Team Information:
 Investigation Team:
  Team ID: LC-08 (Moore / Nobre)
  Investigator:
   Name: Braswell, Rob H.
   Email: rob.braswell@unh.edu
  Investigator:
   Name: Frolking, Steve
   Email: steve.frolking@unh.edu
  Investigator:
   Name: Hagen, Steve 
   Email: hagen@eos.sr.unh.edu
  Investigator:
   Name: Hurtt, George C.
   Email: George.Hurtt@unh.edu
  Investigator:
   Name: Moorcroft, Paul R.
   Email: paul@eno.princeton.edu
  Investigator:
   Name: Moore, Berrien
   Email: b.moore@unh.edu
  Investigator:
   Name: Nobre, Carlos Afonso
   Email: nobre@cptec.inpe.br
  Investigator:
   Name: Pacala, Steve
   Email: pacala@princeton.edu
  Investigator:
   Name: Peterson, Bruce J.
   Email: peterson@mbl.edu
  Investigator:
   Name: Tian, Hanqin
   Email: htian@mbl.edu
  Investigator:
   Name: Vorosmarty, Charles J.
   Email: charles.vorosmarty@unh.edu
  Investigator:
   Name: Wildes, Pam
   Email: pam.wildes@unh.edu
  Investigator:
   Name: Xiao, Xiangming
   Email: xiangming.xiao@unh.edu
 Contact Person:
  Name: Hagen, S.
  Email: hagen@eos.sr.unh.edu
 LBA Science Component: Land Use and Land Cover
 Metadata Author:
  Name: Hagen, S.
  Email: hagen@eos.sr.unh.edu
  Phone: 603 749 1961
Data Set Information:
 Data Set Title: Large Scale Remote Observations of Disturbance in the Amazon Basin
 Activity: Poster -- LBA Science Conference, Belem, Para, June 2000
 Project: LBA (Large-Scale Biosphere-Atmosphere Experiment in the Amazon)
 Site Information:
  Site: 
    other
 Time Period:
  Temporal Coverage:
 Parameter Description:
  Topic: LAND SURFACE
  Term: LAND USE/LAND COVER
  Parameter: LAND CLASSES
  Sensor: TM and AVHRR
 Keywords: 
   Remote Sensing
TM
AVHRR
Land Use
High Resolution
Moderate Resolution
Land Use Change
Amazon
Basin
Time Series
Deforestation
Land Cleared
Cerrado
 Description: 
   Introduction (from poster):
Global biogeochemical models need land cover change estimates annually at a 0.5 degree resolution. One potential source of this annual product is an interpolation between the decadally spaced maps derived from high resolution (30-m) TM imagery.  Another option is to use annual coarse resolution (8-km) AVHRR imagery. We report initial results using aggregated 48-km AVHRR data (0.5 degrees), calibrated with Landsat TM data, to evaluate historical disturbance patterns (1981-1994) for an area in the Amazon region.  Optical measurements from AVHRR almost certainly contain artifacts that mask subtle year-to-year changes in reflectance associated with the removal of some small fraction of forest from a 48-km grid cell. Despite this, we have developed a model based on NDVI and TM which appears to capture some details of the spatial and temporal patterns of disturbance. Though tropical rainforest monitoring is in many ways a remote sensing worst-case scenario because of the region?s high cloud frequency and the dominance of other atmospheric constituents in the signal, this study suggests that AVHRR data contain information about disturbance patterns and rates.  
 Data Last Modified: 20000630
Data Access Information:
 Data Set Status: Ready for archive
 Data Set Restrictions: Public
 Data Set Location: Anonymous ftp at the University of New Hampshire
 Data Center Contact: Stephen Hagen
 Data Set Link:
  URL: ftp.eos.sr.unh.edu
  Label: ftp.eos.sr.unh.edu