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Relative Spectral Mixture Analysis (RSMA) - MODIS, Australia coverage 

Ver: 1.0
Status of Data: completed
Update Frequency: notPlanned
Security Classification: unclassified
Record Last Modified: 2025-12-02
Viewed 8244 times
Accessed 48 times
Dataset Created: 2021-08-11
Dataset Published: 2022-04-30
Data can be accessed from the following links:
HTTPPoint-of-truth metadata URLHTTPRelative Spectral Mixture Analysis (RSMA)HTTPro-crate-metadata.json
How to cite this collection:
Clarke, K. & Lewis, M. (2022). Relative Spectral Mixture Analysis (RSMA) - MODIS, Australia coverage. Version 1.0. Terrestrial Ecosystem Research Network. Dataset. https://portal.tern.org.au/metadata/36408a5f-0ab3-442f-a78e-822c8edaf07f 
RSMA measures change in the relative contributions of photosynthetic vegetation (PV, or GV green vegetation), non-photosynthetic vegetation (NPV) and soil reflectance compared to a baseline date. These spectral changes correspond to changes in fractional cover relative to the baseline date. Full details on the RSMA method are presented in Okin (2007). One of the key advantages of the RSMA, its insensitivity to changes in soil spectra, is a result of the fact that it does not require us to know the soil reflectance profile for a region. This strength is also the cause of a major weakness in RSMA. Since the measure is relative to a baseline date, and the absolute cover levels for every pixel are unknown at the baseline, the RSMA does not convey the absolute cover levels at any other point in time. However, if the absolute cover levels are known at any point in time, it is theoretically possible to convert the RSMA to absolute relative spectral mixture analysis (ARSMA).
As with all products derived from passive remote sensing imagery, this product represents the world as seen from above. Therefore, the cover recorded by this product represent what would be observed from a bird's-eye-view. Therefore, dense canopy may prevent observation of significant soil exposure. 
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. 
Purpose
It was demonstrated that the RSMA was a very good measure of change in relative fractional PV, NPV and soil cover, and that the ARSMA was a very good measure of change in absolute fractional PV, NPV and soil cover. Given that the RSMA is not a measure of absolute fraction, it should not be used for monitoring change in absolute soil exposure through time. However, the RSMA may be used for landscape phenology studies. Alternatively, the ARSMA is a measure of absolute fraction, and may therefore be used for landscape phenology studies, and for monitoring change in absolute soil exposure through time. However, the ARSMA is not ready for operational use yet, as it is still in development, and was produced as a proof of concept. 
Lineage
Data not provided. 
Method DocumentationData not provided.
Procedure StepsData not provided.
Australia
Temporal Coverage
From 2000-02-18 to 2011-11-09 
Spatial Resolution

Data not provided.

Vertical Extent

Data not provided.

Data Quality Assessment Scope
Product completeness is dependent on the completeness of the underlying MODIS product, MCD43A4. The MCD43A4 product uses 16 day compositing to minimise the chance of failing to acquire data due to cloud cover, and to maximise the quality of the recorded reflectance. However, frequent cloud cover still prevents acquisition of data, most notably in the far northern tropical areas of Western Australia, Northern Territory and Queensland in the rainy season (November to April), and in Tasmania in the winter (June to August).
The RSMA is an index of total vegetation cover (green and non-photosynthetic vegetation), and so is also an index of soil exposure. Importantly this means that it is unit-less, and is not intended to report absolute vegetation or soil fraction. It may be possible to calibrate the RSMA to absolute fractions for a specific region, with appropriate field data, as was done in Clarke et al. (2011). 
Data Quality Report
Data not provided. 
Data Quality Assessment Outcome
Evaluation of RSMA and ARSMA with field data. The field fractional cover data reported in Section 2 (Clarke, 2011) was used to evaluate the RSMA and ARSMA. The first field survey date, 24 April 2010, was used as the baseline date for RSMA since this was the date with the greatest soil exposure. Comparison of the field cover and RSMA was performed by Pearson's correlation, and RMSE. These evaluations are documented in Clarke et al. (2011). 
ANZSRC - FOR
Climate change impacts and adaptation
Land capability and soil productivity
GCMD Sciences
BIOSPHERE - VEGETATION COVER
LAND SURFACE - SOIL EROSION
LAND SURFACE - SOILS
Horizontal Resolution
500 meters - < 1 km
Instruments
MODIS
Parameters
land condition index
Platforms
Aqua
Terra
Temporal Resolution
Weekly - < Monthly
Topic
environment
imageryBaseMapsEarthCover
User Defined
ARSMA
RSMA
Author
Clarke, Ken
Co-Author
Lewis, Megan
Contact Point
Clarke, Ken
Publisher
Terrestrial Ecosystem Research Network
Clarke, K., Lewis, M., Dutkiewicz, A., Forward, G., and Ostendorf, B., (2011) Spatial and Temporal Monitoring of Soil Erosion Risk with Satellite Imagery. Land Condition Monitoring Reports, Report 4. The University of Adelaide
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