STACK tutorial

This service provides a multi-mission and multi-temporal image stack of multiple co-located single-band assets against a reference one. The service supports single band assets taken from Optical or Radar Calibrated Datasets, Auxiliary Datasets or Results of other processors. It performs resampling and warping of secondary assets and the stacking of each secondary with the reference. It can also generate assets from the co-located stack using band arithmetic.

STACK 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 and select the processing service Co-located stacking (STACK).

The Co-located stacking (STACK) panel is displayed in the right panel of the interface with a series of parameters values to be filled-in.

Use cases

STACK is an advanced processing service that does not only perform a co-location of multi-sensor single band assets, but thanks to its band arithmetic function it can be used for multiple applications. Below are listed some possible use cases:

1. Evaluate changes in spectral indexes from a co-located stack of pre- and post-event images from the same sensor,

2. Evaluate NDVI changes from a co-located stack of pre- and post-event images from different sensors,

3. Generate multiple differential normalized indices from a multi-temporal co-located stack of images from the same sensor using optical EO data,

4. Generate a multi-temporal co-located stack of images from the same sensor using SAR EO data,

5. Generate NDVI loss map from a co-located stack of pre- and post-event reflectance assets derived from the same sensor,

6. Generate coherence loss map from a co-located stack of pre- and post-event coherence assets derived from the same sensor.

Use case 1: evaluate changes in spectral indexes from a co-located stack of pre- and post-event images from the same sensor

Find the data using multiple filter criteria

Choose an area in which you want to focus your analysis (e.g in Ban Lam Narai, Thailand).

From the Navigation and Search toolbar (located in the upper left side of the map), click on “Spatial Filter” and draw a square around the Ban Lam Narai city near Pa Sak river. This spatial filter allows you to select only the EO data acquired over this area.

From the top of the left panel, use Filter Criteria to search for Pleiades-1a and Pleiades-1b data collections.

Once these filters are in place the Result list is updated as shown in the below figure.

Fill the parameters

After the definition of spatial and time filters, you can apply the co-located stacking, by importing, for example, four single-band assets from a pair of Pleiades-1 Calibrated Datasets. In this example the first input calibrated dataset is the Pleiades-1B MS ORTHO [CD] acquired on 30/09/2021, the second one is the Pleiades-1A MS ORTHO [CD] acquired on 01/10/2021.

Job name

Insert as job name:

STACK Pleiades-1 30/09 01/10 2021 Flood in Thailand

Input references

Drag and Drop in the "Input product reference(s)” field the following calibrated datasets:

1. [CD] PLEIADES-1B PHR-1B ORTHO/BASIC 2021/09/30 04:07:39,

2. [CD] PLEIADES-1A PHR-1A ORTHO/BASIC 2021/10/01 03:59:28.

Bands

Insert the list of single-band geophysical assets from the given pair of calibrated datasets in the "List(s) of comma separated band(s)” field. Inserted comma separated bands must follow the following convention:

reference_number.single_band_asset

Therefore, to create NDVI and NDWI pre- and post-event from multiple co-located assets in STACK the red, green, and nir geophysical single-band assets from each of the two calibrated datasets must be inserted as following:

1.green,1.red,1.nir,2.green,2.red,2.nir

Area of interest expressed as Well-known text

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

S-expression

The remaining optional parameter to be filled in is the one dedicated for generating new bands from the ones present in the stack using s-expressions. In STACK a new band generated from the image stack is defined with a band name and it's associated s-expression separated by a colon : .

output_band_name:(s-expression)

To generate NDVI and NDWI spectral indexes from pre- and post-event datasets, insert the following s-expressions to generate four new bands in the image stack using the six input multispectral ones:

ndvi_pre:(norm_diff 1.nir 1.red)

ndvi_post:(norm_diff 2.nir 2.red)

ndwi_pre:(norm_diff 1.green 1.nir)

ndwi_post:(norm_diff 2.green 2.nir)

Once all parameters are inserted the processing service panel shall appear as the one shown in the figure below.

Run the job

Click on the button Run Job and see the Running Job. You can monitor job progress through the progress bar.

Results: download and visualization

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

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

{
   "input_reference": [
      "https://catalog.disasterscharter.org//charter/cat/[chartercalibrateddataset,{callid844}]/search?format=json&uid=call844_DS_PHR1B_202109300407024_FR1_PX_E101N15_0306_01095-calibrated",
      "https://catalog.disasterscharter.org//charter/cat/[chartercalibrateddataset,{callid844}]/search?format=json&uid=call844_DS_PHR1A_202110010358514_FR1_PX_E101N15_0306_01186-calibrated"
   ],
   "bands": "1.green,1.red,1.nir,2.green,2.red,2.nir",
   "aoi": "POLYGON((101.156 15.202,101.156 15.233,101.186 15.233,101.186 15.202,101.156 15.202))",
   "s_expressions": [
      "ndvi_pre:(norm_diff 1.nir 1.red)",
      "ndvi_post:(norm_diff 2.nir 2.red)",
      "ndwi_pre:(norm_diff 1.green 1.nir)",
      "ndwi_post:(norm_diff 2.green 2.nir)"
   ]
}

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 “Co-located stack from DS_PHR1B_202109300407024_FR1_PX_E101N15_0306_01095-calibrated, DS_PHR1A_202110010358514_FR1_PX_E101N15_0306_01186-calibrated” will appear and then click on the Show details button.

In the left panel under the result Details is possible to customize the 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 ndwi_post band in the red channel, and ndwi_pre in the green and blue channels.

This Red-Cyan band composite highlights NDWI changes derived from Pleiades-1 data. In cyan is shown the water receding after the peak of the flood event.

Download

In this first use case the Co-located stacking (STACK) service returned as output the following products:

• 1.green co-located single-band geophysical asset with CBN green from the first input calibrated dataset,
• 1.red co-located single-band geophysical asset with CBN red from the first input calibrated dataset,
• 1.nir co-located single-band geophysical asset with CBN nir from the first input calibrated dataset,
• 2.green co-located single-band geophysical asset with CBN green from the second input calibrated dataset,
• 2.red co-located single-band geophysical asset with CBN red from the second input calibrated dataset,
• 2.nir co-located single-band geophysical asset with CBN nir from the second input calibrated dataset,
• ndvi_pre NDVI single-band geophysical asset derived from co-located 1.red and 1.nir assets using the first inserted s-expression,
• ndvi_post NDVI single-band geophysical asset derived from co-located 2.red and 2.nir assets using the second inserted s-expression,
• ndwi_pre NDWI single-band geophysical asset derived from co-located 1.green and 1.nir assets using the third inserted s-expression,
• ndwi_post NDWI single-band geophysical asset derived from co-located 2.green and 2.nir assets using the last inserted s-expression.

All of them are given as single band GeoTIFF in COG format. These products can be downloaded by clicking on the Download button located at the bottom of the Product Details tab in the left panel.

Use case 2: evaluate NDVI changes from a co-located stack of pre- and post-event images from different sensors

Find the data using multiple filter criteria

Choose an area in which you want to focus your analysis (e.g in Baybay, Philippines).

From the Navigation and Search toolbar (located in the upper left side of the map), click on “Spatial Filter” and draw a square around the north western of Baybay municipality. This spatial filter allows you to select only the EO data acquired over this area.

From the top of the left panel, use Filter Criteria to search for Pleiades-1a, Pleiades-1b and Worldview-2 data collections.

Once these filters are in place the Result list is updated as shown in the below figure.

Fill the parameters

After the definition of spatial and time filters, you can apply the co-located stacking, by importing, for example, four single-band assets a Worldview-2 (pre-event) and Pleiades-1 (post-event) Calibrated Datasets. In this example the first input calibrated dataset is the Worldview-2 MSI L1B [CD] acquired on 24/05/2020, the second is the Pleiades-1A MS ORTHO [CD] acquired on 17/04/2022.

Job name

Insert as job name:

STACK - NDVI change - Landslide in Baybay Philippines Apr 2022

Input references

Drag and Drop in the "Input product reference(s)” field the following calibrated datasets:

1. [CD] WORLDVIEW-2 MSI LV1B 2020-05-24 02:02:22,

2. [CD] PLEIADES-1A PHR-1A ORTHO/BASIC 2022-04-17 01:58:50.

Bands

Insert the list of single-band geophysical assets from the given pair of calibrated datasets in the "List(s) of comma separated band(s)” field. Inserted comma separated bands must follow the following convention:

reference_number.single_band_asset

Therefore, to create NDVI pre- and post-event from multiple co-located assets in STACK the red, and nir08 geophysical single-band assets from the Worldview-2 calibrated dataset and the red, and nir geophysical single-band assets from the Pleiades-1A calibrated dataset must be inserted as following:

1.red,1.nir08,2.red,2.nir

Area of interest expressed as Well-known text

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

S-expression

The remaining optional parameter to be filled in is the one dedicated for generating new bands from the ones present in the stack using s-expressions. In STACK a new band generated from the image stack is defined with a band name and it's associated s-expression separated by a colon : .

output_band_name:(s-expression)

To generate NDVI spectral indexes from pre- and post-event datasets, insert the following s-expressions to generate four new bands in the image stack using the six input multispectral ones:

ndvi_pre:(norm_diff 1.nir08 1.red)

ndvi_post:(norm_diff 2.nir 2.red)

Run the job

Click on the button Run Job and see the Running Job. You can monitor job progress through the progress bar.

Results: download and visualization

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

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

{
   "input_reference": [
      "https://catalog.disasterscharter.org//charter/cat/[chartercalibrateddataset,{callid869}]/search?format=json&uid=call869_WV02N10_679722E124_8037502020052400000000MS00-calibrated",
      "https://catalog.disasterscharter.org//charter/cat/[chartercalibrateddataset,{callid869}]/search?format=json&uid=call869_DS_PHR1A_202204170158146_FR1_PX_E124N10_1019_00936-calibrated"
   ],
   "bands": "1.nir08,1.red,2.nir,2.red",
   "aoi": "POLYGON((124.835 10.664,124.835 10.685,124.858 10.685,124.858 10.664,124.835 10.664))",
   "s_expressions": [
      "ndvi_pre:(norm_diff 1.nir08 1.red)",
      "ndvi_post:(norm_diff 2.nir 2.red)"
   ]
}

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 “Co-located stack from WV02N10_679722E124_8037502020052400000000MS00-calibrated, DS_PHR1A_202204170158146_FR1_PX_E124N10_1019_00936-calibrated” will appear and then click on the Show details button.

In the left panel under the result Details is possible to customize the 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 ndwi_post band in the red channel, and ndwi_pre in the green and blue channels.

This Red-Cyan band composite highlights NDVI changes derived from Worldview-2 and Pleiades data. In red is shown the vegetation loss due to a landslide near Baybay.

Download

In this second use case the Co-located stacking (STACK) service returned as output the following products:

• 1.red co-located single-band geophysical asset with CBN red from the first input calibrated dataset,
• 1.nir co-located single-band geophysical asset with CBN nir08 from the first input calibrated dataset,
• 2.red co-located single-band geophysical asset with CBN red from the second input calibrated dataset,
• 2.nir co-located single-band geophysical asset with CBN nir from the second input calibrated dataset,
• ndvi_pre NDVI single-band geophysical asset derived from co-located 1.red and 1.nir08 assets using the first inserted s-expression,
• ndvi_post NDVI single-band geophysical asset derived from co-located 2.red and 2.nir assets using the second inserted s-expression,

All of them are given as single band GeoTIFF in COG format. These products can be downloaded by clicking on the Download button located at the bottom of the Product Details tab in the left panel.

Use case 3: generate multiple differential normalized indices from a multi-temporal co-located stack of images from the same sensor using optical EO data

Find the data using multiple filter criteria

Choose an area in which you want to focus your analysis (e.g in Northern California, US).

From the Navigation and Search toolbar (located in the upper left side of the map), click on Spatial Filter and draw a square around over Lassen and Butten counties in California, US. This spatial filter allows you to select only the EO data acquired over this area.

From the top of the left panel, use Filter Criteria to search for Sentinel-2 data collections.

Once these filters are in place the Result list is updated as shown in the below figure.

Fill the parameters

After the definition of spatial and time filters, you can apply the co-located stacking, by importing, for example, twelve single-band assets from six Sentinel-2 Calibrated Datasets. In this example the input calibrated datasets are: Sentinel-2A/B L2A [CD] acquired on 13/07/2021, 18/07/2021, 23/07/2021, 28/07/2021, 02/08/2021, and 01/09/2021.

Job name

Insert as job name:

STACK Sentinel-2 from 13/07 to 01/09 2021 Fire in the US

Input references

Drag and Drop in the "Input product reference(s)” field the following calibrated datasets:

1. [CD] SENTINEL-2A MSI L2A 113 2021/07/13 18:49:19,

2. [CD] SENTINEL-2A MSI L2A 113 2021/07/18 18:49:19,

3. [CD] SENTINEL-2B MSI L2A 113 2021/07/23 18:49:19,

4. [CD] SENTINEL-2A MSI L2A 113 2021/07/28 18:49:19,

5. [CD] SENTINEL-2B MSI L2A 113 2021/08/02 18:49:19,

6. [CD] SENTINEL-2B MSI L2A 113 2021/09/01 18:49:19.

Bands

Insert the list of single-band geophysical assets from the given pair of calibrated datasets in the "List(s) of comma separated band(s)” field. Inserted comma separated bands must follow the following convention:

reference_number.single_band_asset

Therefore, to generate five dNBR indexes from six pairs of nir, and swir22 geophysical single-band assets derived from six calibrated datasets the following list can be inserted:

1.nir,1.swir22,2.nir,2.swir22,3.nir,3.swir22,4.nir,4.swir22,5.nir,5.swir22,6.nir,6.swir22

Area of interest expressed as Well-known text

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

S-expression

The remaining optional parameter to be filled in is the one dedicated for generating new bands from the ones present in the stack using s-expressions. In STACK a new band generated from the image stack is defined with a band name and it's associated s-expression separated by a colon : .

output_band_name:(s-expression)

To generate five dNBR indexes from the six input calibrated datasets, insert the following s-expressions to generate five new bands in the image stack using the twelve input multispectral ones:

dNBR1:(- (norm_diff 1.nir 1.swir22) (norm_diff 2.nir 2.swir22))

dNBR2:(- (norm_diff 2.nir 2.swir22) (norm_diff 3.nir 3.swir22))

dNBR3:(- (norm_diff 3.nir 3.swir22) (norm_diff 4.nir 4.swir22))

dNBR4:(- (norm_diff 4.nir 4.swir22) (norm_diff 5.nir 5.swir22))

dNBR5:(- (norm_diff 5.nir 5.swir22) (norm_diff 6.nir 6.swir22))

Run the job

Click on the button Run Job and see the Running Job. You can monitor job progress through the progress bar.

Results: download and visualization

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

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

{
   "input_reference": [
      "https://catalog.disasterscharter.org//charter/cat/[chartercalibrateddataset,{callid1016}]/search?format=json&uid=call1016_S2B_MSIL2A_20210713T184919_N0301_R113_T10TFK_20210713T213143-calibrated",
      "https://catalog.disasterscharter.org//charter/cat/[chartercalibrateddataset,{callid1016}]/search?format=json&uid=call1016_S2A_MSIL2A_20210718T184921_N0301_R113_T10TFK_20210718T225851-calibrated",
      "https://catalog.disasterscharter.org//charter/cat/[chartercalibrateddataset,{callid1016}]/search?format=json&uid=call1016_S2B_MSIL2A_20210723T184919_N0301_R113_T10TFK_20210723T214031-calibrated",
      "https://catalog.disasterscharter.org//charter/cat/[chartercalibrateddataset,{callid1016}]/search?format=json&uid=call1016_S2A_MSIL2A_20210728T184921_N0301_R113_T10TFK_20210728T230926-calibrated",
      "https://catalog.disasterscharter.org//charter/cat/[chartercalibrateddataset,{callid1016}]/search?format=json&uid=call1016_S2B_MSIL2A_20210802T184919_N0301_R113_T10TFK_20210802T213522-calibrated",
      "https://catalog.disasterscharter.org//charter/cat/[chartercalibrateddataset,{callid1016}]/search?format=json&uid=call1016_S2B_MSIL2A_20210901T184919_N0301_R113_T10TFK_20210901T214918-calibrated"
   ],
   "bands": "1.nir,1.swir22,2.nir,2.swir22,3.nir,3.swir22,4.nir,4.swir22,5.nir,5.swir22,6.nir,6.swir22",
   "aoi": "POLYGON((-121.523 39.809,-121.523 40.361,-120.786 40.361,-120.786 39.809,-121.523 39.809))",
   "s_expressions": [
      "dNBR1:(- (norm_diff 1.nir 1.swir22) (norm_diff 2.nir 2.swir22))",
      "dNBR2:(- (norm_diff 2.nir 2.swir22) (norm_diff 3.nir 3.swir22))",
      "dNBR3:(- (norm_diff 3.nir 3.swir22) (norm_diff 4.nir 4.swir22))",
      "dNBR4:(- (norm_diff 4.nir 4.swir22) (norm_diff 5.nir 5.swir22))",
      "dNBR5:(- (norm_diff 5.nir 5.swir22) (norm_diff 6.nir 6.swir22))"
   ]
}

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 “Co-located stack from S2B_MSIL2A_20210713T184919_N0301_R113_T10TFK_20210713T213143-calibrated, S2A_MSIL2A_20210718T184921_N0301_R113_T10TFK_20210718T225851-calibrated and other datasets or products” will appear and then click on the Show details button.

In the left panel under the result Details is possible to customize the 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 RGB band composite by setting dNBR1 in the red channel, dNBR3 in the green channel, and dNBR5 in the blue channels.

Download

In this third use case the Co-located stacking (STACK) service returned as output the following products:

• 1.nir co-located single-band geophysical asset with CBN nir from the 1st input calibrated dataset,
• 1.swir22 co-located single-band geophysical asset with CBN swir22 from the 1st input calibrated dataset,
• 2.nir co-located single-band geophysical asset with CBN nir from the 2nd input calibrated dataset,
• 2.swir22 co-located single-band geophysical asset with CBN swir22 from the 2nd input calibrated dataset,
• 3.nir co-located single-band geophysical asset with CBN nir from the the 3rd calibrated dataset,
• 3.swir22 co-located single-band geophysical asset with CBN swir22 from the 3rd input calibrated dataset,
• 4.nir co-located single-band geophysical asset with CBN nir from the 4th input calibrated dataset,
• 4.swir22 co-located single-band geophysical asset with CBN swir22 from the 4th input calibrated dataset,
• 5.nir co-located single-band geophysical asset with CBN nir from the 5th input calibrated dataset,
• 5.swir22 co-located single-band geophysical asset with CBN swir22 from the 5th input calibrated dataset,
• 6.nir co-located single-band geophysical asset with CBN nir from the 6th input calibrated dataset,
• 6.swir22 co-located single-band geophysical asset with CBN swir22 from the 6th input calibrated dataset,
• dNBR1 dNBR single-band geophysical asset derived from co-located 1.nir and 1.swir22 assets using the 1st inserted s-expression,
• dNBR2 dNBR single-band geophysical asset derived from co-located 2.nir and 2.swir22 assets using the 2nd inserted s-expression,
• dNBR3 dNBR single-band geophysical asset derived from co-located 3.nir and 3.swir22 assets using the 3rd inserted s-expression,
• dNBR4 dNBR single-band geophysical asset derived from co-located 4.nir and 4.swir22 assets using the 4th inserted s-expression,
• dNBR5 dNBR single-band geophysical asset derived from co-located 5.nir and 5.swir22 assets using the 5th inserted s-expression.

All of them are given as single band GeoTIFF in COG format. These products can be downloaded by clicking on the Download button located at the bottom of the Product Details tab in the left panel.

Use case 4: generate a multi-temporal co-located stack of images from the same sensor using SAR EO data

Find the data using multiple filter criteria

Choose an area in which you want to focus your analysis (e.g in Zambezia province, Mozambique).

From the Navigation and Search toolbar (located in the upper left side of the map), click on “Spatial Filter” and draw a square around Licungo floodplain, Mozambique. This spatial filter allows you to select only the EO data acquired over this area.

From the top of the left panel, use Filter Criteria to search for Sentinel-1 data collection.

Once these filters are in place the Result list is updated as shown in the below figure.

Fill the parameters

After the definition of spatial and time filters, you can apply the co-located stacking, by importing, for example, three single-band assets from three Sentinel-1 Calibrated Datasets. In this example the input calibrated datasets are: Sentinel-1A GRD [CD] acquired on 16/01/2022, 28/01/2022, 09/02/2022.

Job name

Insert as job name:

STACK - S1 Sigma0 diff from average 16/01-09/02- Tropical Storm in Mozambique

Input references

Drag and Drop in the "Input product reference(s)” field the following calibrated datasets:

1. [CD] SENTINEL-1A GRD IW VV/VH 108 2022-02-09 03:00:31,

2. [CD] SENTINEL-1A GRD IW VV/VH 108 2022-01-28 03:00:31,

3. [CD] SENTINEL-1A GRD IW VV/VH 108 2022-01-16 03:00:32.

Bands

Insert the list of single-band geophysical assets from the given pair of calibrated datasets in the "List(s) of comma separated band(s)” field. Inserted comma separated bands must follow the following convention:

reference_number.single_band_asset

Assuming to work only with co-pol assets in VV polarization, three s0_db_c_vv geophysical single-band assets derived from the three selected calibrated datasets can be specified as input bands by inserting:

1.s0_db_c_vv,2.s0_db_c_vv,3.s0_db_c_vv

Area of interest expressed as Well-known text

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

S-expression

The remaining optional parameter to be filled in is the one dedicated for generating new bands from the ones present in the image stack using s-expressions. In STACK a new band generated from the image stack is defined with a band name and it's associated s-expression separated by a colon : .

output_band_name:(s-expression)

The 4 new Assets to be generated are the average backscatter (average of the value of each of the 3 Assets at pixel level) and the 3 differences between the backscatter value (for each of the 3 observation dates) and the average backscatter. To compute them provide the following 4 s-expressions that are using the three input assets (Sigma Nought co-pol of each acquisition). For instance average is the arithmetic average of three backscatter assets (Asset1+Asset2+Asset3)/3 and diff_from_average1 is the difference between the backscatter value of Asset 1 (first observation date) and the average backscatter value Asset1-((Asset1+Asset2+Asset3)/3).

average:(/ (+ 1.s0_db_c_vv 2.s0_db_c_vv 3.s0_db_c_vv) 3)

diff_from_average1:(- 1.s0_db_c_vv (/ (+ 1.s0_db_c_vv 2.s0_db_c_vv 3.s0_db_c_vv) 3))

diff_from_average2:(- 2.s0_db_c_vv (/ (+ 1.s0_db_c_vv 2.s0_db_c_vv 3.s0_db_c_vv) 3))

diff_from_average3:(- 3.s0_db_c_vv (/ (+ 1.s0_db_c_vv 2.s0_db_c_vv 3.s0_db_c_vv) 3))

Run the job

Click on the button Run Job and see the Running Job. You can monitor job progress through the progress bar.

Results: download and visualization

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

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

{
   "input_reference": [
      "https://catalog.disasterscharter.org//charter/cat/[chartercalibrateddataset,{callid859}]/search?format=json&uid=call859_S1A_IW_GRDH_1SDV_20220116T030032_20220116T030057_041480_04EEB8_7702-calibrated",
      "https://catalog.disasterscharter.org//charter/cat/[chartercalibrateddataset,{callid859}]/search?format=json&uid=call859_S1A_IW_GRDH_1SDV_20220128T030031_20220128T030056_041655_04F4A1_7A3D-calibrated",
      "https://catalog.disasterscharter.org//charter/cat/[chartercalibrateddataset,{callid859}]/search?format=json&uid=call859_S1A_IW_GRDH_1SDV_20220209T030031_20220209T030056_041830_04FAC0_EB2F-calibrated"
   ],
   "bands": "1.s0_db_c_vv,2.s0_db_c_vv,3.s0_db_c_vv",
   "aoi": "POLYGON((36.747 -18.378,36.747 -17.416,37.694 -17.416,37.694 -18.378,36.747 -18.378))",
   "s_expressions": [
      "average:(/ (+ 1.s0_db_c_vv 2.s0_db_c_vv 3.s0_db_c_vv) 3)",
      "diff_from_average1:(- 1.s0_db_c_vv (/ (+ 1.s0_db_c_vv 2.s0_db_c_vv 3.s0_db_c_vv) 3))",
      "diff_from_average2:(- 2.s0_db_c_vv (/ (+ 1.s0_db_c_vv 2.s0_db_c_vv 3.s0_db_c_vv) 3))",
      "diff_from_average3:(- 3.s0_db_c_vv (/ (+ 1.s0_db_c_vv 2.s0_db_c_vv 3.s0_db_c_vv) 3))"
   ]
}

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 “Co-located stack from S1A_IW_GRDH_1SDV_20220116T030032_20220116T030057_041480_04EEB8_7702-calibrated, S1A_IW_GRDH_1SDV_20220128T030031_20220128T030056_041655_04F4A1_7A3D-calibrated and other datasets or products” will appear and then click on the Show details button.

In the left Result panel under Details is possible to customize the overview on the fly by clicking on Layer Styling and Combine Assets. As an example under Combine Assets you can create on the fly Red-Cyan band composite by setting average in the red channel, and diff_from_average2 in the green and blue channels.

Set as Min Max for average the desired values of Sigma Nought in dB: as an example [-25,-15] to highlight water. Define also Min and Max for the diff_from_average2 asset by selecting only negative values [-10,0] obtained from the difference between the 2.s0_db_c_vv and the average from all input scenes. The aims of this false color composite is to highlight permanent waters in cyan and increases of negative Sigma Nought in dB from averaged backscatter values in red (flood).

Download

In this fourth use case the Co-located stacking (STACK) service returned as output the following products:

• 1.s0_db_c_vv co-located single-band geophysical asset with CBN s0_db_c_vv from the 1st input calibrated dataset,
• 2.s0_db_c_vv co-located single-band geophysical asset with CBN s0_db_c_vv from the 2nd input calibrated dataset,
• 3.s0_db_c_vv co-located single-band geophysical asset with CBN s0_db_c_vv from the 3rd input calibrated dataset,
• average single-band geophysical asset derived from the average of co-located 1.s0_db_c_vv, 2.s0_db_c_vv and 3.s0_db_c_vv assets using the 1st inserted s-expression,
• diff_from_average1 single-band geophysical asset derived from the difference between 1.s0_db_c_vv and the average of input co-located assets using the 2nd inserted s-expression,
• diff_from_average2 single-band geophysical asset derived from the difference between 2.s0_db_c_vv and the average of input co-located assets using the 3rd inserted s-expression,
• diff_from_average3 single-band geophysical asset derived from the difference between 3.s0_db_c_vv and the average of input co-located assets using the 4th inserted s-expression.

All of them are given as single band GeoTIFF in COG format. These products can be downloaded by clicking on the Download button located at the bottom of the Product Details tab in the left panel.

Use case 5: generate NDVI loss map from a co-located stack of pre- and post-event NDVI assets derived from the same sensor

Find and access a Result from other on-demand services

Select the area for which you want to do an analysis e.g. over Northern California in the US. In this use case two Results from the OPT-Index are used to assess the NDVI change that occurred during the Dixie Fire event of 2021.

Access two successful OPT-Index jobs in the Right Panel Processing Services under the Jobs tab by clicking on the Show results button. Same OPT-Index processing results can also be listed in the left panel under theResults tab by clicking on My results or Shared results under the Results data context.

When selecting the pair of Results to be used for the Co-located Stacking drag ang drop the Results into the feature basket.

In this example the selected pair of OPT-Index results derived from Sentinel-2 L1C Calibrated Datasets are:

• Reference OPT-Index Result (before Dixie wildfire): OPT-Index - S2 13/07/2021 Dixie Fire, US

• Secondary OPT-Index Result (after Dixie wildfire): OPT-Index - S2 01/09/2021 Dixie Fire, US

Fill the parameters

After the identification of input OPT-Index Results, you can employ STACK, by using a suitable pair of normalized difference single band assets (e.g. ndvi assets) from the two OPT-Index Results derived with Sentinel-2 data. To do so you can fill the parameters as described in the following sections.

Job name

Insert as job name:

STACK - NDVI change Dixie wildfire 13/07-01/09 2021

Input references

Drag and Drop in the "Input product reference(s)” field the first (OPT-Index - S2 13/07/2021 Dixie Fire, US) and the second (OPT-Index - S2 01/09/2021 Dixie Fire, US) Result obtained from on-demand processing with the OPT-Index service.

Bands

Insert the list of single-band coherence assets from the given pair of OPT-Index results in the "List(s) of comma separated band(s)” field. Inserted comma separated bands must follow the following convention:

reference_number.single_band_asset

The two selected coherence assets can be specified as input bands by inserting:

1.ndvi,2.ndvi

S-expression

The remaining optional parameter to be filled in is the one dedicated for generating new bands from the ones present in the image stack using s-expressions. In STACK a new band generated from the image stack is defined with a band name and it's associated s-expression separated by a colon : .

output_band_name:(s-expression)

The 2 new Assets to be generated are the NDVI difference and the binary mask representing vegetation loss derived from thresholding of NDVI difference.

To compute them provide the following 2 s-expressions that are using the two input assets (NDVI from each Sentinel-2 CD pair). For instance ndvi_diff is the arithmetic difference of the two NDVI assets (ndvi2 - ndvi1) and ndvi_change is a binarization of NDVI difference (where (ndvi_diff >= threshold) set 1 else 0).

ndvi_diff:(- 1.ndvi 2.ndvi)

ndvi_change:(where (>= (- 1.ndvi 2.ndvi) 0.25) 1 0)

Run the job

Click on the button Run Job and see the Running Job. You can monitor job progress through the progress bar.

Results: download and visualization

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

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

{
   "input_reference": [
      "https://catalog.disasterscharter.org//VA_ESA_MArcorace/cat/9f6ddbdd21bab19b4cfd06ead3ab2576310521dd85c56641cc18cd2e61bc426a/search?format=json&uid=9f6ddbdd-spectral-index",
      "https://catalog.disasterscharter.org//VA_ESA_MArcorace/cat/9021a912bc8955392547133cffbbb1d52a7133fe1d41de793bc47bf2f1c6dd72/search?format=json&uid=9021a912-spectral-index"
   ],
   "bands": "1.ndvi,2.ndvi",
   "s_expressions": [
      "ndvi_diff:(- 1.ndvi 2.ndvi)",
      "ndvi_change:(where (>= (- 1.ndvi 2.ndvi) 0.25) 1 0)"
   ]
}

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 “Co-located stack from coherence_intensity, coherence_intensity” will appear and then click on the Show details button.

In the left Result panel under Details is possible to create an overview on the fly from co-located assets by clicking on Layer Styling and Combine Assets. As an example under Combine Assets you can create on the fly Red-Cyan NDVI band composite by setting 1.ndvi in the red channel, and 2.ndvi in the green and blue channels.

The NDVI difference generated from the two co-located ndvi assets with the first s-expression, can be seen in the map by clicking on Layer Styling and under Select Assets by selecting the ndvi_diff single band asset.

The result from the binarization of the NDVI difference obtained with the second s-expression, can be seen in the map by clicking on Layer Styling and under Select Assets by selecting the ndvi_change single band asset.

Download

In this fifth use case the Co-located stacking (STACK) service returned as output the following products:

• 1.ndvi: single band asset for the co-located 1.ndvi asset from the 1st input Result,
• 2.ndvi: single band asset for the co-located 2.ndvi asset from the 2nd input Result,
• ndvi_diff single-band asset representing the difference of co-located 1.ndvi and 2.ndvi assets derived with the 1st inserted s-expression,
• ndvi_change single-band asset a binary mask ok NDVI loss from the difference of co-located 1.ndvi and 2.ndvi assets derived with the 2nd inserted s-expression.

All of them are given as single band GeoTIFF in COG format. These products can be downloaded by clicking on the Download button located at the bottom of the Product Details tab in the left panel.

Use case 6: generate coherence loss map from a co-located stack of pre- and post-event coherence assets derived from the same sensor

Find and access a Result from other on-demand services

Select the area for which you want to do an analysis e.g. over the Southern part of Turkey near the border with Syria. In this use case two Results from the SAR-COIN are used to assess the change in coherence that occurred after the 7.8-magnitude earthquake of 06/02/2023.

Access two successful SAR-COIN jobs in the Right Panel Processing Services under the Jobs tab by clicking on the Show results button. Same SAR-COIN processing results can also be listed in the left panel under theResults tab by clicking on My results or Shared results under the Results data context.

When selecting the pair of Results to be used for the Co-located Stacking drag ang drop the Results into the feature basket.

In this example the selected two SAR-COIN results derived from two pairs of Sentinel-1 SLC Datasets are:

1. Reference SAR-COIN Result (before earthquake): COIN S1A T14 17-29/01/2023 Turkey Earthquake

2. Secondary SAR-COIN Result (after earthquake): COIN S1A T14 29/01-10/02 2023 Turkey Earthquake

The first SAR-COIN Result is derived from the following SLC products (acquired both before the earthquake):

• Reference: S1A_IW_SLC__1SDV_20230117T033426_20230117T033454_046818_059D16_1A0C

• Secondary: S1A_IW_SLC__1SDV_20230129T033427_20230129T033455_046993_05A2FE_6FF2

The second SAR-COIN Result instead is derived from the following SLC interferometric pair (reference as the secondary of the first SAR-COIN result and secondary after the event):

• Reference: S1A_IW_SLC__1SDV_20230129T033427_20230129T033455_046993_05A2FE_6FF2

• Secondary: S1A_IW_SLC__1SDV_20230210T033426_20230210T033454_047168_05A8CD_FAA6

Job name

Insert as job name:

STACK - S1A Coherence loss 17-29/01-10/02 2023 Earthquake in Turkey

Input references

Drag and Drop in the "Input product reference(s)” field the first (COIN S1A T14 17-29/01/2023 Turkey Earthquake) and the second (COIN S1A T14 29/01-10/02 2023 Turkey Earthquake) Result obtained from on-demand processing with the SAR-COIN service.

Bands

Insert the list of single-band coherence assets from the given pair of SAR-COIN results in the "List(s) of comma separated band(s)” field. Inserted comma separated bands must follow the following convention:

reference_number.single_band_asset

The two selected coherence assets can be specified as input bands by inserting:

1.coh_c_vv_20230117_20230129,2.coh_c_vv_20230129_20230210

S-expression

The remaining optional parameter to be filled in is the one dedicated for generating new bands from the ones present in the image stack using s-expressions. In STACK a new band generated from the image stack is defined with a band name and it's associated s-expression separated by a colon : .

output_band_name:(s-expression)

The 2 new Assets to be generated are the coherence difference and the binary mask representing coherence loss derived from thresholding of coherence difference.

To compute them provide the following 2 s-expressions that are using the two input assets (coherence from each interferometric SLC pair). For instance coh_diff is the arithmetic difference of the two coherence assets (coherence2 - coherence1) and ccd as coherent change detection is a binarization of coherence difference (where (coh_diff >= threshold) set 1 else 0).

coh_diff:(- 2.coh_c_vv_20230129_20230210 1.coh_c_vv_20230117_20230129)

ccd:(where (>= (- 1.coh_c_vv_20230117_20230129 2.coh_c_vv_20230129_20230210) 0.4) 1 0)

coh_diff:(- 2.coh_c_vv_20230129_20230210 1.coh_c_vv_20230117_20230129)

ccd_n:(where (<= (- 1.coh_c_vv_20230117_20230129 2.coh_c_vv_20230129_20230210) 0.4) 1 0)

ccd_p:(where (>= (- 2.coh_c_vv_20230129_20230210 1.coh_c_vv_20230117_20230129) 0.4) 1 0)

Run the job

Click on the button Run Job and see the Running Job. You can monitor job progress through the progress bar.

Results: download and visualization

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

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

{
   "input_reference": [
      "https://catalog.disasterscharter.org//test_esa_marcorace/cat/1330ca4fa4e57223754f21910897444f96ec6bf2a87de77096fcb160a939d721/search?format=json&uid=1330ca4f-coherence_intensity",
      "https://catalog.disasterscharter.org//test_esa_marcorace/cat/8e1d8434cc422325f0c1457b9b1f9d0ce43a425fb69d75c771c7c2643113aba3/search?format=json&uid=8e1d8434-coherence_intensity"
   ],
   "bands": "1.coh_c_vv_20230117_20230129,2.coh_c_vv_20230129_20230210",
   "aoi": "POLYGON((36.381 37.305,36.381 38.419,37.969 38.419,37.969 37.305,36.381 37.305))",
   "s_expressions": [
      "coh_diff:(- 2.coh_c_vv_20230129_20230210 1.coh_c_vv_20230117_20230129)",
      "ccd:(where (>= (- 1.coh_c_vv_20230117_20230129 2.coh_c_vv_20230129_20230210) 0.4) 1 0)"
   ]
}

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 “Co-located stack from coherence_intensity, coherence_intensity” will appear and then click on the Show details button.

Red-Cyan coherence composite

In the left Result panel under Details is possible to create an overview on the fly from co-located assets by clicking on Layer Styling and Combine Assets. As an example under Combine Assets you can create on the fly Red-Cyan coherence band composite by setting 1.coh_c_vv_20230117_20230129 in the red channel, and 2.coh_c_vv_20230129_20230210 in the green and blue channels.

Coherence difference single band asset

The difference in coherence generated from the two co-located coh_c_vv_20230117_20230129 and coh_c_vv_20230129_20230210 assets with the first s-expression, can be seen in the map by clicking on Layer Styling and under Select Assets by selecting the coh_diff single band asset.

This coh_diff single band asset generated is displayed in the map using the Select Assets function and the coolwarm color map (negative coherence differences in shades of blue and positive differences in shades of red).

Coherence loss binary mask single band asset

The result from the binarization of negative coherence difference values (coh_dif < -0.4) obtained with the second s-expression, can be seen in the map by clicking on Layer Styling and under Select Assets by selecting the ccd single band asset.

This ccd single band asset is displayed in the map using the Select Assets function, the BlueRed color map (true values in red), No Data Value set as 0, and brightness filter set as 300%.

Download

In this fifth use case the Co-located stacking (STACK) service returned as output the following products:

• coh_c_vv_20230117_20230129: single band asset for the co-located coh_c_vv_20230117_20230129 asset from the 1st input Result,
• coh_c_vv_20230129_20230210: single band asset for the co-located coh_c_vv_20230129_20230210 coherence asset from the 2nd input Result,
• coh_diff single-band asset representing the difference of co-located coh_c_vv_20230117_20230129 and coh_c_vv_20230129_20230210 assets derived with the 1st inserted s-expression,
• ccd single-band asset a binary mask ok coherence loss from the difference of co-located coh_c_vv_20230117_20230129 and coh_c_vv_20230129_20230210 assets derived with the 2nd inserted s-expression.

All of them are given as single band GeoTIFF in COG format. These products can be downloaded by clicking on the Download button located at the bottom of the Product Details tab in the left panel.