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CVA service specifications


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Service Description

The Change Vector Analysis (CVA) processing service derives a vector of differences between a set of pre- and post-event calibrated assets derived from the same mission.

The CVA algorithm derives from a N-dimensional space magnitude and direction of change between the two input single-band geophysical assets for date 1 and date 2.

Figure 1

Figure 1 - Schema describing the Change Vector Analysis algorithm. Image credits: Portland State University.

In this change detection service pairs of assets having the same CBN are extracted from pre- and post-event calibrated datasets to make a co-located stack.

Note

CVA requires at least two CBNs from pre- and post-event datasets (minimum 4 assets).

The standardization of inputs is made by removing the mean and scaling to unit variance. Later the CVA1 is applied followed by an automatic thresholding of the multidimensional change detection map based on the Otsu’s method2,3. The Otsu algorithm minimizes the intra-class intensity variance and returns a single intensity threshold which is then employed in the service for the binarization of the change. Thus, the output of the service is a binary map detecting changes before and after the event.

Note

the change detection is applied to all image pixels in the AOI thus clouds and/or water bodies will potentially be part of changes detected. Also change detection results depend on georeferencing accuracy of input pairs of pre- post-event single-band assets. The change detection of the image stack is made after a co-location of input single-band assets without a co-registration.

Inputs

The CVA service requires as input a pair of calibrated Datasets from SAR or Optical missions. Ideally, input SAR Datasets to be made with a pair of Calibrated Datasets from the same mission, track, and polarization.

Warning

This minimum number of single-band geophysical assets must be more than one per Calibrated Dataset. Therefore, CVA requires at least two CBNs from pre- and post-event datasets (minimum 4 assets).

Parameters

The CVA service requires a specified number of mandatory and optional parameters. Table 1 describes the service parameters.

Parameter Description Required Default value
Input pre-event product reference Pre-event input product to be used in creating the collocated stack and performing CVA. YES
Input post-event product reference Post-event input product to be used in creating the collocated stack and performing CVA. YES
List(s) of comma separated bands This parameter is a list of bands expressed as a comma separated list of common band names. It defines the list of common band names to extract. List of single band assets to be extracted from the calibrated dataset before and after the event. The service requires the same assets in the pre- and post-event calibrated datasets. YES
Area of Interest This parameter defines the area of interest expressed as a Well-Known Text value. If set, it overrides the automatic determination of the maximum common area between the input-reference products geometry. YES

Table 1 - Service parameters for the CVA processor.

Input pre- and post-event product references

The pre-event and post-event Calibrated datasets input products to be used in creating the collocated stack and performing CVA.

List-of-comma-separated-bands

This second mandatory parameter is a list of bands expressed as a comma separated list of common band names. The list of single-band geophysical assets to be used for the co-location shall be given as a list of comma separated CBN.

Example

To define multiple reflectance single-band assets from VIS and NIR (e.g. blue, green, red, and nir) from pre- and post-event Calibrated Dataset, the user shall define the 4 input assets in CVA as following:

blue,green,red,nir

AOI

This last parameter may define the area of interest expressed as a Well-Known Text value.

Tip

In the definition of “Area of interest as Well Known Text” it is possible to apply as AOI the drawn polygon defined with the area filter. To do so, click on the :fontawesome-solid-magic: button in the left side of the "Area of interest expressed as Well-known text" box and select the option AOI from the list. The platform will automatically fill the parameter value with the rectangular bounding box taken from the current search area in WKT format.

Output

The result product of the CVA service is a single-band change detection binary map (1 change, 0 no change) GeoTIFF in COG format. Product specifications for this service are shown in the below Table.

Attribute Value / description
Long Name CVA change detection map
Short Name cva-change-mask
Description Binary change mask: 0=No-change, 1=Change
Data Type 1-bit
Band Single
Format COG
Projection Native or EPSG:4326 - WGS84
Units N/A
Valid Range [0 - 1]

  1. Bovolo F. and Bruzzone L., “A Theoretical Framework for Unsupervised Change Detection Based on Change Vector Analysis in the Polar Domain,” IEEE Trans. Geosci. Remote Sens., vol. 45, no. 1, pp. 218–236, 2007. DOI: 10.1109/TGRS.2006.885408

  2. Otsu’s method, wikipedia

  3. Nobuyuki Otsu (1979). "A threshold selection method from gray-level histograms". IEEE Trans. Sys. Man. Cyber. 9 (1): 62–66. DOI 10.1109/TSMC.1979.4310076