ABCD-GIS / Geography Colloquium - Integrating cloud computing with the KNIME platform for monitoring deforestation
Date and Time
Location
Abstract
The burgeoning volume of Earth observation data necessitates robust and scalable computational platforms. Google Earth Engine (GEE) , a cloud-based platform, addresses this need by offering a multi-petabyte catalog of satellite imagery and geospatial datasets. It facilitates planetary-scale analysis capabilities, enabling users to explore data visualization and undertake extensive analyses using diverse algorithms and models. The integration of Google Earth Engine with KNIME, a free and open-source data analytics platform, extends these capabilities to desktop-based workflows. KNIME supports a low-code experience, allowing users to construct analytical tools and integrate workflows for applications in geospatial analysis and remote sensing.
This seminar will explore the utilization of Google Earth Engine for data processing and analysis, emphasizing the synergy with KNIME workflows to enhance the node coding experience as well as local machine-based analysis. The session will focus on a case study of deforestation monitoring, showcasing how these integrated technologies can be leveraged to address complex environmental challenges.
Presentation Agenda
12:00 – 12:25 Bandit Mienmany Introduction to an overview of Google Earth Engine for geospatial datasets, remote sensing analysis, and a case study of deforestation monitoring.
12:25 – 12:50 Xiaokang Fu Introduction to KNIME platform and how to use KNIME to do reproducible geospatial analysis especially with KNIME Google Earth Engine extension without coding.
12:50 – 1:15 Zhan Zhang presentation of the KNIME workflow for processing remote sensing images and applying land use/land cover classification techniques.
1:15 – 1:30 Bandit Mienmany Wrap-up on analysis, limitations, and future plans and open discussion.
Presentation video available upon request.
