Selected consultancy references

I have worked with clients on an international level. These include companies, universities, and research organisations.

Find below a selection of my consultancy references:

Migrating the Copernicus Global Land Service to cloud

Consultancy on migrating the Copernicus Global Land Service to a cloud environment

Role: Consultant

Period: 06/2020 – 10/2020

Customer: European Commission/JRC

Project scope:
This consultancy service provided a detailed roadmap for the migration of the Copernicus Global Land Service, a key component of the EU’s flagship Earth Observation program, to a cloud-based environment.
The Copernicus program, known for providing a wide range of user-oriented products for monitoring the environment, climate and anthropogenic impacts on the Earth, was facing major challenges due to the increase in data and product volumes over the last decade. The service needed to move from product-specific and unharmonized processing chains to a more integrated, harmonized and efficient cloud architecture. The aim was to improve the use of Earth observation data and transform it into actionable knowledge to manage complex global change.
A transition to a cloud infrastructure is a technological challenge, but promises significant improvements. It required disassembling numerous production chains into modular components and reassembling them into a coherent system. The proposed service focuses on ensuring a seamless and integrated user experience and evaluates the tangible benefits and effort of this cloudification process for Copernicus’ global terrestrial production lines and user interfaces.

Result: Abernathey, R., Neteler, M., Amici, A., Jacob, A., Cherlet, M., Strobl, P. (2021): Opening new horizons: How to migrate the Copernicus Global Land Service to a Cloud environment. EUR 30554 EN, Publications Office of the European Union, Luxembourg, 2021, ISBN 978-92-76-28406-2 (online), doi:10.2760/668980, JRC122454.

Related topics: Cloud infrastructures, big data

Location: Brussels (remote)

Compilation scripts for GRASS GIS and QGIS on CentOS

Creation of compilation scripts for the installation of GRASS GIS and QGIS on a Linux VM (CentOS)

Role: Software developer

Period: 09/2015 – 09/2015

Customer: Private business from UK

Project scope:
This consulting service provided a comprehensive solution for the installation of GRASS GIS and QGIS on a Linux VM (CentOS) in a new server environment. The service mainly focused on the preparation and execution of compilation scripts using the RPM Package Manager, a standard software package management system used by various Linux distributions such as CentOS, Fedora and others. The main tasks included preparing the compilation environment, installing important libraries such as PROJ and GEOS, and compiling important components such as GeoTIFF and GDAL from Fedora SRPMs. This process included installing a newly generated GeoTIFF RPM and modifying the SPEC file for GDAL compilation to ensure compatibility with the new GeoTIFF library. In addition, the latest versions of GRASS GIS and QGIS were downloaded from the respective online code repositories and compiled to provide a stable and up-to-date GIS installation on the CentOS-based server.

Result: RPM spec files, see blog post

Related topics: GRASS GIS, CentOS, RPM spec files

Location: United Kingdom (remote)

Optimization of groundwater flood risk mapping

Consulting services for the optimization of groundwater flood risk mapping

Role: Consultant

Period: 06/2014 – 06/2015

Customer: Private business from UK

Project scope:

This consultancy project provided our client with specific support to improve their groundwater flood risk mapping software, which was to be developed on a detailed 5-meter grid. Our consultancy services were delivered over a set number of hours and focused on several key areas:

  • Advice on optimizing the Python/GRASS GIS code:
    • Our consultation included expert advice on Python and GRASS GIS code optimization. It is important to note that the actual code optimization was not part of this project, while we provided consulting.
  • Advice on computing power and hardware investments:
    • We advised the client on the computational effort and hardware investment required to achieve the goal of developing an improved flood risk mapping system. This included assessing current capabilities and recommending any necessary upgrades or modifications.
  • Improving model efficiency:
    • As the client’s numerical model had increased significantly in size (by a factor of 100 due to higher spatial resolution), we provided advice on how to make the model run faster and more efficiently. This included both hardware and software optimizations, with a focus on code efficiency.
  • Analysis of the model structure:
    • Using the model flow diagram provided, which detailed the input and output layers and the GRASS GIS modules used, we analyzed how the model could be optimized on the new, higher-resolution grid.
  • Feasibility of model segmentation:
    • We investigated the feasibility of segmenting the model into smaller, more manageable units (e.g. by watershed) to improve efficiency and manageability.
  • Pilot analysis of the high-resolution grid:
    • An evaluation was carried out to estimate the runtime and resource requirements for the high-resolution grid in the pilot area and thus gain important insights for implementation on a large scale.


  • As part of this consultancy project, we provided our client with the knowledge and strategies required to successfully update and manage their groundwater flood risk map and ensure that it was both efficient and effective in its new, more detailed format.

Result: reports

Related topics: Python, Bash, C-language, Parallel Processing, Hardware-Architecture

Location: United Kingdom (remote)

Solar energy potential on roofs in Alpine terrain

Consulting services for the optimization of groundwater flood risk mapping

Role: Geospatial Analyst

Period: 11/2013 – 12/2013

Customer: Private business from Italy

Project scope:
The solar energy potential on roofs in alpine terrain is reduced by surrounding mountains, buildings and clouds. The complexity of the terrain requires an accurate calculation of shadow conditions and cloud cover throughout the year.

This short-term consultancy focused on data analysis and mapping of cloud data over an area in northern Italy (southern Dolomites). After product selection and evaluation, the identified cloud cover data products from MODIS satellite sensor data, CM SAF datasets and Cloudsat were pre-processed and imported into a GIS database. The time series were then divided into weekly and monthly data products.

For the weekly data product, approximately 2920 daily data layers from November 2004 to November 2013 were processed. This includes pre-processing, reprojection to LatLong/UTM and aggregation to weekly averages. The result was 52 GeoTIFF maps with cloud percentages for Italy in UTM32 format, which were delivered to the customer.

The monthly data product involved the processing of approximately 320 monthly data layers from 1982 to 2009 with similar pre-processing and aggregation to 12 monthly averages. The result is 12 GeoTIFF cloud percentage maps for Italy delivered to the client.

The consultancy effectively delivered detailed geodata products over different time periods.

Result: GeoTIFF files

Related topics: GRASS GIS, QGIS, GDAL, Geospatial Analysis, Scripting

Location: Italy