Data Science, Artificial Intelligence and Geographic Information Systems (GIS) for Environmental Sciences

Scope

This course aims to help the participant explore and understand the ease and benefit of combining the complex (spatial) data science and AI methods and techniques with the powerful capabilities of ArcGIS platform (Esri). This course explores state-of-the-art principles, methods, and techniques related to data science and artificial intelligence applications in relation to the Environmental Sciences’ major topics. We intend to train the participants in open science and towards integrated solutions of data science and Geographic Information Systems (GIS), using different types of spatial and non-spatial data relevant to solving environmental and societal problems. In this way, the participants can give a new dimension to their research by adding a spatial component to their data and being able to process, analyze, combine, and visualize the data in time and space.

Learning goals

The participants will explore potential links between their own research questions and GIS, using their own data or using sample data (remote sensing data or other image and spectra-based information). This training will familiarize the participants with using ArcGIS Pro and develop or integrate a project example or tool within ArcGIS Pro and/or ArcGIS Notebooks(A web-based interactive computing platform working on the Python Environment of the ArcGIS Platform, having the capabilities of integrating open science libraries and frameworks – other than the platform’s default).

Contents

The course starts with understanding the data. For example, we will deep dive into image processing, which entails working with multispectral image data, extracting spectral profiles, or raster functions (like band arithmetic, band composition etc.). Next, we will continue with machine learning (clustering, classification, and prediction) and deep learning (object detection, object tracking) involving different types of image data and/or video or camera feeds. To this end, we will use the ArcGIS Pro integrated geoprocessing tools. Furthermore, we will develop or/and integrate scientific algorithms directly on the ArcGIS platform using ArcGIS Notebooks.