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Rights | Copyright 2013 UTS. Rights owned by the University of Technology Sydney (UTS). Rights licensed subject to Creative Commons Attribution (CC BY). |
Licence | Creative Commons Attribution 3.0 License, http://creativecommons.org/licenses/by/3.0. |
Access | These data can be freely downloaded and used subject to the CC BY licence. Attribution and citation is required as described at http://www.auscover.org.au/citation. We ask that you send us citations and copies of publications arising from work that use these data. |
The Australian phenology product from MOD13C1(16-days,5600 m) - covering Australia
The Australian Phenology Product is a continental data set that allows the quantitative analysis of Australia’s phenology 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 Australia.
Phenological cycles are defined as a period of EVI-measured greening and browning that may occur at any time of the year, extend across the end of a year, skip a year (not occur for one or multiple years) or occur more than once a year. Multiple phenological cycles within a year can occur in the form of double cropping in agricultural areas or be caused by a-seasonal rain events in water limited environments.
Based on per-pixel greenness trajectories measured by MODIS EVI, phenological cycle curves were modelled and their key properties in the form of phenological curve metrics were derived including: the first and second minimum point, peak, start and end of cycle; length of cycle, and; the amplitude of the cycle. Integrated EVI under the curve between the start and end of the cycle time of each cycle is calculated as a proxy of productivity.
Item | Detail |
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Spatial resolution (degrees) | 0.05 degree (5600 m) |
Spatial coverage (degrees) | 112 to 154 E 9.5 to 45 S |
Temporal resolution | 16 days |
Temporal coverage | 2000 to 2015 |
Sensor & platform | MODIS Terra, MOD13C1 |
Item | Detail |
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Spatial representation type | Grid |
Spatial reference system | WGS 84 |
Item | Detail |
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Name | Alfredo Huete |
Organisation | Climate Change Cluster, University of Technology Sydney, Australia |
Position | Professor |
alfredo.huete@uts.edu.au | |
Role | Principle Investigator |
Address | |
Telephone | |
URL | http://www.c3.uts.edu.au |
Item | Detail |
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Name | Rakhesh Devadas |
Organisation | Climate Change Cluster, University of Technology Sydney, Australia |
Position | Remote sensing scientist |
rakhesh.devadas@uts.edu.au | |
Role | Point of contact |
Address | |
Telephone | |
URL | http://www.c3.uts.edu.au |
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.
Thesauri | Keyword |
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GCMD | EARTH SCIENCE > BIOSPHERE > VEGETATION > PLANT PHENOLOGY |
CF | |
FoR | Environmental Sciences > Ecological Applications = 0501 |
There are three main thesauri that AusCover recommends:
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 2000-2012 MOD13C1 16-day record. Individual pixel observations with less than a “good data” MOD13C1 QA flags are gap filled (interpolated).
Less than “good data” MOD13C1 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” MOD13C1 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 2012 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 of seasonal/phenologic parameters is accomplished across a wide range of Australian landscapes 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. Tower measures of ET potentially provide more accurate measures of vegetation green-up and duration in the arid and semiarid landscapes. At regional levels, 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.
Item | Product link |
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Phenology - MODIS, derived from MOD13A1 EVI, NSW-Vic coverage | http://www.auscover.org.au/xwiki/bin/view/Product+pages/Phenology+MOD13A1+UTS+NSWVic |
Fractional cover metrics - MODIS, ABARES algorithm, Australia coverage | http://www.auscover.org.au/xwiki/bin/view/Product+pages/FC+Metrics+MODIS+ABARES |
Dynamic Land Cover Dataset - MODIS, Australia coverage | http://www.auscover.org.au/xwiki/bin/view/Product+pages/Product+User+Page+GA+1 |
Land Cover Dynamics - MODIS, LPDAAC MCD12Q2 mosaic, Australia coverage | http://www.auscover.org.au/xwiki/bin/view/Product+pages/LPDAAC+Mosaics+MCD12Q2+CMAR |
Item | Detail or link |
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Publication | Mark Broich, Alfredo Huete, Matt Paget, Xuanlong Ma, Mirela Tulbure, Natalia Restrepo Coupe, Bradley Evans, Jason Beringer, Rakhesh Devadas, Kevin Davies, Alex Held (2015). A spatially explicit land surface phenology data product for science, monitoring and natural resources management applications. Environmental Modelling & Software, 64, pp. 191–204, http://dx.doi.org/10.1016/j.envsoft.2014.11.017 |
Publication | M. 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. Biogeosciences, 11, pp. 5181-5198, http://dx.doi.org/10.5194/bg-11-5181-2014 |
Publication | Xuanlong Ma, Alfredo Huete, Qiang Yu, Natalia Restrepo Coupe, Kevin Davies, Mark Broich, Piyachat Ratana, Jason Beringer, Lindsay B. Hutley, James Cleverly, Nicolas Boulain, Derek Eamus (2013). Spatial patterns and temporal dynamics in savanna vegetation phenology across the North Australian Tropical Transect. Remote Sensing of Environment, 139, pp. 97–115, http://dx.doi.org/10.1016/j.rse.2013.07.030 |
Validation report | |
Online info |
R software, Savitzsky-Golay filtering and double-logistics curve modelling is used to generate the entire set of seasonal metrics from MOD13C1 EVI data cubes. The product can be updated annually.
Version label | Detail |
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1.0 | Initial release |
1.1 | a)Algorithm ported to Python for operationalisation reasons b)Various fixes to algorithm that may have resulted in incorrect phenology metrics c)Consistent fill values with the 500m phenology product |
2.0 | Updated temporal coverage to end 2015, and improved processing efficiency |
Date | Detail |
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2012-12-10 | Updated metadata into the new template. Renamed the AusCover product title. Created a corresponding GeoNetwork record. |
2014-09-01 | Updated some section |
2014-10-09 | Added related product link to Phenology MOD13A1 |
2016-08-04 | Updated netcdf link to v2, temporal coverage to end 2015, point of contact, and figure |