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The Use of AVHRR NDVI in Environmental Applications
Contact: Elizabeth R. McDonaldERIN Remote Sensing Coordinator
Department of the Environment and Heritage
Policy FrameworkCommonwealth Programmes Using RS
EPBC Act– Compliance
State of the Environment Report 2006– Indicator Reporting
National Resource Management – National Matters for Target
CERF (Commonwealth Environment Research Fund)
BRS Climate Group– Drought Exceptional Circumstances– National Agricultural Monitoring System
DEH Remote Sensing Archives
ERIN AVHRR NDVI - continental ‘91 – currentAGO Landsat Archive – continental ’72 - 04– Images– Image Products
Other Data - ad hoc collections– MODIS– SPOT– Quickbird– Ikonos
ERIN AVHRR Processing
Data is supplied by DLI to ERIN as continental 14 day composites of raw satellite counts.
Calibrated using a variant of Roa and Chen (1999) using reference points from the Australian deserts.
As the gain values change over time a regression equation is fitted relating the gain values to the time since launch.
Cloud detection and masking by individual pixels through time and identified using an arbitrary threshold.
State of the Environment Reporting
1. Data Types – Medium spatial resolution data
• Landsat
– High temporal resolution data• AVHRR NDVI
2. Applications– Forest non Forest– Forested stream lengths– Urban expansion including coastal urban expansion– Mangrove mapping
NRM – National Matters for Target
1. Data Types – High to Medium spatial resolution data
• SPOT data• Landsat
– High temporal resolution data• AVHRR NDVI
2. Applications– Forest non Forest and forested stream length– Monitoring and Trend analysis– Water Quality assessment
Inland Aquatic Ecosystems Integrity
River Condition* Forested Stream Length by NHT region
Wetland ecosystem extent and distribution* Extent and change of regionally significant wetlands using an algorithm supplied by of Tim Danaher, QLD Dept. Natural Resources, Mines and Water (pers. Comm. 2005).
Wetland ecosystem condition* Colour (turbidity index)* Transparency (light penetration)* Vegetation (presence/absence)* Vegetation (NDVI greenness)
BRS Climate Group
1. Data Types – High temporal resolution data
• AVHRR NDVI• MODIS NDVI
2. Applications– NDVI Time traces for drought exceptional circumstances– NDVI Anomaly for the National Agricultural Monitoring
System. The Anomoly algorithm is sourced from: McVicar, T.R., Briggs, P.R., King, E.A. and Raupach, M.R. (2003) A Review of Predictive Modelling from a Natural Resource Management Perspective: The Role of Remote Sensing of the Terrestrial Environment. CSIRO Land and Water Client Report to the Bureau of Rural Sciences (also available as CSIRO Earth Observation Centre Report 2003/03 and CSIRO Atmospheric Research Report 2003/31), Canberra, Australia, pp. 26. http://www.clw.csiro.au/publications/consultancy/2003/Review_Of_Remote_Sensing.pdf)
NDVI Anomaly
(NDVIm – NDVIt)/(NDVIt)
NDVIm = NDVI for a particular month (eg. May 2004)
NDVIt = the archive average of that month (eg May 1991 – 2004)
MODIS/AVHRR NDVI Comparison
Comparison of AVHRR NDVI and MOD13Q1 (CSIRO, 2004) using four major land covers:forests; shrublands, grassland and croplands.In all cases MODIS was positively offset and the seasonal variation is greater
Vegetation Class R2
Tall Forest 0.02Low Shrubland 0.41
Tussock Grassland 0.82 Cereal Crop 0.85
Unexplained variance limits the direct simple translation for all but basic applications.
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