Revision Date: August 7, 2014
This data set provides Normalized Difference Vegetation Index (NDVI) composite images of the Amazon Basin for the years 1999-2000 at approximately1-km spatial resolution. The images were from the VEGETATION 1 sensor, aboard the SPOT 4 satellite.
Ten day composite images were reprocessed through several filters for cloud removal. Monthly NDVI data were used to create five metrics: maximum NDVI, minimum of 6 greenest months, range of NDVI between min and max, mean NDVI dry months, and mean NDVI wet months.
There are five GeoTIFF (.tif) files with this data set.
Cite this data set as follows:
Saatchi, S., M. Steinenger, C.J. Tucker, B. Nelson, and M. Simard. 2014. LBA-ECO LC-15 NDVI Composite Images of the Amazon Basin: 1999-2000. Data set. Available on-line [http://daac.ornl.gov] from Oak Ridge National Laboratory Distributed Active Archive Center, Oak Ridge, Tennessee, USA. http://dx.doi.org/10.3334/ORNLDAAC/1239
The LBA Data and Publication Policy [http://daac.ornl.gov/LBA/lba_data_policy.html] is in effect for a period of five (5) years from the date of archiving and should be followed by data users who have obtained LBA data sets from the ORNL DAAC. Users who download LBA data in the five years after data have been archived must contact the investigators who collected the data, per provisions 6 and 7 in the Policy.
This data set was archived in August 2014. Users who download the data between August 2014 and September 2019 must comply with the LBA Data and Publication Policy.
Data users should use the Investigator contact information in this document to communicate with the data provider.
Data users should use the Data Set Citation and other applicable references provided in this document to acknowledge use of the data.
Activity: Regional Vegetation Variables
LBA Science Component: Land Use and Land Cover
Team ID: LC-15 (Saatchi / Alvala)
The investigator was Dr. Sassan S.Saatchi. You may contact Dr Saatchi at (Saatchi@congo.jpl.nasa.gov).
LBA Data Set Inventory ID: LC15_SPOT_Metrics
This data set provides Normalized Difference Vegetation Index (NDVI) composite images for the Amazon Basin for the years 1999-2000. The images were from the VEGETATION 1 sensor, aboard the SPOT 4 satellite. Ten day composites NDVI image data covering the Amazon basin for two years were reprocessed through several filters for cloud removal and monthly NDVI data were used to create five metrics: maximum NDVI, minimum of 6 greenest months, range of NDVI between min and max, mean NDVI dry months, and mean NDVI wet months.
There are five GeoTIFF (.tif) files of NDVI composite images at approximately 1-km spatial resolution. The images depict Maximum NDVI, Minimum of 6 greenest months, Range of NDVI between Min and Max, Mean NDVI Dry Months, and Mean NDVI Wet Months.
Each file contains one NDVI metric indicated by number in the file name:
1. amazon_ndvi_metric1.tif: Maximum NDVI
2. amazon_ndvi_metric2.tif: Minimum NDVI of 6 greenest months
3. amazon_ndvi_metric3.tif: Range of NDVI between Min and Max
4. amazon_ndvi_metric4.tif: Mean NDVI Dry Months
5. amazon_ndvi_metric5.tif: Mean NDVI Wet Months
Spatial Data Properties
Spatial Representation Type: Raster
Pixel Depth: 8 bit
Pixel Type: unsigned integer
Compression Type: LZW
Number of Bands: 1
Band Information: Landsat Band
Raster Format: TIFF
Source Type: continuous
No Data Value: none
Scale Factor: none
Number Columns: 5900
Column Resolution: 0.00833 degrees
Number Rows: 4200
Row Resolution: 0.00833 degrees
Extent in the items coordinate system
Cell Geometry: area
Point in Pixel: center
Spatial Reference Properties
Geographic Coordinate Reference: GCS_WGS_1984
Site boundaries: (All latitude and longitude given in decimal degrees)
|Site (Region)||Westernmost Longitude||Easternmost Longitude||Northernmost Latitude||Southernmost Latitude||Geodetic Datum|
|Amazon Basin||-82.72083||-33.5739||13.8583||-21.1277||World Geodetic System, 1984 (WGS-84)|
Platform/Sensor/Parameters measured include:
Incorporating remote sensing data from several sensors responding to various attributes of land cover, commonly referred to as data fusion is one way to improve current land classifications in the tropics. These NDVI data, in combination with radar data from the JERS-1 satellite, were used in a test of a data fusion approach for the Amazon Basin land cover mapping.
The standard correction method for all VEGETATION products is based on SMAC (Simplified Method for Atmospheric Correction) with the aerosol optical depth at 550 nm and the vertically integrated gaseous contents for water vapor and ozone (Rahman and Dedieu, 1994). The ground surface reflectance was then used to calculate the NDVI for each pixel. The 10-day composite images were used to obtain the monthly NDVI images based on the maximum-NDVI criterion. To further reduce potential cloud contamination, monthly maximum NDVI images from April, 1998 through March, 2001 were used to calculate monthly mean NDVI over a 3-year period. The final monthly NDVI time series was further processed to eliminate any outliers using the Fourier-based adjustment technique (Los, 1998).
Two years of approximately 1-km NDVI data were obtained from SPOT VEGETATION. The VEGETATION 1 sensor is aboard the SPOT 4 satellite launched on 24 March 1998. The sensor provides daily 1-km resolution images of nearly all of the terrestrial earth, with 2,250-km swath, 101 degrees field of view, and four spectral channels: blue (0.43-0.47 mm), red (0.61-0.68 mm), near infrared (0.78-0.89 mm), and middle infrared (1.58-1.75 mm). The radiometric resolution of surface reflectance is from 0.001 to 0.003 with different adjustments for each band. All pixels are resampled onto a regular grid by taking into account the spectral band registration, satellite location and attitude correction, and parallax distortion caused by terrain elevation.
The 10-day composite was obtained by choosing the best measurement of the period that met the following criteria:
These data are available through the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).
Contact for Data Center Access Information:
Telephone: +1 (865) 241-3952
Hansen, M.C., R. DeFries, and J. Townshend. (2000). Global land cover classification at 1 km spatial resolution using classification tree. International Journal of Remote Sensing, 21, 1331-1364.
Los, S.O. (1998). Linkages Between Global Vegetation and Climate: An Analysis Based on NOAA Advanced Very High
Resolution Radiometer Data. PhD. Dissertation, Vrije Universiteit, NASA/GSFC/CR-1998-206852.
Rahman, H. and G. Dedieu. (1994). SMAC: A Simplified Method of Atmospheric Correction of satellite measurements in the solar spectrum. International Journal of Remote Sensing, 15, 123-143.
TRFIC (2002). Tropical Rain Forest Information Center. http://bsrsi.msu.edu/trfic/.