Felipe Carlos Email and Phone Number

The GEO Knowledge Hub is an open-source digital library for Earth Observations applications. I work on the GEO Knowledge Hub team as the developer of the digital library, being responsible for:1. Application architecture2. Operation of the digital library3. Infrastructure managementThe development of the GEO Knowledge Hub is based on InvenioRDM. Thus, all functionalities are created using Python and React technologies.

I worked on the development of data processing and analysis tools, including:1. rwlts: R client for the Land Trajectory Service Web service;2. rlccs: R Client for Land Cover Classification System Web Service;3. wlts.py: Python client for the Land Trajectory Service web service.Concerning infrastructure, I managed the JupyterHub instance of the Brazil Data Cube project. I also managed the public Docker images of the project tools. I assisted in managing the cluster of machines using Proxmox. Also, I was in charge of managing the project's GeoServer and Geonetwork instances.In addition to these activities, I also developed reproducible articles with project colleagues. Also, I gave mini-course presentations, teaching students how to use the BDC project tools.

Brazil Data Cube (BDC) is the Brazilian data cube initiative created by INPE researchers and collaborators. The BDC produces data cubes for the entire national territory with data from satellites like Sentinel-2/MSI, Landsat-8/OLI, and CBERS-4/MUX, among others.At BDC, I worked on integrating the BDC Platform with Open Data Cube (ODC) technology. The integration was done by customizing the ODC modules for the Brazil Data Cube. The integration was made using Python. At the end of the integration, the ODC functionalities were available in the BDC ecosystem.In addition, I also worked on configuring and managing the infrastructure used in the integration stages, which included managing clusters of Linux machines and technologies such as Docker, Nginx, and several others.Also, I worked on creating the monitoring system for the machine park of the BDC project. For this, I made use of Prometheus and Grafana.

I developed tools for processing and analyzing water quality data, including in-situ and remote sensing data (Sentinel-2/MSI, Landsat-8/OLI). The tools helped the operations of the Aquatic Systems Instrumentation Laboratory (LabISA). To create the tools, I used Python and Matlab programming languages.Among the tools developed are:1. AtmosPy: Python library for radiometric correction of Sentinel-2/MSI and Landsat-8/OLI images based on the 6SV model;2. Uranus: Python library for generating analysis-ready time series data (radiometric correction, spatial and temporal correction);3. dgipy: Python library for automating the acquisition of CBERS-4 images.In addition to these packages, other tools for specific use in master's and doctoral work were created, which include:1. Tools for generating chl-a maps based on Sentinel-2/MSI time series;2. Spectral classification tools;3. Visualization tools for spatial, spectral, and hyperspectral data.All tools were documented and versioned in LabISA's GitLab.

As an Infrastructure Analyst intern, I performed several activities regarding network management, data security, user support, and computer maintenance.Regarding network management, I worked with the configuration and management of Linux (Debian), OpenBSD, and Windows Server (2008, 2012, 2016) servers. I managed and configured equipment such as Dell SonicWall, Mikrotik, and pfSense Appliances for network security. Regarding data security, I was responsible for routine backups of several servers. For this, it used software such as S.O.S Backup and Symantec Backup.Concerning user support, I made remote and on-site assistance to solve software and hardware issues. When required, I also performed hardware maintenance.Finally, at certain times during the internship, I had the opportunity to work with the configuration and management of the GLPI tool.

Assistance in the maintenance of industrial machines.