Dr. Carlos M. Di Bella | Universidad de Buenos Aires (original) (raw)

Papers by Dr. Carlos M. Di Bella

Research paper thumbnail of -Uncertainties in fPAR estimation of grass canopies under different stress situations and differences in architecture

Research paper thumbnail of Forage Production of the Argentine Pampa Region Based on Land Use and Long-Term Normalized Difference Vegetation Index Data

Rangeland Ecology & Management, 2009

Research paper thumbnail of The effects of tree establishment on water and salt dynamics in naturally salt-affected grasslands

Oecologia, 2007

Plants, by influencing water fluxes across the ecosystem–vadose zone–aquifer continuum, can leave... more 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

Research paper thumbnail of A land cover map of South America

Global Change Biology, 2004

A digital land cover map of South America has been produced using remotely sensed satellite data ... more 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.

Research paper thumbnail of MONITOREO Y DETERMINACION DEL RIESGO DE INCENDIOS FORESTALES UTILIZANDO IMAGENES NOAA-AVHRR EN LA REGION PATAGONICA ARGENTINA

Summary In this last decade, the Patagonia Region was affected for fires that burned thousand of ... more Summary In this last decade, the Patagonia Region was affected for fires that burned thousand of hectares of native forests and natural grasslands. The climate conditions, characterized by a winter with a scarce snowy and a spring with insufficient precipitations, have increased blazes with greater frequency and intensity. The objective of the present work was to apply detection and monitoring

Research paper thumbnail of Monoterpene emissions from three Nothofagus species in Patagonia, Argentina

Journal of Plant Interactions, 2008

Isoprenoid emissions have key roles in plant biology and plant interactions with the environment.... more Isoprenoid emissions have key roles in plant biology and plant interactions with the environment. Global emission inventories of isoprenoid emissions still lack information from a large number species, especially from South American vegetation other than the rainforest ecosystem. A study was conducted to identify the basal emission of isoprenoid under field conditions from three Nothofagus species. The three Nothofagus species

Research paper thumbnail of Comparación de Técnicas de Clasificación de cultivos a partir de información Multi E Hyperespectral

… . 12. 2007 09 19-21, 19-21 …, 2007

Research paper thumbnail of Land cover classification in the Argentine Pampas using multi-temporal Landsat TM data

International Journal of Remote Sensing, 2003

The objective of this study was to explore the use of multi-temporal Landsat TM data from the sam... more 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.

Research paper thumbnail of Remote sensing capabilities to estimate pasture production in France

International Journal of Remote Sensing, 2004

ABSTRACT Pastures constitute an important terrestrial ecosystem. In France, pastures occupy 21% o... more ABSTRACT Pastures constitute an important terrestrial ecosystem. In France, pastures occupy 21% of the total area. A big effort is being made to develop a real-time systematic approach to estimate biomass production at a national level, focusing on spatial and seasonal variability in relation to drought. The absence of indirect low-cost methods that could be applied to large areas contributes to this situation. Advances in remote sensing and crop models offer new methodological and operative possibilities to solve this problem. In this paper, 13 forage regions (FR) in France were selected on the basis of their different geomorphologic, climatic and soil conditions with regard to pastoral production. Images from Systeme Probatoire de l'Observation de la Terre (SPOT) 4- VEGETATION were used to forecast productive variables estimated by the STICS-Prairie simulation model. In general terms, both satellite and productive data agreed properly. Particularly, the relationship between the middle infrared based vegetation index (SWVI) and the Leaf Area Index (LAI) demonstrated the best results whatever the FR. Results obtained confirm the capabilities of remote sensing data as an accurate predictor of productive variables estimated as from simulation models. Differences between satellite information and model estimations of pasture systems, especially during the harvesting periods, could be good indicators to improve model estimations at a regional scale as well.

Research paper thumbnail of Using VEGETATION satellite data and the crop model STICS-Prairie to estimate pasture production at the national level in France

Physics and Chemistry of the Earth, Parts A/B/C, 2005

In France, pastures constitute an important land cover type, sustaining principally husbandry pro... more In France, pastures constitute an important land cover type, sustaining principally husbandry production. The absence of lowcost methods applicable to large regions has conducted to the use of simulation models, as in the ISOP system. Remote sensing data may be considered as a potential tool to improve a correct diagnosis in a real time framework. Thirteen forage regions (FR) of France, differing in their soil, climatic and productive characteristics were selected for this purpose. SPOT4-VEGETATION images have been used to provide, using subpixel estimation models, the spectral signature corresponding to pure pasture conditions. This information has been related with some growth variables estimated by STICS-Prairie model (inside ISOP system). Beyond the good general agreement between the two types of data, we found that the best relations were observed between NDVI middle infrared based index (SWVI) and leaf area index. The results confirm the capacities of the satellite data to provide complementary productive variables and help to identify the spatial and temporal differences between satellite and model information, mainly during the harvesting periods. This could contribute to improve the evaluations of the model on a regional scale.

Research paper thumbnail of Fire patterns in north-eastern Argentina: influences of climate and land use/cover

International Journal of Remote Sensing, 2011

Fires are one of the most frequent disturbances on terrestrial ecosystems, thus making their unde... more Fires are one of the most frequent disturbances on terrestrial ecosystems, thus making their understanding and prediction crucial for their management. While the fuels condition are linked to well-known environmental factors, the ignition triggering agents are less understood and may display a more stochastic behaviour. We studied the regional relationship between the fire density and frequency, climate and land use/cover

Research paper thumbnail of Flooding: The effect of water depth on the spectral response of grass canopies

Journal of Hydrology, 2007

Vegetation indices generated from remotely sensed data have been widely used to estimate biophysi... more Vegetation indices generated from remotely sensed data have been widely used to estimate biophysical characteristics of natural vegetation and agricultural crops like aboveground productivity, leaf area index or absorption of the photosynthetically active radiation. ...

Research paper thumbnail of Use of SPOT4-VEGETATION satellite data to improve pasture production simulated by STICS included in the ISOP French system

Agronomie, 2004

In France, pastures represent a significant land-cover type, which mainly sustains husbandry prod... more In France, pastures represent a significant land-cover type, which mainly sustains husbandry production. For this reason, it is of great benefit to develop real-time monitoring of pasture biomass production, taking into account its spatial and temporal variability. The absence of low-cost methods applicable to large regions has oriented French stakeholders to the use of growth simulation models adequately informed through

Research paper thumbnail of Validation of the global land cover 2000 map

IEEE Transactions on Geoscience and Remote Sensing, 2000

The Joint Research Centre of the European Commission (JRC), in partnership with 30 institutions, ... more 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.

Research paper thumbnail of Effect of senescent leaves on NDVI-based estimates of f APAR: Experimental and modelling evidences

International Journal of Remote Sensing, 2004

Research paper thumbnail of Estimation of primary production of subhumid rangelands from remote sensing data

Applied Vegetation Science, 2000

Above-ground Net Primary Production (ANPP) is the main determinant of forage availability and hen... more Above-ground Net Primary Production (ANPP) is the main determinant of forage availability and hence of stocking density. A tool to track the seasonal and interannual changes in ANPP at the paddock level will be very important for livestock management. We studied the relationship between field ANPP data and the Normalized Difference Vegetation Index (NDVI) for rangelands of the Flooding Pampa of Argentina using spectral data provided by sensors on board of two satellites: NOAA/AVHRR and Landsat TM. The relationship between NDVI and ANPP was linear both for data derived from NOAA/AVHRR and Landsat TM. Changes in ANPP accounted for a large proportion of the temporal and spatial variation of NDVI: 71% of NOAA/AVHRR data and 74% of Landsat TM data. By inverting these models, ANPP may be inferred from NDVI data at a seasonal and paddock scale. NOAA/AVHRR data captured better the seasonal variation in ANPP and were less sensitive to local variations than Landsat TM data. In contrast, Landsat TM data were more sensitive to inter-site differences in primary production, except for the winter months. Thus, combining information from these two sources offers a good alternative for monitoring rangeland production at high temporal and spatial resolution.

Research paper thumbnail of GLOBAL BURNED-LAND ESTIMATION IN LATIN AMERICA USING MODIS COMPOSITE DATA

Ecological Applications, 2008

This paper presents results of the AQL2004 project, which has been developed within the GOFC-GOLD... more This paper presents results of the AQL2004 project, which has been developed 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, USA) 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 km 2 . 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.

Research paper thumbnail of Using remote sensing information and simulation models to estimate pastures production at the national scale

Pastures constitute an important terrestrial ecosystem. In France, pastures occupy 21% of the tot... more Pastures constitute an important terrestrial ecosystem. In France, pastures occupy 21% of the total area. There is a big effort to develop a real time systematic approach to estimate biomass production at the national level, focusing on spatial and seasonal variability in relation to drought. The non-existence of indirect methods of low cost that can be applied to large areas contributes to this situation. The advances registered in crop modeling and remote sensing offer new methodological and operative possibilities to solve this problem. In this work, thirteen Forage Regions (FR) of France were selected for their different geomorphologic, climatic and soil conditions with regard to pastoral productions. Images from the VEGETATION sensor on board SPOT4 satellite (1 km spatial resolution) were used to forecast some productive variables estimated by STICS Prairie simulation model. There was a general good agreement between the satellite and productive data. Particularly, the relation...

Research paper thumbnail of -Uncertainties in fPAR estimation of grass canopies under different stress situations and differences in architecture

Research paper thumbnail of Forage Production of the Argentine Pampa Region Based on Land Use and Long-Term Normalized Difference Vegetation Index Data

Rangeland Ecology & Management, 2009

Research paper thumbnail of The effects of tree establishment on water and salt dynamics in naturally salt-affected grasslands

Oecologia, 2007

Plants, by influencing water fluxes across the ecosystem–vadose zone–aquifer continuum, can leave... more 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

Research paper thumbnail of A land cover map of South America

Global Change Biology, 2004

A digital land cover map of South America has been produced using remotely sensed satellite data ... more 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.

Research paper thumbnail of MONITOREO Y DETERMINACION DEL RIESGO DE INCENDIOS FORESTALES UTILIZANDO IMAGENES NOAA-AVHRR EN LA REGION PATAGONICA ARGENTINA

Summary In this last decade, the Patagonia Region was affected for fires that burned thousand of ... more Summary In this last decade, the Patagonia Region was affected for fires that burned thousand of hectares of native forests and natural grasslands. The climate conditions, characterized by a winter with a scarce snowy and a spring with insufficient precipitations, have increased blazes with greater frequency and intensity. The objective of the present work was to apply detection and monitoring

Research paper thumbnail of Monoterpene emissions from three Nothofagus species in Patagonia, Argentina

Journal of Plant Interactions, 2008

Isoprenoid emissions have key roles in plant biology and plant interactions with the environment.... more Isoprenoid emissions have key roles in plant biology and plant interactions with the environment. Global emission inventories of isoprenoid emissions still lack information from a large number species, especially from South American vegetation other than the rainforest ecosystem. A study was conducted to identify the basal emission of isoprenoid under field conditions from three Nothofagus species. The three Nothofagus species

Research paper thumbnail of Comparación de Técnicas de Clasificación de cultivos a partir de información Multi E Hyperespectral

… . 12. 2007 09 19-21, 19-21 …, 2007

Research paper thumbnail of Land cover classification in the Argentine Pampas using multi-temporal Landsat TM data

International Journal of Remote Sensing, 2003

The objective of this study was to explore the use of multi-temporal Landsat TM data from the sam... more 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.

Research paper thumbnail of Remote sensing capabilities to estimate pasture production in France

International Journal of Remote Sensing, 2004

ABSTRACT Pastures constitute an important terrestrial ecosystem. In France, pastures occupy 21% o... more ABSTRACT Pastures constitute an important terrestrial ecosystem. In France, pastures occupy 21% of the total area. A big effort is being made to develop a real-time systematic approach to estimate biomass production at a national level, focusing on spatial and seasonal variability in relation to drought. The absence of indirect low-cost methods that could be applied to large areas contributes to this situation. Advances in remote sensing and crop models offer new methodological and operative possibilities to solve this problem. In this paper, 13 forage regions (FR) in France were selected on the basis of their different geomorphologic, climatic and soil conditions with regard to pastoral production. Images from Systeme Probatoire de l'Observation de la Terre (SPOT) 4- VEGETATION were used to forecast productive variables estimated by the STICS-Prairie simulation model. In general terms, both satellite and productive data agreed properly. Particularly, the relationship between the middle infrared based vegetation index (SWVI) and the Leaf Area Index (LAI) demonstrated the best results whatever the FR. Results obtained confirm the capabilities of remote sensing data as an accurate predictor of productive variables estimated as from simulation models. Differences between satellite information and model estimations of pasture systems, especially during the harvesting periods, could be good indicators to improve model estimations at a regional scale as well.

Research paper thumbnail of Using VEGETATION satellite data and the crop model STICS-Prairie to estimate pasture production at the national level in France

Physics and Chemistry of the Earth, Parts A/B/C, 2005

In France, pastures constitute an important land cover type, sustaining principally husbandry pro... more In France, pastures constitute an important land cover type, sustaining principally husbandry production. The absence of lowcost methods applicable to large regions has conducted to the use of simulation models, as in the ISOP system. Remote sensing data may be considered as a potential tool to improve a correct diagnosis in a real time framework. Thirteen forage regions (FR) of France, differing in their soil, climatic and productive characteristics were selected for this purpose. SPOT4-VEGETATION images have been used to provide, using subpixel estimation models, the spectral signature corresponding to pure pasture conditions. This information has been related with some growth variables estimated by STICS-Prairie model (inside ISOP system). Beyond the good general agreement between the two types of data, we found that the best relations were observed between NDVI middle infrared based index (SWVI) and leaf area index. The results confirm the capacities of the satellite data to provide complementary productive variables and help to identify the spatial and temporal differences between satellite and model information, mainly during the harvesting periods. This could contribute to improve the evaluations of the model on a regional scale.

Research paper thumbnail of Fire patterns in north-eastern Argentina: influences of climate and land use/cover

International Journal of Remote Sensing, 2011

Fires are one of the most frequent disturbances on terrestrial ecosystems, thus making their unde... more Fires are one of the most frequent disturbances on terrestrial ecosystems, thus making their understanding and prediction crucial for their management. While the fuels condition are linked to well-known environmental factors, the ignition triggering agents are less understood and may display a more stochastic behaviour. We studied the regional relationship between the fire density and frequency, climate and land use/cover

Research paper thumbnail of Flooding: The effect of water depth on the spectral response of grass canopies

Journal of Hydrology, 2007

Vegetation indices generated from remotely sensed data have been widely used to estimate biophysi... more Vegetation indices generated from remotely sensed data have been widely used to estimate biophysical characteristics of natural vegetation and agricultural crops like aboveground productivity, leaf area index or absorption of the photosynthetically active radiation. ...

Research paper thumbnail of Use of SPOT4-VEGETATION satellite data to improve pasture production simulated by STICS included in the ISOP French system

Agronomie, 2004

In France, pastures represent a significant land-cover type, which mainly sustains husbandry prod... more In France, pastures represent a significant land-cover type, which mainly sustains husbandry production. For this reason, it is of great benefit to develop real-time monitoring of pasture biomass production, taking into account its spatial and temporal variability. The absence of low-cost methods applicable to large regions has oriented French stakeholders to the use of growth simulation models adequately informed through

Research paper thumbnail of Validation of the global land cover 2000 map

IEEE Transactions on Geoscience and Remote Sensing, 2000

The Joint Research Centre of the European Commission (JRC), in partnership with 30 institutions, ... more 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.

Research paper thumbnail of Effect of senescent leaves on NDVI-based estimates of f APAR: Experimental and modelling evidences

International Journal of Remote Sensing, 2004

Research paper thumbnail of Estimation of primary production of subhumid rangelands from remote sensing data

Applied Vegetation Science, 2000

Above-ground Net Primary Production (ANPP) is the main determinant of forage availability and hen... more Above-ground Net Primary Production (ANPP) is the main determinant of forage availability and hence of stocking density. A tool to track the seasonal and interannual changes in ANPP at the paddock level will be very important for livestock management. We studied the relationship between field ANPP data and the Normalized Difference Vegetation Index (NDVI) for rangelands of the Flooding Pampa of Argentina using spectral data provided by sensors on board of two satellites: NOAA/AVHRR and Landsat TM. The relationship between NDVI and ANPP was linear both for data derived from NOAA/AVHRR and Landsat TM. Changes in ANPP accounted for a large proportion of the temporal and spatial variation of NDVI: 71% of NOAA/AVHRR data and 74% of Landsat TM data. By inverting these models, ANPP may be inferred from NDVI data at a seasonal and paddock scale. NOAA/AVHRR data captured better the seasonal variation in ANPP and were less sensitive to local variations than Landsat TM data. In contrast, Landsat TM data were more sensitive to inter-site differences in primary production, except for the winter months. Thus, combining information from these two sources offers a good alternative for monitoring rangeland production at high temporal and spatial resolution.

Research paper thumbnail of GLOBAL BURNED-LAND ESTIMATION IN LATIN AMERICA USING MODIS COMPOSITE DATA

Ecological Applications, 2008

This paper presents results of the AQL2004 project, which has been developed within the GOFC-GOLD... more This paper presents results of the AQL2004 project, which has been developed 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, USA) 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 km 2 . 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.

Research paper thumbnail of Using remote sensing information and simulation models to estimate pastures production at the national scale

Pastures constitute an important terrestrial ecosystem. In France, pastures occupy 21% of the tot... more Pastures constitute an important terrestrial ecosystem. In France, pastures occupy 21% of the total area. There is a big effort to develop a real time systematic approach to estimate biomass production at the national level, focusing on spatial and seasonal variability in relation to drought. The non-existence of indirect methods of low cost that can be applied to large areas contributes to this situation. The advances registered in crop modeling and remote sensing offer new methodological and operative possibilities to solve this problem. In this work, thirteen Forage Regions (FR) of France were selected for their different geomorphologic, climatic and soil conditions with regard to pastoral productions. Images from the VEGETATION sensor on board SPOT4 satellite (1 km spatial resolution) were used to forecast some productive variables estimated by STICS Prairie simulation model. There was a general good agreement between the satellite and productive data. Particularly, the relation...