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.

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17In countries like Argentina, whose economy depends heavily on crop production, 18 the estimation of harvests is an elementary requirement. Besides providing objectivity, the 19 use of remote sensing allows estimating yield in advance. Since the time of maximum leaf 20 area in wheat corresponds with the critical period of the crop, a good relationship is 21 expected between the Normalized Difference Vegetation Index (NDVI) and yield. The 22 present study was carried out in the North of Buenos Aires province, Argentina. Based on 23 the type of soil, the study area can be divided into two homogeneous subzones: a subzone 24 with lower clay content in the southwest and a subzone with higher clay content in the 25 northeast. Nine growing seasons (2003-2011) were studied. In the first five years, an 26 empirical model was calibrated and validated with field-observed wheat yields and 27 MOD13q1 product-NDVI data, whereas in the other four years, the calibrated model was 28 applied by means of yield maps and by comparing with official yields. The MOD13q1 image 29 corresponding to julian day 289 showed the best fit between NDVI and yield to estimate 30 wheat yield early. Through yield maps, better weather conditions showed higher yields and 31 higher soil productivity presented a greater proportion of the area occupied by higher 32 yields. At department level, an R 2 value of 0.75 was found after relating the estimation of 33 the calibrated empirical model with official yields. The method used allows predicting wheat 34 yield 30 days before harvest. Through yield maps, the NDVI perceived the temporal and 35 spatial variability in the study area.36 37

Plants, by influencing water fluxes across the ecosystem-vadose zone-aquifer continuum, can leave an imprint on salt accumulation and distribution patterns. We explored how the conversion of native grasslands to oak plantations affected the abundance and distribution of salts on soils and groundwater through changes in the water balance in naturally salt-affected landscapes of Hortobagy (Hungary), a region where artificial drainage performed approximately 150 years ago lowered the water table (from -2 to -5 m) decoupling it from the surface ecosystem. Paired soil sampling and detailed soil conductivity transects revealed consistently different salt distribution patterns between grasslands and plantations, with shallow salinity losses and deep salinity gains accompanying tree establishment. Salts accumulated in the upper soil layers during pre-drainage times have remained in drained grasslands but have been flushed away under tree plantations (65 and 83% loss of chloride and sodium, respectively, in the 0 to -0.5 m depth range) as a result of a five- to 25-fold increase in infiltration rates detected under plantations. At greater depth, closer to the current water table level, the salt balance was reversed, with tree plantations gaining 2.5 kg sodium chloride m(-2) down to 6 m depth, resulting from groundwater uptake and salt exclusion by tree roots in the capillary fringe. Diurnal water table fluctuations, detected in a plantation stand but not in the neighbouring grasslands, together with salt mass balances suggest that trees consumed approximately 380 mm groundwater per year, re-establishing the discharge regime and leading to higher salt accumulation rates than those interrupted by regional drainage practices more than a century ago. The strong influences of vegetation changes on water dynamics can have cascading consequences on salt accumulation and distribution, and a broad ecohydrological perspective that explicitly considers vegetation-groundwater links is needed to anticipate and manage them.

This paper presents results of the AQL2004 project, which has been develope within the GOFC-GOLD Latin American network of remote sensing and forest fires (RedLatif). The project intended to obtain monthly burned-land maps of the entire region, from Mexico to Patagonia, using MODIS (moderate-resolution imaging spectroradiometer) reflectance data. The project has been organized in three different phases: acquisition and preprocessing of satellite data; discrimination of burned pixels; and validation of results. In the first phase, input data consisting of 32-day composites of MODIS 500-m reflectance data generated by the Global Land Cover Facility (GLCF) of the University of Maryland (College Park, Maryland, U.S.A.) were collected and processed. The discrimination of burned areas was addressed in two steps: searching for "burned core" pixels using postfire spectral indices and multitemporal change detection and mapping of burned scars using contextual techniques. The validation phase was based on visual analysis of Landsat and CBERS (China-Brazil Earth Resources Satellite) images. Validation of the burned-land category showed an agreement ranging from 30% to 60%, depending on the ecosystem and vegetation species present. The total burned area for the entire year was estimated to be 153 215 km2. The most affected countries in relation to their territory were Cuba, Colombia, Bolivia, and Venezuela. Burned areas were found in most land covers; herbaceous vegetation (savannas and grasslands) presented the highest proportions of burned area, while perennial forest had the lowest proportions. The importance of croplands in the total burned area should be taken with reserve, since this cover presented the highest commission errors. The importance of generating systematic products of burned land areas for different ecological processes is emphasized.

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