STACK tutorial

This service provides a multi-mission and multi-temporal image stack of co-located single-band assets coming from different optical and SAR sensors against a reference asset. It performs resampling and warping of the 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 case 1: evaluate changes in spectral indexes from a co-located stack of pre- and post-event images from the same sensor

Abstract

This first use case explains how to create a stack of co-located images and derive from it pre- and post-event NDVI (Rouse et al., 1973)¹ and NDWI (Mc Feeters, 1996)² spectral indexes for a prelimianry impact assessment of a flood event.

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. The first input can be the Pleaides-1B [CD] acquired on 30/09/2021, the second one can be the Pleaides-1A [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:

[CD] PLEIADES-1B PHR-1B ORTHO/BASIC 2021/09/30 04:07:39,
[CD] PLEIADES-1A PHR-1A ORTHO/BASIC 2021/10/01 03:59:28.

Warning

Drag and drop the Dataset (e.g. "[CD] PLEIADES-1B PHR-1B ORTHO/BASIC 2021/09/30 04:07:39") and not the single-band asset (e.g. "red") into the Input product reference(s) field.

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 omma 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

Warning

Use comma-separated reference.bands and avoid spaces between assets.

Note

All CBNs available in the ESA Charter Mapper can be found here.

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.

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 which is taken from the current search area in WKT format.

Note

This parameter is optional.

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)

Warning

S-expressions inserted by the user must be given within brackets.

Note

This parameter is optional.

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.

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.

{
   "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.

Warning

STACK does not currently provide a visual product (overview). Thus, the preview in the map is made by default with a RGB composite taking the first 3 single-band assets generated as product by the service.

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 composites highlights NDWI changes derived from Pleiades-1 data. In cyan is shown the water receding after the peak of the flood event.

Warning

When combining geophysical single-band assets under Combine assets please consider the valid range associated with the specific asset. As an example consider [-1,1] for a spectral index from a normalized difference, [0,10000] for TOA reflectances, etc. Valid ranges for all geophysical single-band products can be found here. Min and Max values shall be inserted manually in the Channel histogram min/max boxes.

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

Abstract

This first use case explains how to create a stack of co-located images and derive from it pre- and post-event NDVI (Rouse et al., 1973)¹ spectral indexes for a preliminary delineation of a landslide.

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. The first input can be the Worldview-2 [CD] acquired on 24/05/2020, the second one can be the Pleaides-1A [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:

[CD] WORLDVIEW-2 MSI LV1B 2020-05-24 02:02:22,
[CD] PLEIADES-1A PHR-1A ORTHO/BASIC 2022-04-17 01:58:50.

Warning

Drag and drop the Dataset (e.g. "[CD] WORLDVIEW-2 MSI LV1B 2020-05-24 02:02:22") and not the single-band asset (e.g. "red") into the Input product reference(s) field.

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 omma 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

Warning

Use comma-separated reference.bands and avoid spaces between assets.

Note

All CBNs available in the ESA Charter Mapper can be found here.

Tip

Always check the list of CBNs available in a Calibrated Dataset before defining list of single-band geophysical assets. A Worldview-2 CD does not have a nir asset but a nir08 one.

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.

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 which is taken from the current search area in WKT format.

Note

This parameter is optional.

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)

Warning

S-expressions inserted by the user must be given within brackets.

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.

Results: download and visualization

Once the job is completed, click on the button Show results 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.

{
   "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.

Warning

STACK does not currently provide a visual product (overview). Thus, the preview in the map is made by default with a RGB composite taking the first 3 single-band assets generated as product by the service.

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

Warning

When combining geophysical single-band assets under Combine assets please consider the valid range associated with the specific asset. As an example consider [-1,1] for a spectral index from a normalized difference, [0,10000] for TOA reflectances, etc. Valid ranges for all geophysical single-band products can be found here. Min and Max values shall be inserted manually in the Channel histogram min/max boxes.

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

Abstract

This third use case explains how to create a a multi-temporal co-located stack of TOA Reflectance Assets from the same sensor and perform multi-temporal analysis using the delta Normalized Burn Ratio (Miller and Thode, 2014)³ dNBR index.

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. Input calibrated datasets can be: 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:

[CD] SENTINEL-2A MSI L2A 113 2021/07/13 18:49:19,
[CD] SENTINEL-2A MSI L2A 113 2021/07/18 18:49:19,
[CD] SENTINEL-2B MSI L2A 113 2021/07/23 18:49:19,
[CD] SENTINEL-2A MSI L2A 113 2021/07/28 18:49:19,
[CD] SENTINEL-2B MSI L2A 113 2021/08/02 18:49:19,
[CD] SENTINEL-2B MSI L2A 113 2021/09/01 18:49:19.

Warning

Drag and drop the Dataset (e.g. "[CD] SENTINEL-2B MSI L2A 113 2021/09/01 18:49:19") and not the single-band asset (e.g. "nir") into the Input product reference(s) field.

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 omma 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

Warning

Use comma-separated reference.bands and avoid spaces between assets.

Note

All CBNs available in the ESA Charter Mapper can be found here.

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.

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 which is taken from the current search area in WKT format.

Note

This parameter is optional.

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))

Warning

S-expressions inserted by the user must be given within brackets.

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.

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.

Warning

STACK does not currently provide a visual product (overview). Thus, the preview in the map is made by default with a RGB composite taking the first 3 single-band assets generated as product by the service.

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.

Warning

When combining geophysical single-band assets under Combine assets please consider the valid range associated with the specific asset. As an example consider [-1,1] for a spectral index from a normalized difference, [0,10000] for TOA reflectances, etc. Valid ranges for all geophysical single-band products can be found here. Min and Max values shall be inserted manually in the Channel histogram min/max boxes.

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

Abstract

This fourth use case explains how to create a stack of co-located Sigma Nought Assets and and perform multi-temporal analysis using average backscatter and multi-temporal differences from average.

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. Input calibrated datasets can be: Sentinel-1A L2A [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:

[CD] SENTINEL-1A GRD IW VV/VH 108 2022-02-09 03:00:31,
[CD] SENTINEL-1A GRD IW VV/VH 108 2022-01-28 03:00:31,
[CD] SENTINEL-1A GRD IW VV/VH 108 2022-01-16 03:00:32.

Warning

Drag and drop the Dataset (e.g. "[CD] SENTINEL-1A GRD IW VV/VH 108 2022-02-09 03:00:31") and not the single-band asset (e.g. "s0_db_c_vv") into the Input product reference(s) field.

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 omma 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

Warning

Use comma-separated reference.bands and avoid spaces between assets.

Note

SAR CBNs for radar backscatter used in the ESA Charter Mapper can be found here.

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.

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 which is taken from the current search area in WKT format.

Note

This parameter is optional.

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 new bands as average backscatter and a multitemporal differences from the average backscatter the three input calibrated datasets, insert the following s-expressions to generate four new bands in the image stack using the three input Sigma Nought co-pol assets:

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))

Warning

S-expressions inserted by the user must be given within brackets.

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.

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.

Warning

STACK does not currently provide a visual product (overview). Thus, the preview in the map is made by default with a RGB composite taking the first three single-band assets generated as product by the service.

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.

Warning

When combining geophysical single-band assets under Combine assets please consider the valid range associated with the specific asset. As an example consider [-1,1] for a spectral index from a normalized difference, [0,10000] for TOA reflectances, etc. Valid ranges for all geophysical single-band products can be found here. Min and Max values shall be inserted manually in the Channel histogram min/max boxes.

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. This 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).

Example

Create the same RGB composite on the fly mainintaing the same Min and Max values for RGB channels by simply swithing from diff_from_average1 to or diff_from_average3 under the Green and Blue channels.

Scene 1: Sentinel-1A IW VV 2022-01-16 03:00:31

Image-note-01

Scene 2: Sentinel-1A IW VV 2022-01-28 03:00:31

Image-note-02

Scene 3: Sentinel-1A IW VV 2022-02-09 03:00:32

Image-note-03

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.

Rouse J., Haas R. H., Schell J. A., Deering D. (1973), “Monitoring vegetation systems in the great plains with ERTS”, NASA. Goddard Space Flight Center 3d ERTS-1 Symp., Vol. 1, Sect. A. Available at: ntrs.nasa.gov ↩↩
McFeeters S. K. (1996), “The use of the Normalized Difference Water Index (NDWI) in the delineation of open water features”, International Journal of Remote Sensing, 17:7, 1425-1432, DOI: 10.1080/01431169608948714. ↩
Miller J. and Thode A. (2007), “Quantifying burn severity in a heterogeneous landscape with a relative version of the delta Normalized Burn Ratio (RdNBR)”, Remote Sensing of Environment, 109, 66-80. DOI: 10.1016/j.rse.2006.12.006. ↩