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Product pages » Phenology - MODIS, derived from MOD13A1 EVI, NSW-Vic coverage

Phenology - MODIS, derived from MOD13A1 EVI, NSW-Vic coverage

Last modified by Matt Paget on 2016/08/04 11:59

Phenology - MODIS, derived from MOD13A1 EVI, NSW-Vic coverage


Link to the data

DescriptorData link
Dataset digital object identifier (DOI)
GeoNetwork record

Data licence and Access rights

RightsCopyright 2013 UTS. Rights owned by the University of Technology Sydney (UTS). Rights licensed subject to Creative Commons Attribution (CC BY).
LicenceCreative Commons Attribution 3.0 License,
AccessThese data can be freely downloaded and used subject to the CC BY licence. Attribution and citation is required as described at We ask that you send us citations and copies of publications arising from work that use these data.

Alternate title

The Australian phenology product from MOD13A1(16-days,500m) - covering NSW/VIC

Abstract or Summary

The NSW/VIC Phenology Product is a dataset that allows the quantitative analysis of phenology in NSW and VIC derived from MODIS Enhanced Vegetation Index (EVI) data using an algorithm designed to accommodate Australian conditions. The product can be used to characterize phenological cycles of greening and browning and quantify the cycles’ inter and intra annual variability from 2000 to 2015 across NSW/VIC.

Spatial and Temporal extents

Spatial resolution (degrees)500 m
Spatial coverage (degrees)140 to 154 E 27 to 39 S
Temporal resolution16 days
Temporal coverage2000 to 2015
Sensor & platformMODIS Terra, MOD13A1
Spatial representation typeGrid
Spatial reference systemWGS 84

Point of contact

NameAlfredo Huete
OrganisationClimate Change Cluster, University of Technology Sydney, Australia
RolePrinciple Investigator
NameRakhesh Devadas
OrganisationClimate Change Cluster, University of Technology Sydney, Australia
PositionRemote sensing scientist
RolePoint of contact


The development of the Australian Phenology Product was funded by the AusCover Facility of the Australian Terrestrial Ecosystem Research Network (TERN) and supported by ARC-DP1115479 grant entitled "Integrating remote sensing, landscape flux measurements, and phenology to understand the impacts of climate change on Australian landscapes" (Huete, CI). Calculations were preformed on the University of Technology, Sydney eResearch high performance computing facility.


FoREnvironmental Sciences > Ecological Applications = 0501

There are three main thesauri that AusCover recommends:

  1. Global Change Master Directory (
  2. Climate and Forecast (CF) convention standard names (
  3. Fields of Research codes (

Data quality

The quality of the phenological parameters could be limited by the spatial-temporal resolution of the input data, sub pixel clouds, and by the ‘local’ applicability of the gap filling, smoothing, and curve fitting methodology within the phenology algorithm that is applied at national scale.

The dataset covers all of Australia. The input dataset is the complete 2000-2013 MOD13A1 16-day record. Individual pixel observations with less than a “good data” MOD13A1 QA flags are gap filled (interpolated).

Less than “good data” MOD13A1 QA flags occur more frequently during the monsoon season at tropical latitudes near the coast and during the southern hemisphere winter at higher latitudes. The west coast of Tasmania and high elevation areas in South Eastern Australia also have more frequent cloud cover causing data gaps. The gap filling scheme used by the phenology algorithm overcomes the issue of missing observation in most cases except for areas with persistent cloud cover.

Less than “good data” MOD13A1 QA flags occur with very high frequency over highly reflecting surfaces (salt crusts) in the continent’s interior. The gap filling method and the subsequently derived phenological metrics should not be considered reliable.

Seasons in Australia do only in certain regions ‘fit’ within a calendar year. The implication for data completeness is that part of a season that occurred in the beginning of 2000 or in late 2013 may not be captured by the derived phenological metrics as the season’s complete trajectory is not covered by the input data time series.

Validation status

Validation of seasonal/phenologic parameters is accomplished across NSW/VIC through comparisons with finer resolution (half-hourly/ daily) OzFlux eddy covariance tower measures of gross primary productivity (GPP) and evapotranspiration (ET). Tower measurements of actual photosynthetic activity (GPP) primarily relate to onset, duration, magnitude, and growing season length.

We plan validation activities focused on the use of phenocam networks that capture the seasonal dynamics and species-level phenology of overstory and understory plant functional types. This is being prototyped in NSW and thenceforth to be expanded to TERN supersites, and transects. We are exploring the availability, prevalence, and cost-effectiveness of using CSIRO's Wireless Sensor Network technology for 'light' sensors. The combined use of a PAR sensor (400-700nm) and total radiation sensor (0.4 to 3.5um) enables the calculation of Visible/ Near-infrared based broadband vegetation indices yielding in situ measures of seasonal vegetation profiles.

Related products

ItemProduct link
Phenology - MODIS, derived from MOD13C1 EVI, Australia coverage
Fractional cover metrics - MODIS, ABARES algorithm, Australia coverage
Dynamic Land Cover Dataset - MODIS, Australia coverage
Land Cover Dynamics - MODIS, LPDAAC MCD12Q2 mosaic, Australia coverage


ItemDetail or link
PublicationM.Broich,A.Huete,M.G.Tulbure,X.Ma,Q.Xin,M.Paget,N.Restrepo-Coupe,K.Davies,R.Devadas and A.Held.(2014). Land surface phenological response to decadal climate variability across Australia using satellite remote sensing
Validation report
Online info

Algorithm summary

Python software, Savitzsky-Golay filtering and double-logistics curve modelling is used to generate the entire set of seasonal metrics from MOD13A1 EVI data cubes.

Product version history

Version labelDetail
1.0Initial release
2.0Updated temporal coverage to end 2015, and improved processing efficiency

Metadata history

2014-10-09Add new product page
2016-08-04Updated netcdf link to v2, temporal coverage to end 2015, point of contact, and figure
Created by Matt Paget on 2014/10/09 09:46

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