed for a satisfactory classification. These scenes must embrace the shift between winter and summer crops (i.e. one spring and one summer image). Using the NDVI instead of Landsat TM bands 3, 4 and 5 increased the biological interpretability of the results but caused a decrease in accuracy.

Spectral indices from remotely sensed data, such as the Normalized Difference Vegetation Index (NDVI), are often used to estimate biophysical characteristics of vegetation. The objective of this study is to evaluate the effect of senescent leaves on the estimation of the fraction of photosynthetically active radiation absorbed by the green elements of the canopy (fAPAR _g ) from NDVI measurements. An experiment was conducted under controlled conditions over grass canopies. Both NDVI and fAPAR _g were measured when the cover fraction by senescent leaves was changed. The results demonstrated that the effect of senescent leaves was significant on NDVI values. A similar effect was observed on the fAPAR _g values. In these conditions, simple models were developed to relate the fAPAR _g to NDVI values when the cover fractions of the senescent leaves vary. When combining these models, a linear relationship was found between NDVI and fAPAR _g , which was in good agreement with our experimental observations. Complementary radiative transfer model simulations were then run and confirmed these results. In addition, the vertical and horizontal distribution of the senescent leaves was investigated. They show that the relationship between NDVI and fAPAR _g was only marginally affected by the distribution of the senescent leaves.