Seasonal surface reflectance - Landsat, JRSRP algorithm, Australia Coverage
The dataset consists of composited seasonal surface reflectance images (4 seasons per year) created from the full time series of Landsat TM/ETM+/OLI imagery. The imagery has been composited over a season to produce imagery which is representative of that period, using techniques which will reduce contamination by cloud and other problems. This creates a regular time series of reflectance values which captures the variability at seasonal time scales. The benefits are a regular time series with minimal missing data or contamination from various sources of noise as well as data reduction. Each season has exactly one value (per band) for each pixel (or is null, i.e., missing), and the value for that season is assumed to be the representative of the whole season. The algorithm is based on the medoid (in reflectance space) over the time period (the medoid is a multi-dimensional analogue of the median), which is robust against extreme values.
Simple
Identification info
- Date (Creation)
- 2014-06-20
- Date (Publication)
- 2021-04-09
- Date (Revision)
- 2024-10-04
- Edition
- 1.0
Publisher
Author
Department of Environment and Science (2017-2023), Queensland Government
41 Boggo Road, Dutton Park, Queensland, 4102, Australia
Dutton Park
Queensland
4102
Australia
- Website
- https://www.tern.org.au/
- Purpose
- This product captures surface reflectance at seasonal (ie three-monthly) time scales, forming a consistent time series from 1987 - present. For applications that focus on vegetation changes, the fractional cover and ground cover products may be more suitable.
- Credit
- We at TERN acknowledge the Traditional Owners and Custodians throughout Australia, New Zealand and all nations. We honour their profound connections to land, water, biodiversity and culture and pay our respects to their Elders past, present and emerging.
- Credit
- This dataset was produced by the Joint Remote Sensing Research Program using data sourced from US Geological Survey.
- Status
- On going
Point of contact
Department of Environment and Science (2017-2023), Queensland Government - van den Berg, Deanna (Principal Scientist (Remote Sensing))
41 Boggo Road, Dutton Park, Queensland, 4102, Australia
41 Boggo Road
Dutton Park
Queensland
4102
Australia
- Topic category
-
- Environment
- Imagery base maps earth cover
Extent
- Description
- Australia
N
S
E
W
))
Temporal extent
- Time period
- 1987-12-01
- Title
- Flood, N., Danaher, T., Gill, T. and Gillingham, S. (2013) An Operational Scheme for Deriving Standardised Surface Reflectance from Landsat TM/ETM+ and SPOT HRG Imagery for Eastern Australia. Remote Sens. 2013, 5(1), 83-109
- Website
-
Flood, N., Danaher, T., Gill, T. and Gillingham, S. (2013) An Operational Scheme for Deriving Standardised Surface Reflectance from Landsat TM/ETM+ and SPOT HRG Imagery for Eastern Australia. Remote Sens. 2013, 5(1), 83-109
Related documentation
- Title
- Flood, N. (2013) Seasonal Composite Landsat TM/ETM+ Images Using the Medoid (a Multi-dimensional Median). Remote Sens. 2013, 5(12), 6481-6500
- Website
-
Flood, N. (2013) Seasonal Composite Landsat TM/ETM+ Images Using the Medoid (a Multi-dimensional Median). Remote Sens. 2013, 5(12), 6481-6500
Related documentation
- Title
- Zhu, Z. and Woodcock, C.E. (2012). Object-based cloud and cloud shadow detection in Landsat imagery Remote Sensing of Environment 118 (2012) 83-94.
- Website
-
Zhu, Z. and Woodcock, C.E. (2012). Object-based cloud and cloud shadow detection in Landsat imagery Remote Sensing of Environment 118 (2012) 83-94.
Related documentation
- Maintenance and update frequency
- Quarterly
- GCMD Science Keywords
- ANZSRC Fields of Research
- TERN Platform Vocabulary
- TERN Instrument Vocabulary
- TERN Parameter Vocabulary
- QUDT Units of Measure
- GCMD Horizontal Resolution Ranges
- GCMD Temporal Resolution Ranges
Resource constraints
- Use limitation
- The Creative Commons Attribution 4.0 International (CC BY 4.0) license allows others to copy, distribute, display, and create derivative works provided that they credit the original source and any other nominated parties. Details are provided at https://creativecommons.org/licenses/by/4.0/
- File name
- 88x31.png
- File description
- CCBy Logo from creativecommons.org
- File type
- png
- Title
- Creative Commons Attribution 4.0 International Licence
- Alternate title
- CC-BY
- Edition
- 4.0
- Access constraints
- License
- Use constraints
- Other restrictions
- Other constraints
- Copyright 2010-2021. JRSRP. Rights owned by the Joint Remote Sensing Research Project (JRSRP).
- Other constraints
- While 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.
- Other constraints
- It is not recommended that these data sets be used at scales more detailed than 1:100,000.
- Other constraints
- TERN services are provided on an “as-is” and “as available” basis. Users use any TERN services at their discretion and risk. They will be solely responsible for any damage or loss whatsoever that results from such use including use of any data obtained through TERN and any analysis performed using the TERN infrastructure. Web links to and from external, third party websites should not be construed as implying any relationships with and/or endorsement of the external site or its content by TERN.
Resource constraints
- Classification
- Unclassified
- Supplemental Information
- The standard form of the file naming convention is: <satellite category code> <instrument code> <product code> _<where> _<when> _<processing stage code> _<additional dataset specific tags> For this dataset are (comma-separated): Data Naming Element, Possible Code(s), Descriptor Standard Elements satellite category, lz, Landsat - all possible, l8, Landsat 8, instrument, tm, thematic, ol, operational land imager product, re, reflective where, qld,nsw,vic,tas,sa,nt,wa, state when , myyyymmyyyymm , season start date (1st day of month) and season end date (last day of month) processing stage, dbi, seasonal surface reflectance, data projection, a2, Australian Albers Equal Area
Distribution Information
Distributor
Distributor
- Distribution format
-
- NetCDF
Distribution Information
Distributor
Distributor
Terrestrial Ecosystem Research Network
80 Meiers Road, Indooroopilly, Queensland, 4068, Australia
Indooroopilly
Queensland
4068
Australia
- Distribution format
-
- OnLine resource
- Cloud Optimised GeoTIFFs - Seasonal Surface Reflectance
- OnLine resource
-
Seasonal surface reflectance - Landsat
landsat_seasonal_surface_reflectance
- OnLine resource
- ro-crate-metadata.json
Data quality info
- Hierarchy level
- Dataset
- Other
- The input imagery was processed to level L1T by the USGS. Geodetic accuracy of the product depends on the image quality and the accuracy, number, and distribution of the ground control points.
Report
Result
- Statement
- The USGS aims to provide image-to-image registration with an accuracy of 12m. Refer to the L8 Data Users Handbook for more detail.
Resource lineage
- Statement
- Landsat imagery < 80% cloud cover downloaded > corrections and masking > medoid calculated > seasonal surface reflectance
- Hierarchy level
- Dataset
Process step
- Description
- Image Pre-Processing: All input Landsat TM/ETM+/OLI imagery was downloaded from the USGS EarthExplorer website as level L1T imagery. Images which the EarthExplorer site rated as having greater than 80% cloud cover were not downloaded, on the assumption that they would contribute little, and would add extra noise in the form of undetected cloud, shadow, and mis-registration (which is a greater risk in very cloudy images). The imagery has been corrected for atmospheric effects, and bi-directional and topographic effects, using the methods detailed by Flood et al. (2013). The resulting imagery is expressed as surface reflectance. Cloud, cloud shadow and snow have been masked out using the Fmask automatic cloud mask algorithm. Topographic shadowing has been masked using the Shuttle Radar Topographic Mission DEM at 30 m resolution, and the methods described by Robertson.
Process step
- Description
- Seasonal Compositing: The seasonal composites were calculated using the medoid in the 6-dimensional space of reflectance values from the six Landsat reflective bands. The medoid is a “measure of centre” of a multi-variate set of points, similar in nature to the median of a univariate dataset. The medoid has similar desirable properties to the univariate median. In a general cluster of points, in n-dimensional space, the medoid will lie roughly in the centre of the cluster, making it a good choice as representative of that set of points. Most importantly, it is robust against the presence of outliers in the set, until at least half of the points are to be considered as outliers, after which it breaks down. Two variations of seasonal surface reflectance are available and can be distinguished by the ‘satellite category code’ component of the filename. (Refer to file naming convention information). ‘lz’ indicates that the composite was derived from all possible Landsat data, and ‘l8’ indicates that the composite was derived from Landsat8 OLI data only. For the latter case, the OLI Band 1 is omitted so that the resulting composite has the same bands as the generic Landsat ‘lz’ variant.
Process step
- Description
- Image Restrictions: In estimating a value which is representative of the season, we choose to add a restriction on the number of input points. If a given pixel has less than three observations available for the season, after masking, we define the result as missing, on the principle that we do not have enough data to know how representative our choice might be. Neither the medoid nor the geometric median are robust against a single outlier in the case of less than three observations.
Reference System Information
- Reference system identifier
- EPSG/EPSG:4326
- Reference system type
- Geodetic Geographic 2D
Metadata
- Metadata identifier
-
urn:uuid/5a31eed4-e43a-404d-b534-3f820305ed61
- Title
- TERN GeoNetwork UUID
- Language
- English
- Character encoding
- UTF8
Point of contact
Type of resource
- Resource scope
- Dataset
- Metadata linkage
-
https://geonetwork.tern.org.au/geonetwork/srv/eng/catalog.search#/metadata/5a31eed4-e43a-404d-b534-3f820305ed61
Point-of-truth metadata URL
- Date info (Creation)
- 2014-06-20T00:00:00
- Date info (Revision)
- 2024-10-04T00:00:00
Metadata standard
- Title
- ISO 19115-1:2014/AMD 1:2018 Geographic information - Metadata - Fundamentals
- Edition
- 1
Metadata standard
- Title
- ISO/TS 19115-3:2016
- Edition
- 1.0
Metadata standard
- Title
- ISO/TS 19157-2:2016
- Edition
- 1.0
- Title
- Terrestrial Ecosystem Research Network (TERN) Metadata Profile of ISO 19115-3:2016 and ISO 19157-2:2016
- Date (published)
- 2021
- Edition
- 1.0
Identifier
Overviews
Spatial extent
N
S
E
W
Provided by
Associated resources
Not available