Deriving consistent long-term vegetation information from AVHRR reflectance data using a cover-triangle-based framework
Download (1.97 MB)
-
Altmetric Citations
Donohue, Randall; Roderick, Michael; McVicar, Tim R
Description
Long-term vegetation dynamics associated with climatic changes can be assessed using Advanced Very High Resolution Radiometer (AVHRR) red and near-infrared reflectance data provided that the data have been processed to remove the effects of non-target signal variability, such as atmospheric and sensor calibration effects. Here we present a new method that performs a relative calibration of reflectance data to produce consistent long-term vegetation information. It is based on a simple...[Show more]
dc.contributor.author | Donohue, Randall | |
---|---|---|
dc.contributor.author | Roderick, Michael | |
dc.contributor.author | McVicar, Tim R | |
dc.date.accessioned | 2015-12-10T22:50:40Z | |
dc.identifier.issn | 0034-4257 | |
dc.identifier.uri | http://hdl.handle.net/1885/58713 | |
dc.description.abstract | Long-term vegetation dynamics associated with climatic changes can be assessed using Advanced Very High Resolution Radiometer (AVHRR) red and near-infrared reflectance data provided that the data have been processed to remove the effects of non-target signal variability, such as atmospheric and sensor calibration effects. Here we present a new method that performs a relative calibration of reflectance data to produce consistent long-term vegetation information. It is based on a simple biological framework that assumes that the position of the vegetation cover triangle is invariant in reflectance space. This assumption is in fact an intrinsic assumption behind the commonly used Normalised Difference Vegetation Index (NDVI) and is violated when the NDVI is calculated from inadequately corrected reflectance data. In this new method, any temporal variability in the position of the cover triangle is removed by geometrically transforming the observed reflectance data such that two features of the triangle-the soil line and the dark point-are stationary in reflectance space. The fraction of Photosynthetically Active Radiation absorbed by vegetation (fPAR; 0.0-0.95) is then calculated, via the NDVI, from calibrated reflectances. This method was tested using two distinct, monthly AVHRR products for Australia: (i) the coarse-resolution, fully calibrated, partially atmospherically corrected PAL data (1981-1994); and (ii) the fine-resolution, fully calibrated, non-atmospherically corrected HRPT data (1992-2004). Results show that, in the 20-month period when the two datasets overlap (1992-1994), the Australia-wide, root mean square difference between the two datasets improved from 0.098 to 0.027 fPAR units. The calibrations have produced two approximately equivalent datasets that can be combined as a single input into time-series analyses. The application of this method is limited to areas that have a wide-enough variety of land-cover types so that the soil line and dark point are evident in the cover triangle in every image of the time-series. Another limitation is that the methodology performs only bulk, relative calibrations and does not remove the absolute effects of observation uncertainties. The simplicity of the method means that the calibration procedure can be easily incorporated into near-real-time operational remote-sensing environments. Vegetation information produced using this invariant-cover-triangle method is expected to be well suited to the analysis of long-term vegetation dynamics and change. | |
dc.publisher | Elsevier | |
dc.source | Remote Sensing of Environment | |
dc.subject | Keywords: Advanced very high resolution radiometers (AVHRR); Calibration; Climate change; Data structures; Remote sensing; Atmospheric effects; Cover triangle; Dark points; Sensor calibration; Soil lines; Vegetation dynamics; Vegetation; AVHRR; calibration; climate Atmospheric effects; AVHRR; Cover triangle; Dark point; fPAR; NDVI; Reflectance; Sensor calibration; Soil line; Vegetation dynamics | |
dc.title | Deriving consistent long-term vegetation information from AVHRR reflectance data using a cover-triangle-based framework | |
dc.type | Journal article | |
local.description.notes | Imported from ARIES | |
local.identifier.citationvolume | 112 | |
dc.date.issued | 2008 | |
local.identifier.absfor | 060208 - Terrestrial Ecology | |
local.identifier.absfor | 040608 - Surfacewater Hydrology | |
local.identifier.ariespublication | u9204316xPUB454 | |
local.type.status | Published Version | |
local.contributor.affiliation | Donohue, Randall, College of Medicine, Biology and Environment, ANU | |
local.contributor.affiliation | Roderick, Michael, College of Medicine, Biology and Environment, ANU | |
local.contributor.affiliation | McVicar, Tim R, CSIRO Land and Water | |
local.description.embargo | 2037-12-31 | |
local.bibliographicCitation.startpage | 2938 | |
local.bibliographicCitation.lastpage | 2949 | |
local.identifier.doi | 10.1016/j.rse.2008.02.008 | |
dc.date.updated | 2015-12-10T07:19:46Z | |
local.identifier.scopusID | 2-s2.0-43949145240 | |
local.identifier.thomsonID | 000256986400017 | |
Collections | ANU Research Publications |
Download
File | Description | Size | Format | Image |
---|---|---|---|---|
01_Donohue_Deriving_consistent_long-term_2008.pdf | 1.97 MB | Adobe PDF |
Items in Open Research are protected by copyright, with all rights reserved, unless otherwise indicated.
Updated: 17 November 2022/ Responsible Officer: University Librarian/ Page Contact: Library Systems & Web Coordinator