Seasonal RGB Composite

Last modified by Tuan Le on 2019/04/09 15:14

Building upon monthly or seasonal means, the TU Wien seasonal RGB composites convey changes in land cover by setting each band of an RGB image to a mean covering different timespans of a year.

Product overview

The base dm Sentinel-1 time series.

Product description

The surface soil moisture estimate (SSM) represents the topmost soil layer (< 5 cm) and is given in degree of saturation , ranging from 0% (dry) to 100% (wet). can be converted into (absolute) volumetric units with the help of soil porosity information.

where is absolute soil moisture in , is porosity in . As it can be seen in the equation above, the accuracy of soil porosity is as much as important as the relative soil moisture content. The SSM images are encoded with the scale factor of 2 (e.g. SSM of 75.5%  corresponds to a pixel value of 145).

Areas without SSM measurements during the day have no data value of 255. Areas, where SSM retrieval is not possible, are masked out. The pixel data value is then set to 255 (no data value). Those areas include:

  • permanent water
  • areas with low sensitivity for SSM (e.g. urban areas)
  • steep terrain

Product variables

The Sentinel-1 product comprises the surface soil moisture variable. The following subsection and table will give an overview of the data format.

NameScaling factorUnitsTypeByte sizeNo -data
SSM2%uint81255

Overview of Sentinel-1 parameters.

Area and time period

SSM has been computing over the area of Austria from 01st January 2016 to the present.

Temporal resolution

SSM images are computed for every orbital overpass separately. There are Ascending (A) and Descending (D) overpasses. This means that each Sentinel-1 SSM image represents one overpass, and multiple overpasses can be averaged to obtain a mean image.

Image timestamps

The date, timestamp and direction of the SSM image acquisition can be found in the image file name. They can also be found in the metadata header of the original GeoTiff file.

Spatial resolution and sampling

Originally, the SSM images are tiled and georeferenced using the TU Wien Equi7(see Data specifications and formats) and have easting and northing coordinates with pixel spacing of 500m which correspond to a resolution of 1km.

Data format

The SSM data is originally stored and delivered in GeoTIFF format. GeoTIFF is a standard which allows storing georeferencing information within a TIFF raster image. For each day where Sentinel-1 SSM data is available, a GeoTIFF is created with the SSM measurements.

Limitations and caveats

The current algorithm to retrieve SSM from Sentinel-1 does not account for vegetation dynamics. This can lead to biases in the soil moisture which vary with vegetation dynamics. Soil moisture cannot be retrieved over deserts and high vegetation areas like tropical forests. Although a terrain correction is performed, it does not completely remove the influence of topography. Especially over high mountain ranges, this limitation comes into effect. In addition, no reliable soil moisture measurements can be done during frozen or snow-covered conditions. At the moment no mask or flag is in place for these conditions (e.g. frozen soil, snow cover, open water) and thus it is left to the user to judge whether the SSM data is meaningful or not. Users are advised to use the best auxiliary data available to improve the flagging of snow, frozen soil and (temporary) standing water. However, under the following conditions an SSM retrieval from Sentinel-1 should be most suited: low to moderate vegetation regimes, unfrozen and no snow, low to moderate topographic variations, no wetlands, and coastal areas.

Linear artefacts can be seen in the individual SSM images. Although calibration is performed by ESA on the three parallel sub-swaths, a number of orbits are still affected by scalloping (a bias in the backscatter per sub-swath). Although visually unappealing to the user, the error is of low magnitude and has only little effect on the temporal signal.

Lastly, some images are affected by Radio Frequency Interference (RFI) stemming from ground-based C-band transmitting systems. Unfortunately, the RFI cannot be removed by ESA or by the SSM algorithm.

Sentinel-1 SSM image over eastern Poland on 04/10/2014. Scalloping causes jump in the soil moisture images, along with the edges of the backscatter image’s sub-swaths.

Sentinel-1 Seasonal RGB Composite product at 10m spatial sampling over South West Pavia, Italy. Red band, green band and blue band are represented by Sentinel-1 VV polarisation image of June 2017, Sentinel-1 VH polarisation of July 2017 and the cross-ratio (VH/VV) of August 2017, respectively.

Product NameSeasonal RGB composite
Code NameS-COMP
CategorySentinel-1 products
Spatial Sampling10m
Temporal Resolution1 month
UnitdB (scaled)

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