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Informatics and Computing
Description: This class will teach a range of ecological and environmental modelling techniques from simple back of the envelope quantitative techniques, to simple models, to more complex models, and spatial modelling. Specifically, in the first part, we will learn quantitative techniques from the book "Consider a spherical cow" and solve complex questions with back of the envelop techniques. Next, we will learn to create and test a simple mechanistic models with Matlab. In part three, we will run and modify complex mechanistic models such as the land model component of a Global Circulation Model (GCM) and the Madingley model, the first global model to incorporate both animal and plant ecology. Finally, we will learn spatial modelling using the Google Earth engine which combines a multi-petabyte catalog of satellite imagery and geospatial datasets with planetary-scale analysis capabilities. The class will serve as an introduction to all of these techniques. Overall, it will be a practical, results driven modelling class that will help graduate students learn new methods and techniques that can be applied to their dissertation research. Co-convened with INF 421. Letter grade only.
Units: 3
No sections currently offered.
Prerequisite: Graduate Status
Informatics and Computing
Term : Fall 2024
Catalog Year : 2024-2025
INF 521 - Mechanistic Ecological And Environmental Modeling
Description: This class will teach a range of ecological and environmental modelling techniques from simple back of the envelope quantitative techniques, to simple models, to more complex models, and spatial modelling. Specifically, in the first part, we will learn quantitative techniques from the book "Consider a spherical cow" and solve complex questions with back of the envelop techniques. Next, we will learn to create and test a simple mechanistic models with Matlab. In part three, we will run and modify complex mechanistic models such as the land model component of a Global Circulation Model (GCM) and the Madingley model, the first global model to incorporate both animal and plant ecology. Finally, we will learn spatial modelling using the Google Earth engine which combines a multi-petabyte catalog of satellite imagery and geospatial datasets with planetary-scale analysis capabilities. The class will serve as an introduction to all of these techniques. Overall, it will be a practical, results driven modelling class that will help graduate students learn new methods and techniques that can be applied to their dissertation research. Co-convened with INF 421. Letter grade only.
Units: 3
No sections currently offered.
Prerequisite: Graduate Status