Large-Scale Biosphere-Atmosphere Experiment (LBA)
Datasets for Amazonia and the Cerrado
This collection of Amazonian datasets assembled with funding from the National Aeronautics and Space Agency (NASA). This project was conducted in anticipation of the Large-Scale Biosphere Atmosphere Experiment (LBA), an international research effort led by Brazil. The LBA home page is maintained by the Brazilian weather and climate agency CPTEC (Centro de Previsão de Tempo e Estudos Climáticos) with a US LBA mirror site maintained at Oak Ridge National Laboratory (ORNL).
The science questions addressed by LBA include:
- How does Amazonia currently function as a regional entity?
- How will changes in land use and climate affect the biological, chemical, and physical functions of Amazonia, including the sustainability of development in the region and the influence of Amazonia on global climate?
An ecologically focused portion of the LBA effort has been funded by NASA. This portion has as its science question, the following:
- How do tropical forest conversion, re-growth, and selective logging influence carbon storage, nutrient dynamics, trace gas fluxes, and the prospect for sustainable land use in Amazonia?
These datasets are intended to facilitate both the LBA research as well as other studies that require spatially-explicit datasets for this tropical forest formation.
The datasets presented here were assembled by The Woods Hole Research Center in collaboration with the following institutions: Instituto de Pesquisa Ambiental da Amazônia (Amazonian Institute for Environmental Research, IPAM), Pennsylvania State University, Instituto de Homem e do Meio Ambiente da Amazônia (The Amazonian Institute for Man and the Environment, IMAZON), Empresa Brasileira de Pesquisa Agropecuária/Centro de Pesquisa Agropecuária do Cerrado (Brazilian Agricultural Research Agency/Center for Agricultural Research of the Cerrado, EMBRAPA/CPAC), Instituto Nacional de Pesquisas Espaciais (National Institute of Space Research, INPE), and Universidade de Brasilia (University of Brasilia, UNB).
Funding for this project was provided by NASA through grant HPUSP#884, MTPE Number 5303-TE/95-0059 to The Woods Hole Research Center.
Datasets Acquired from Non-Brazilian Sources
- Composited Normalized Difference Vegetation Index, including:
16 km ndvi data from the noaa avhrr satellites in weekly time steps from the period 1982-1994 (Source: Dataset ID: GNV28, UNEP/GRID, Geneva). metadata (pdf) / data 8 km NDVI data from the NOAA AVHRR satellites in weekly time steps from the period 1982-1994 (Source: Landsat AVHRR Pathfinder, NASA/GSFC website). metadata (pdf) / data
1 km NDVI data from the NOAA AVHRR satellites in monthly time steps from the period April 1992-March 1993 (Source: Global Land Cover Characterization, USGS/EROS Data Center website). metadata (pdf) / data
- Soil Map of Brazil (IBGE, 1981) (Source: Dataset from UNEP/GRID, Sioux Falls ftp site). metadata (pdf) / data
- Vegetation Map of Brazil (IBGE, 1988) (Source: Dataset from UNEP/GRID, Sioux Falls ftp site). metadata (pdf) / data
- A Map of the Vegetation of South America Based on Satellite Imagery (1992) (Source: Stone et al., The Woods Hole Research Center, Woods Hole, MA). metadata (pdf) / data
Datasets Acquired from Brazilian Sources
- Fire Count Images (Source: A. Setzer, INPE, Brazil).
These data contain weekly cumulative fire counts from analyses of AVHRR data from NOAA 12 and 14 in grid cells of 0.5 degrees of latitude by 0.5 degrees of longitude arranged in a matrix covering from 7 deg N to 40 deg S and from 75 deg W to 34.5 deg W for 1994-1997. metadata (pdf) / data
- Land Cover Evaluation of the State of Tocantins, Brazil (Source: EMBRAPA-CPAC/UnB, Brazil).
Eduardo Assad (EMBRAPA-CPAC) and Carlos Klink (UnB) have completed Landsat TM-based mapping of areas of native cerrado vegetation conversion for southern Maranhão State and Tocantins. The digitized maps of cerrado conversion are available here for the State of Tocantins. Assad has also done conversion/deforestation mapping for Mata Grosso, Goias, and Southern Pará. Some of these maps may also be available for LBA. metadata (pdf) / data
- Industrial Mining (Source: IPAM, Brazil/WHRC, USA).
One of the most important human activities in Amazonia is industrial mining. The areal extent of active mine sites in the region is quite small, totalling less than 50,000 hectares, the size of a single large ranch. However, the influence of industrial mines on land-use in Amazonia goes far beyond the area of direct impact, for they can exert a strong influence on the construction of roads, the development of electricity networks, and the migration patterns of the Amazon labor. Knowledge of the current distribution of mines, and the plans that are being made for new mines, is needed to predict the course of frontier expansion in Amazonia.The Woods Hole Research Center, in collaboration with the Amazon Institute of Environmental Research (Instituto de Pesquisa Ambiental da Amazônia, IPAM), has assembled data from the Brazilian National Department of Mineral Production (Departamento Nacional de Produção Mineral, DNPM) on the requests for mineral exploration and for mine construction in the following states of the Brazilian Amazon: Acre, Amapá, Amazônas, Pará, Rondônia, and Roraima. Data were not available for the states of Tocantins, Mato Grosso and Maranhão. metadata (pdf)
- Soil Profiles of Amazonia (Source: IPAM, Brazil/WHRC, USA).
We are releasing soil profile descriptions for 1168 locations throughout Brazilian Amazonia. These data are primarily based on RADAMBRASIL surveys. metadata (pdf) / data
The Amazon Scenarios project was initiated in 1998 by the Woods Hole Research Center and the Amazon Institute for Environmental Research (IPAM). It has been built on the premise that a comprehensive strategy for conserving the Amazon rainforest will depend upon rapid advances in understanding of the linkages between Amazon forests, its climate, and its economies. The goal is to simulate the responses of land use, forests, climate, biodiversity and watersheds to policy interventions and to each other, providing an integrated scientific framework for supporting conservation and sustainable development. Collaborators actively apply findings to regional conservation and development planning processes underway along the region’s new highway arteries, and are committed to supporting conservation activities generally across the Basin.
This collection of Pan Amazonian datasets was produced in 2001 through a project titled the “Foundations for a Sustainable Future: Scenarios for the Development of the Amazon Basin”, a collaborative venture among WHRC, IPAM, Center for Applied Biodiversity Science of Conservation International, and Instituto Nacional de Pesquisas Espaciais (National Institute of Space Research, INPE), using their own data and contributions by many other organizations. The main intent of this effort was to integrate studies that documented social, economic, and ecological effects of different policies, infrastructure investments, and land uses via GIS to produce a Pan Amazonian model for predicting social, economic, biological and ecological effects of different infrastructure and policy scenarios.
One of the intended deliverables of this joint work was a publicly-accessible database of geographic data for modeling development actions in the Pan Amazon region. All datasets presented here are packed into GZIPed and TARed files; all long filenames have been preserved. Within each archive are ArcView shapefile or grid formatted data, as well as a respective metadata file; the metadata file format is compliant with the BCIS (Biodiversity Conservation Information System) standard. Contact information was correct at time of publication. However, current contact information is as follows:
Paul Lefebvre, Research Associate
All data are in geographic projection (unless otherwise noted in the metadata) and use WGS84 datum.
Funding for the preparation of these data was provided by the Center for Applied Biodiversity Science of Conservation International to the Woods Hole Research Center.