nf-core/rangeland

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Introduction

This document describes the output produced by the pipeline.

The directories listed below will be created in the results directory after the pipeline has finished. All paths are relative to the top-level results directory.

Pipeline overview

The pipeline is built using Nextflow and processes data using the following steps:

• untar - Optionally extract input files
• Preparation- Create a masks and boundaries for further analyses.
• Preprocessing - Preprocessing of satellite imagery.
• Higher-level-Processing - Classify preprocessed imagery and perform time series analyses.
• Visualization. Create two visualizations of the results.
• MultiQC - Aggregate report describing results and QC from the whole pipeline
• Pipeline information - Report metrics generated during the workflow execution

Untar

untar is a nf-core module used to extract files from tar archives.

Invokation of untar depends on certain parameters (i.e input_tar, dem_tar and wvdb_tar). Thus, the outputs files are only generated when these are set to true.

Preparation

In the preparation step, usable tiles and pixels per tile are identified.

force-tile-extent analyses the area of interest information and determines the tiles that can be used. These tiles are later used by other FORCE submodules.

force-cube computes the usable pixels for each FORCE tile. This computation is based on the specified are of interest and the resolution. The resulting binary masks can be used to understand which pixels were discarded (e.g. because they only contain water).

Preprocessing

Preprocessing consist of two parts, generating parameter files and actual preprocessing.

The parameter files created through force-parameter can be viewed to understand concrete preprocessing techniques applied for a given tile.

Logs and analysis-ready-data (ARD) are generated using the force-l2ps command. Logs can be consulted for debugging purposes. ARD may be collected as a basis for other remote sensing workflows. Moreover, ARD contains two .tif files per initial input image, a quality data file and the atmospherically corrected satellite data, that can be viewed using geographic information systems (GISs). Note that ARD data is only published as symbolic links due to the amount and size of the files.

Higher-level-Processing

Higher level processing consist of two parts, generating parameter files and performing various processing task as defined in the parameter files.

Parameter files may be consulted to derive information about the specific processing task performed for a given tile. In this workflow, classification using spectral unmixing is performed.

Spectral unmixing is a common technique to derive sub-pixel classification. Concretely, a set of endmember (provided using --endmember) is consulted to determine fractions of different types of vegetation, soil, $\ldots$ for each pixel.

Next, time series analysis for different vegetation characteristics is performed.

The resulting trend files can be consulted to view trends for individual tiles. They are saved as symlinks because of their large size.

If the return_tss parameter was set to true, the pipeline will also output files with the TSS ending. These files contain the time series stack(TSS) for the given tile and index or band. Here, for each date of acquisition, an image is available that contains the values for that date.

Visualization

Two types of common visualizations are generated in the last step of the pipeline. They are results of force-mosaic and force-pyramid. Note that these visualizations do not add more logic to the workflow but rather rearrange the output files of higher-level-processing. Both visualizations are enabled by default but may be disabled in a certain configuration files. Thus, these outputs are optional.

MultiQC

MultiQC is a visualization tool that generates a single HTML report summarising all samples in your project. Most of the pipeline QC results are visualised in the report and further statistics are available in the report data directory.

Results generated by MultiQC collate pipeline QC from supported tools e.g. FastQC. The pipeline has special steps which also allow the software versions to be reported in the MultiQC output for future traceability. For more information about how to use MultiQC reports, see http://multiqc.info.

Pipeline information

Nextflow provides excellent functionality for generating various reports relevant to the running and execution of the pipeline. This will allow you to troubleshoot errors with the running of the pipeline, and also provide you with other information such as launch commands, run times and resource usage.