Estimating tree-cover change in Australia: Challenges of using the MODIS vegetation index product

Gill, Tony, Phinn, SR, Armston, J.D. and Pailthorpe, Bernard (2009) Estimating tree-cover change in Australia: Challenges of using the MODIS vegetation index product. International Journal of Remote Sensing, 30 6: 1547-1565. doi:10.1080/01431160802509066

Author Gill, Tony
Phinn, SR
Armston, J.D.
Pailthorpe, Bernard
Title Estimating tree-cover change in Australia: Challenges of using the MODIS vegetation index product
Journal name International Journal of Remote Sensing   Check publisher's open access policy
ISSN 0143-1161
Publication date 2009-03-20
Year available 2009
Sub-type Article (original research)
DOI 10.1080/01431160802509066
Open Access Status
Volume 30
Issue 6
Start page 1547
End page 1565
Total pages 19
Place of publication United Kingdom
Publisher Taylor & Francis
Language eng
Subject C1
090905 Photogrammetry and Remote Sensing
970105 Expanding Knowledge in the Environmental Sciences
Abstract Time series of the vegetation index product MOD13Q1 from the Moderate Resolution Imagery Spectroradiometer (MODIS) were assessed for estimating tree foliage projective cover (FPC) and cover change from 2000 to 2006. The MOD13Q1 product consists of the enhanced vegetation index (EVI) and the normalized difference vegetation index (NDVI). There were four challenges in using the MOD13Q1 product to derive tree FPC: assessing the impact of the sensor's varying view geometry on the vegetation index values; decoupling tree and grass cover contributions to the vegetation index signal; devising a method to relate the temporally composited vegetation index pixels to Lidar estimates of tree FPC for calibration; and estimating the accuracy of the FPC and FPC change measurements using independently derived Lidar, Landsat and MODIS cover estimates. The results show that, for complex canopies, the varying view geometry influenced the vegetation indices. The EVI was more sensitive to the view angle than the NDVI, indicating that it is sensitive to vegetation structure. An existing time series method successfully extracted the evergreen vegetation index signal while simultaneously minimizing the impact of varying view geometry. The vegetation indices were better suited to monitoring tree cover change than deriving accurate single-date estimates of cover at regional to continental scales. The EVI was more suited to monitoring change in high-biomass regions (cover 50%) where the NDVI begins to saturate.
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

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Created: Thu, 03 Sep 2009, 18:16:31 EST by Mr Andrew Martlew on behalf of School of Geography, Planning & Env Management