07-20, 10:00–11:30 (Poland), Room CA4
During the workshop, we will present the Copernicus Data Space Ecosystem, a European project for sharing, storing, and computing EO data from the Copernicus program. Participants will learn about the basic functions of the Ecosystem, which includes several components such as Copernicus Browse, for easy visualization and analysis of imagery data from various Sentinel missions, and Sentinel Hub’s QGIS plugin, for convenient creation and display of EO imagery compositions in QGIS software. These tools provide users with access to worldwide historical and current imagery data without requiring specific technical knowledge. Additionally, participants will be introduced to cloud computing in the CDSE using Jupyter Labs. We will present two use cases utilizing OpenEO, a library that allows for easy access to and processing of Copernicus program data. Each use case will demonstrate the power of cloud computing and the easy access to Sentinel-2 data.
During the workshop, we will present the Copernicus Data Space Ecosystem, a European project for sharing, storing, and computing EO data from the Copernicus program. Participants will learn about the basic functions of the Ecosystem, which includes several components such as Copernicus Browse, for easy visualization and analysis of imagery data from various Sentinel missions, and Sentinel Hub’s QGIS plugin, for convenient creation and display of EO imagery compositions in QGIS software. These tools provide users with access to worldwide historical and current imagery data without requiring specific technical knowledge. Additionally, participants will be introduced to cloud computing in the CDSE using Jupyter Labs. We will present two use cases utilizing OpenEO, a library that allows for easy access to and processing of Copernicus program data. Each use case will demonstrate the power of cloud computing and the easy access to Sentinel-2 data.
🧠As a trained surveyor, I have honed my skills in data analysis and interpretation, which I have leveraged in my transition towards becoming a Junior Data Scientist. Over the last two years, I have been exploring the realm of GIS, remote sensing, LiDAR, and data processing, which have become my primary areas of interest. My vision of the spatial data industry is that of a puzzle with open datasets, Python, SQL, and Machine Learning techniques being the pieces that need to fit together. In my opinion, the future of GIS lies in Big Data solutions and cloud computing, and I am fortunate to be developing my skills in this direction while working at CloudFerro.
🌎I am familiar with:
👉🏻 Python programming - Numpy, PyQt, ArcPy libraries, GeoPandas, SciPy
👉🏻 PostgreSQL, Postgis
👉🏻 QGIS and ArcGIS
👉🏻Remote Sensing, EO
👉🏻 Extensive processing and interpretation of spatial data
😸Privately I am interested in drawing, cats, dogs and alternative rock.
Junior Data Scientist at CloudFerro and Geoinformatic's student at Warsaw University of Technology. Mainly focused on developing solutions for sharing big spatial data via open-source technologies.