# IRIS tutorial

This service performs a Change Detection using a pair of calibrated optical single band assets acquired from the same sensor. The output is represented by Structural Similarity Index maps that show the intensity of the detected changes in the region of interest.

IRIS service description and specifications are available in this section.

## Select the processing service

After the opening of the activation workspace, in the right panel of the interface, open the Processing Services tab.

Select the processing service Change Detection Analysis (IRIS).

The "Change Detection Analysis (IRIS)" panel is displayed with parameters values to be filled-in.

## Find the data using multiple filter criteria

Select the area for which you want to do an analysis, e.g over South-eastern France.

From the Navigation and Search toolbar (located in the upper left side of the map), click on the Spatial Filter and draw a square AOI over the Riviera resort of Saint Tropez in the Var Department, France. This spatial filter allows you to select only the EO data acquired over this area.

From the top of the left panel, use Filter Criterias to search for Optical and sentinel-2 data collections from the list.

After the query the list will be updated as the one shown in the next image.

Now it is possible to choose a pair of pre- and post-event reflectance images from Optical Calibrated Datasets to be used for the change detection analysis. This pair must come from the same sensor.

As an example you can choose the following pair:

• Pre-event calibrated dataset: [CD] SENTINEL-2B MSI L2A 108 2021/08/02 10:25:59

• Post-event calibrated dataset: [CD] SENTINEL-2A MSI L2A 108 2021/08/27 10:30:21

## Fill the parameters

After the definition of spatial and time filters, you can employ IRIS, by using a suitable pair of Calibrated Datasets from Sentinel-2 data.

To do so you can fill the parameters as described in the following sections.

### Job name

• Insert as job name:
IRIS Sentinel-2 02/08 - 27/08 2021 Wildfire Var France


### Input pair of single-band geophysical assets

First two mandatory parameters are input "Reference" and "Secondary" images from Optical Calibrated Datasets. This parameter is required to specify both the reference to the Calibrated Dataset and the band to be use for the change detection analysis by specifying the CBN (e.g. nir).

Hint

To consults the bands of a Calibrated Dataset just Click on Show assets button available near the feature title. After the click a list with all single-band assets (CBNs) included within the Calibrated Dataset will appear under the feature title.

Thus, drag and Drop the selected assets:

1. single-band geophysical asset from a pre-event Calibrated Dataset (Reflectance) for CBN = nir

2. single-band geophysical asset from a post-event Calibrated Dataset (Reflectance) for CBN = nir

in the Optical calibrated pre-event single band asset and Optical calibrated post-event single band asset fields respectively.

Warning

Users must drag and drop the single-band asset (e.g. "red") into both Optical calibrated pre-event single band asset and Optical calibrated post-event single band asset fields. The drag and drop of the Calibrated Dataset (e.g. "[CD] SENTINEL-2A MSI L2A 46 2021/12/11 02:31:11") is not enough.

### Window size

Insert as a value for the window size the value of 39.

Note

This value defines the size of the sliding window in pixels, this parameter can highly influence the result of the analysis. The higher this parameter is set, the more averaged the change map will be, while the smaller and the more detailed changes can be identified at the cost of potentially noisier results. This is due to the SSIM value for each pixel being computed using the information present in the whole sliding window, thus obtaining a more localized value of the index in case of a smaller window.

Warning

The dimension of the window should be set in a range between 9 and 71. Inserted value must be odd. If the inserted value is even or is outside this range, a warning will be given to the user.

### Threshold

Insert as a threshold the value of 0.4. This value will be used by the processor for the binarization of SSI and detecting change contours.

### Co-registration

Insert, for example, the value Rigid to employ a rigid co-registration of secondary and reference input assets. The full-field displacement measured is used to estimate an Affine transformation matrix which is then applied to the secondary image.

### Area of interest expressed as Well-known text (optional)

The “Area of interest as Well Known Text” can be defined by using the drawn polygon defined with the area filter.

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 the from current search area in WKT format.

Note

This parameter is optional.

## Run the job

Click on the button Run Job and see the Running Job

You can monitor job progress through the progress bar.

Once the job is completed, click on the Show results button located at the bottom of the processing service panel.

Tip

You can also save the parameters employed in this job by clicking on the Export params button in the right panel. This allows you to copy all your entries to the clipboard. This is meant to be used for a quick re-submission of a similar job after a fine tuning of the parameters (e.g. to add a color formula later).

Below is reported the syntax which includes all the parameters employed in this example.

{
"pre_event": "https://catalog.disasterscharter.org//charter/cat/[chartercalibrateddataset,!excluded,{callid932}]/search?format=json&uid=call932_S2B_MSIL2A_20210802T102559_N0301_R108_T31TGJ_20210802T133728-calibrated#nir",
"post_event": "https://catalog.disasterscharter.org//charter/cat/[chartercalibrateddataset,!excluded,{callid932}]/search?format=json&uid=call932_S2A_MSIL2A_20210827T103021_N0301_R108_T31TGJ_20210827T151224-calibrated#nir",
"win_size": "39",
"threshold": "0.4",
"coreg_type": "Rigid",
"aoi": "POLYGON((6.31 43.232,6.31 43.44,6.633 43.44,6.633 43.232,6.31 43.232))"
}


### Visualization

See the result on the map. The preview appears within the area defined in the spatial filter.

To get more information about the product just click on the preview in the map, a bubble showing the name of the layer IRIS Change detection for S2B_MSIL2A_20210802T102559_N0301_R108_T31TGJ_20210802T133728-calibrated and S2A_MSIL2A_20210827T103021_N0301_R108_T31TGJ_20210827T151224-calibrated will appear and then click on the Show details button.

Tip

To quickly access Product Details double click on the layer from the Results list.

In the left panel of the interface, the details of Job Result will appear with Product metadata. Furthermore by clicking on Layer styling you can also access to the View options.

In here it is possible to see histogram/s of the Product which is visible in the map, set color formula, change Filters (e.g. Brightness, Opacity).

Tip

To visually compare the SSI overview product with the underlying base layer (e.g. Natural Earth or Dark map) you can set the Opacity filter under View options as 40%.

In the left panel under the result Details is possible to switch from the default asset to another one included into the IRIS results by clicking on Layer Styling and Select Assets. To visualize another asset on the map just select another asset:

ssi asset

iris-change-mask asset

contours asset

In the left panel under the result Details is possible to create customized overview on the fly by clicking on Layer Styling and Combine Assets. As an example under Combine Assets you can create on the fly a Red-Cyan band composite by setting the nir_pre single-band asset in the RED channel, and the co-registered nir_post one in the GREEN and BLUE channels.

This Red-Cyan band composite highlights vegetation changes derived from Sentinel-2 data. In red is shown the loss of vegetation due to wildfires.

• nir_pre: single-band geophysical asset nir product from pre-event image as single band GeoTIFF in COG format,
• nir_post: single-band geophysical asset nir product from post-event image as single band GeoTIFF in COG format,
• overview-iris: multi-band visual asset derived from the ssi asset given as RGBA given as 4-band GeoTIFF in COG format,
• iris-change-mask: single-band binary map asset from thresholding of the ssi asset given as UInt8 single band GeoTIFF in COG format,