Data-driven informed decision-making for climate change mitigation: an evaluation
Authors
Joseph, Pratish
Issue Date
2024
Degree
Master of Science (MSc) Information Systems with Computing
Publisher
Dublin Business School
Rights holder
Rights
Abstract
Climate change is a complex challenge that requires informed decision-making. This applied research explores data-driven approaches to address this challenge.
The methodology involves sourcing climate datasets for India from the IMF’s online repository, a credible source. It performs descriptive and predictive analyses with Python. It explores forecasting techniques and eventually evaluates one for the specific dataset.
This study derives insights using correlation matrices and climate variable plots. It uses ARIMA modelling for forecasting, whose parameters are determined by recommended approaches.
The results are summarised, followed by interpretations of the data patterns, assessments of efforts to mitigate climate crisis, and evaluations of ARIMA statistics applied in this context.
The ARIMA model is evaluated using a combination of automated statistics and visualisation of its results.
Ultimately, this study advocates for a proactive, fact-based approach to addressing the climate crisis, using data as a powerful tool for informed decision-making and effective action.