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Product pages » Seasonal dynamic reference cover method - Landsat, JRSRP, QLD Coverage

Seasonal dynamic reference cover method - Landsat, JRSRP, QLD Coverage

Last modified by Bec Trevithick on 2017/10/11 13:53

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Link to the data

DescriptorData linkLayer name
Persistent URLNot Available Yet 
GeoNetwork recordNot Available Yet

QLD Tiff mosaics - FTP access

Data licence and Access rights

ItemDetail
RightsCopyright 2010-2020. JRSRP. Rights owned by the Joint Remote Sensing Research Project (JRSRP)
LicenceCreative Common Attribution (CC-BY) 4.0
AccessWhile every care is taken to ensure the accuracy of this information, the Joint Remote Sensing Research Project (JRSRP) makes no representations or warranties about its accuracy, reliability, completeness or suitability for any particular purpose and disclaims all responsibility and all liability (including without limitation, liability in negligence) for all expenses, losses, damages (including indirect or consequential damage) and costs which might be incurred as a result of the information being inaccurate or incomplete in any way and for any reason.

Alternate title

Seasonal dynamic reference cover method images derived from USGS Landsat images.

Abstract or Summary

The seasonal dynamic reference cover method images are created using a modified version of the dynamic reference cover method developed by Bastin et al (2012), who calculated a minimum ground cover image across all years to identify locations of most persistent ground cover in years of lowest rainfall and then used a moving window approach to calculate the difference between the window's central pixel and its surrounding reference pixels.
The main differences between this method and the original method are:
This method uses seasonal fractional ground cover rather than the preceding ground cover index (GCI) calculated from a multiple regression model and masked where FPC > 15%
In addition to cleared areas, this method also excludes certain landforms (undulating slopes), which are considered unsuitable for use as reference pixels
Output

Spatial and Temporal extents

ItemDetail
Spatial resolution (metres)30
Spatial coverage (degrees)north:-6; south:-45; west:108 east:160  
Temporal resolutionSeasonally - At least one image per standard calendar season.
Temporal coverage1990 ongoing
Sensor & platformLandsat 5&7&8
ItemDetail
Spatial representation typegrid
Spatial reference systemAustralian Albers. EPSG:3577

Point of contact

ItemDetail
NameRebecca Trevithick
OrganisationQLD Department of Science, Information Technology and Innovation 
PositionSenior Scientist (Remote Sensing)
Emailrebecca.trevithick@dsiti.qld.gov.au
RolepointOfContact
AddressRemote Sensing Centre, DSITI, EcoSciences Precinct
Telephone+61 7 3170 5679
URLhttp://www.qld.gov.au/dsiti/

Credit

Landsat 5 TM and Landsat 7 ETM+ images were acquired from United States Geologic Survey.

Filenaming convention

Filenames for the seasonal fractional cover deciles product conforms to the AusCover standard naming convention. The standard form of this convention is:

<satellite category code><instrument code><product code>_<where>_<when>_<processing stage code>_<additional dataset specific tags>

Details for the unique codes used for this dataset can be found in the following table.

 Data Naming Element Possible
Code(s)
Descriptor 
Standard Elements  
satellite categorylzLandsat - all possible
instrumenttmthematic
productrereflective
whereqldstate
when myyyymmyyyymm season start date (1st day of month) and season end date (last day of month) 
processing stagedoddrcm
data projectiona2Australian Albers Equal Area

Keywords

ThesauriKeyword
GCMDEARTH SCIENCE > BIOSPHERE > VEGETATION > VEGETATION COVER
CFvegetation_area_fraction
FoREnvironmental Sciences > Ecological Applications = 0501

There are three main thesauri that AusCover recommends:

  1. Global Change Master Directory (http://gcmd.nasa.gov)
  2. Climate and Forecast (CF) convention standard names (http://cfconventions.org/standard-names.html).
  3. Fields of Research codes (http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E?opendocument).

Data quality

Horizontal Positional Accuracy

All the data described here has been generated from the analysis of Landsat TM, ETM+ and OLI data, which has a spatial resolution of approximately 30 m. The imagery is rectified using control points measured with a differential GPS ensuring a maximum root mean square (RMS) error of 20 m at these control points. However, it is possible that errors up to ±50 m occur between these control points. The imagery has been corrected for height displacement using a 3" digital elevation model (DEM) based on the National Aeronautics and Space Administration (NASA), Shuttle Radar Topography Mission (SRTM). It is not recommended that these data sets be used at scales more detailed than 1:100,000.

Vertical Positional Accuracy

All the data described here has been generated from the analysis of Landsat TM, ETM+ and OLI data, which has a spatial resolution of approximately 30 m.

The imagery is rectified using control points measured with a differential GPS ensuring a maximum root mean square (RMS) error of 20 m at these control points. However, it is possible that errors up to ±50 m occur between these control points. The imagery has been corrected for height displacement using a 3" digital elevation model (DEM) based on the National Aeronautics and Space Administration (NASA), Shuttle Radar Topography Mission (SRTM). It is not recommended that these data sets be used at scales more detailed than 1:100,000.

 

Validation status

This product has had no validation undertaken.

Related products

Landsat Seasonal Ground Cover

Seasonal Ground Cover Statistics

References

ItemDetail or link
 PublicationG.Bastin, P.Scarth, V.Chewings, A.Sparrow, R.Denham, M.Schmidt, P.O'Reagain, R.Shepherd, B.Abbott (2012) Separating grazing and rainfall effects at regional scale using remote sensing imagery: A dynamic reference-cover method. Remote Sensing of Environment. 2012, 121, 443-457. https://doi.org/10.1016/j.rse.2012.02.021
Publication

Flood, N. (2013) Seasonal Composite Landsat TM/ETM+ Images Using the Medoid (a Multi-dimensional Median). Remote Sens. 2013, 5(12), 6481-6500; doi:10.3390/rs5126481

PublicationTrevithick, R., Scarth, P., Tindall, D., Denham, R. and Flood, N. (2014). Cover under trees: RP64G Synthesis Report. Department of Science, Information Technology, Innovation and the Arts. Brisbane.

Algorithm summary

Excluded Areas

A mask of excluded areas not to be used in the development of the reference pixels is created. This mask includes areas that have previously been cleared and also undulating plains. This data is obtained from the SLATS historical clearing data across QLD and 

Find Reference Pixels

The 90-95 percentile of minimum ground cover are selected from the long term minimum ground cover statistical product , masked with the excluded areas mask described above. These areas represent the 

Create the Delta GC layer

For each pixel this raster equals the difference between the ground cover value and the reference pixel value and is scaled by 100 to avoid negative values(ground cover value - reference pixel value + 100). Values closer to 100 are better performing.

Output

Output for this product is in the form of a two band TIFF image.
Band 1 - the 'delta GC' image.
Band 2 - the reference pixel image

Product version history

Version labelDetail
0.0Demonstration release

Metadata history

DateDetail
2017-10-10Metadata creation date
Tags:
Created by Bec Trevithick on 2017/08/08 12:18

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