Skip to main content
U.S. flag

An official website of the United States government

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

Skip to content

LBA-ECO LC-23 Characterization of Vegetation Fire Dynamics for Brazil: 2001-2003

Metadata Updated: December 6, 2023

Satellite fire detection was determined from two sensors, the Advanced Very High Resolution Radiometer (AVHRR) on NOAA-12 and the Moderate Resolution Imaging Spectroradiometer (MODIS) on both the Terra and Aqua platforms, for 2001- 2003 to characterize fire activity in Brazil, giving special emphasis to the Amazon region. Active fire data for AVHRR/NOAA-12 was produced using a fixed threshold fire detection technique based on the algorithm developed by the Centro de Previsao do Tempo e Estudos Climaticos (CPTEC/INPE) (Setzer and Pereira, 1991; Setzer et al., 1994; Setzer and Malingreau, 1996). Active fire data for MODIS/Terra and MODIS/Aqua was produced using a contextual fire detection technique based on NASA-University of Maryland algorithm (Justice et al., 2003; Giglio et al.2003).Resulting fire counts were compared for major biomes of Brazil (Figure 1), the nine states of the Legal Amazon (e.g., Tocantins, Figure 2), and two important road corridors in the Amazon region (Figure 3). In evaluating the daily fire counts, there is a dependence on variations in satellite viewing geometry, overpass time, atmospheric conditions, and fire characteristics (Schroeder et al., 2005). The data provided are the coordinates of daily active vegetation fires in Brazil for 2001 through 2003 at 1km resolution for both AVHRR and MODIS sensors. Data are provided in both Arcview (shape file format) and ASCII comma separated file formats. Vector files for the major biomes of Brazil, the nine states of the Legal Amazon, and two important road corridors in the Amazon region are also included.

Access & Use Information

Public: This dataset is intended for public access and use. License: No license information was provided. If this work was prepared by an officer or employee of the United States government as part of that person's official duties it is considered a U.S. Government Work.

Downloads & Resources

Dates

Metadata Created Date October 25, 2023
Metadata Updated Date December 6, 2023

Metadata Source

Harvested from NASA Data.json

Graphic Preview

Browse Image

Additional Metadata

Resource Type Dataset
Metadata Created Date October 25, 2023
Metadata Updated Date December 6, 2023
Publisher ORNL_DAAC
Maintainer
Identifier C2784831948-ORNL_CLOUD
Data First Published 2023-10-15
Language en-US
Data Last Modified 2023-10-17
Category LBA-ECO, geospatial
Public Access Level public
Bureau Code 026:00
Metadata Context https://project-open-data.cio.gov/v1.1/schema/catalog.jsonld
Metadata Catalog ID https://data.nasa.gov/data.json
Schema Version https://project-open-data.cio.gov/v1.1/schema
Catalog Describedby https://project-open-data.cio.gov/v1.1/schema/catalog.json
Citation Schroeder, W., J.T. Morisette, I.A. Csiszar, L. Giglio, D.C. Morton, and C.O. Justice. 2006. LBA-ECO LC-23 Characterization of Vegetation Fire Dynamics for Brazil: 2001-2003. ORNL DAAC, Oak Ridge, Tennessee, USA. http://dx.doi.org/10.3334/ORNLDAAC/843
Graphic Preview Description Browse Image
Graphic Preview File https://daac.ornl.gov/graphics/browse/project/square/lba_logo_square.png
Harvest Object Id 821208f4-95c0-45f8-b1b0-353e31c31277
Harvest Source Id 58f92550-7a01-4f00-b1b2-8dc953bd598f
Harvest Source Title NASA Data.json
Homepage URL https://doi.org/10.3334/ORNLDAAC/843
Metadata Type geospatial
Old Spatial -74.0 -33.75 -34.8 5.3
Program Code 026:001
Source Datajson Identifier True
Source Hash efb07f0509923b6c3731eeacba7aad57cfac17c5810ee5681439daae913d38bf
Source Schema Version 1.1
Spatial
Temporal 2001-01-01T00:00:00Z/2003-12-31T23:59:59Z

Didn't find what you're looking for? Suggest a dataset here.