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This paper outlines the methods and results for monitoring forest change and resulting carbon emissions for the 1990-2000 and 200-2005 periods carried out over tropical Central and South America. To produce our forest change estimates we used a systematic sample of medium resolution satellite data processed to forest change maps covering 1230 sites of 20 km by 20 km, each located at the degree confluence. Biomass data were spatially associated to each individual sample site so that annual carbon emissions could be estimated. For our study area we estimate that forest cover in the study area had fallen from 763 Mha (s.e. 10 Mha) in 1990 to 715 Mha (s.e. 10 Mha) in 2005. During the same period other wooded land (i.e., non-forest woody vegetation) had fallen from 191 Mha (s.e. 5.5 Mha) to 184 Mha (s.e. 5.5 Mha). This equates to an annual gross loss of 3.74 Mha·y-1 of forests (0.50% annually) between 1990 and 2000, rising to 4.40 Mha·y-1 in the early 2000s (0.61% annually), with Brazil accounting for 69% of the total losses. The annual carbon emissions from the combined loss of forests and other wooded land were calculated to be 482 MtC·y-1 (s.e. 29 MtC·y-1) for the 1990s, and 583 MtC·y-1 (s.e. 48 MtC·y-1) for the 2000 to 2005 period. Our maximum estimate of sinks from forest regrowth in tropical South America is 92 MtC·y-1. These estimates of gross emissions correspond well with the national estimates reported by Brazil, however, they are less than half of those reported in a recent study based on the FAO country statistics, highlighting the need for continued research in this area. [ABSTRACT FROM AUTHOR]

This paper focuses on the Ice, Cloud and land Elevation Satellite (ICESat) Geoscience Laser Altimeter System (GLAS) data availability over the 2 million km2 Cerrado, the Brazilian central savanna biome and one of the world's biodiversity hotspots. Overall, about 2.5 million laser shots, distributed along the seven years of ICESat operation (2003-2009) and comprising three major seasonal domains, were acquired, from which, 206,026 and 176,035 screened footprints are coincident with the remnant vegetation and cultivated pasture areas (the dominant land-use form in the Cerrado). Although these points are well distributed over the entire Cerrado, the ICESat track data collection results in substantial data gaps. In relation to the 15,612 Cerrado watersheds (6th order Otto basin system), 8,369 and 4,415 watersheds are completely deprived of data points over their remnant vegetation and pasture covers, respectively. Light Detection and Ranging (LIDAR) availability was also evaluated in relation to specific targets of interest, including both fully-protected conservation units as well as areas impacted by fire and deforestation. In spite of the very few occurrences, our assessments indicate that enough LIDAR data is available for retrieving structural and functional properties of a variety of Cerrado physiognomies, as well as to assess how these physiognomies respond to anthropogenic induced changes. In fact, the comprehensive data availability analysis conducted in this study corroborate the potential of GLAS LIDAR waveforms for the retrieval of biophysical properties at both local and regional scales, particularly concerning remnant carbon stocks and pasture conditions, key information for the conservation of the fast-changing and severely threatened Cerrado. [ABSTRACT FROM AUTHOR]

The analysis of rapid environment changes requires orbital sensors with high frequency of data acquisition to minimize cloud interference in the study of dynamic processes such as Amazon tropical deforestation. Moreover, a medium to high spatial resolution data is required due to the nature and complexity of variables involved in the process. In this paper we describe a multiresolution multitemporal technique to simulate Landsat 7 Enhanced Thematic Mapper Plus (ETM+) image using Terra Moderate Resolution Imaging Spectroradiometer (MODIS). The proposed method preserves the spectral resolution and increases the spatial resolution for mapping Amazon Rainfores deforestation using low computational resources. To evaluate this technique, sample images were acquired in the Amazon rainforest border (MODIS tile H12-V10 and ETM+/Landsat 7 path 227 row 68) for 17 July 2002 and 05 October 2002. The MODIS-based simulated ETM+ and the corresponding original ETM+ images were compared through a linear regression method. Additionally, the bootstrap technique was used to calculate the confidence interval for the model to estimate and to perform a sensibility analysis. Moreover, a Linear Spectral Mixing Model, which is the technique used for deforestation mapping in Program for Deforestation Assessment in the Brazilian Legal Amazonia (PRODES) developed by National Institute for Space Research (INPE), was applied to analyze the differences in deforestation estimates. The results showed high correlations, with values between 0.70 and 0.94 (p < 0.05, student's t test) for all ETM+ bands, indicating a good assessment between simulated and observed data (p < 0.05, Z-test). Moreover, simulated image showed a good agreement with a reference image, originating commission errors of 1% of total area estimated as deforestation in a sample area test. Furthermore, approximately 6% or 70 km2 of deforestation areas were missing in simulated image classification. Therefore, the use of Landsat simulated image provides better deforestation estimation than MODIS alone. [ABSTRACT FROM AUTHOR]