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Example LivePublication -- dynamic narratives that reflect experimental states

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Computational Workflow

Parameters

Description	Type

BANDS

Description	Type
A list of spectral band raster files (e.g., B03, B08) for the index calculation.	File

COLOR

Description	Type
The name of the matplotlib-compatible color map for the output TIFF.	Text

INDEX

Description	Type
The name of the vegetation index to compute (e.g., NDVI, GNDVI)	Text

ALL_OUTPUTS

Description	Type
All intermediate and final pickle outputs from the index computation.	File

TIFF

Description	Type
The final TIFF image output with the vegetation index and color map applied.	File

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Steps

Step

This step, , uses the tool .

It was executed from to , using the container image .

Inputs

Name	Reference

Outputs

Name	Reference

Step Index Definition Tool

This step, Run of workflow/packed.cwl#main/index_def , uses the tool Index Definition Tool .

This CWL tool computes a vegetation index matrix from provided spectral bands. It dynamically loads an index definition script (index_def.py) which uses auxiliary functions from file_handling.py.

It was executed from 2025-07-16 09:36:48 to 2025-07-16 09:37:28 , using the container image gusellerm/veg-index-container .

Inputs

Name	Reference

Name	Reference
bands	packed.cwl#index_def.cwl/bands

Name	Reference
index	packed.cwl#index_def.cwl/index

Name	Reference
#30058ce4-c4a0-470d-97cb-aed2e52b2a0f	packed.cwl#index_def.cwl/index_def

Outputs

Name	Reference

Name	Reference
9760aa6cd4cca907a093c9bf748ea4e8a49603bc	packed.cwl#index_def.cwl/index_matrix, packed.cwl#tiff_gen.cwl/index_array

Name	Reference
all_outputs	packed.cwl#index_def.cwl/all_outputs

Step Vegetation Index TIFF Generator

This step, Run of workflow/packed.cwl#main/tiff_gen , uses the tool Vegetation Index TIFF Generator .

This CWL tool converts a vegetation index matrix (in pickle format) into a color-mapped GeoTIFF file. It dynamically loads a TIFF generation script (tiff_gen.py) which depends on auxiliary functions from file_handling.py.

It was executed from 2025-07-16 09:37:29 to 2025-07-16 09:37:57 , using the container image gusellerm/veg-index-container .

Inputs

Name	Reference

Name	Reference
9760aa6cd4cca907a093c9bf748ea4e8a49603bc	packed.cwl#index_def.cwl/index_matrix, packed.cwl#tiff_gen.cwl/index_array

Name	Reference
color	packed.cwl#tiff_gen.cwl/color

Name	Reference
#51fd6288-cdaa-48ed-9d0b-d63049ed7fdd	packed.cwl#tiff_gen.cwl/tiff_gen

Outputs

Name	Reference

Name	Reference
677d2abe3b9e8cc09e3dc2c3eef43676aea129d1	packed.cwl#main/tiff, packed.cwl#tiff_gen.cwl/tiff

Sentinel-2A Data Product Overview

This publication uses a Sentinel-2A Level-2A product acquired during orbit 93 on 2015-07-29 09:20:06 . The dataset, identified by this DOI , was processed using baseline 05.00 (see here for information on baseline processing algorithms) on 2023-10-11 23:48:04 .

Data Alerts

The Sentinel-2A scene was assessed for conditions that may impact analysis reliability. There are currently 1 active data quality flags:

A significant portion of the scene contains no data ( %), which may limit the reliability of GNDVI calculations.

A large proportion of the land surface is cloud-covered ( %), which may significantly distort GNDVI signals.

Thin cirrus clouds are present ( %), potentially elevating NIR values and distorting vegetation estimates.

Cloud shadows affect part of the scene ( %), possibly reducing GNDVI by lowering NIR reflectance.

Saturation has been detected in % of pixels, indicating possible data corruption in bright areas.

Vegetation coverage is low ( %), which can make GNDVI more sensitive to atmospheric noise or edge effects.

A significant portion of the scene contains no data ( 80.64 %), which may limit the reliability of GNDVI calculations.