Potential use of Artificial Intelligence/Machine Learning in Combating/Studying Climate Change Impacts
Climate change is real. It has a profound effect on human life and must be addressed seriously before too late. It has been projected that the world will face catastrophic consequences within the next thirty years if climate change is not tackled properly.
Scientists are putting in a lot of effort to identify viable solutions for adapting to and mitigating climate change. Although not directly, Artificial Intelligence (AI)/Machine Learning (ML) can potentially help combat climate change by acting as a catalyst for other technologies fighting climate change. ML is a computer model that can be trained to perform different tasks based on the training. Although ML is one of the AI subsets, it can be implemented with or without AI. ML models with AI perform intelligently, more like a human. ML and AI-enabled tools can be used to combat climate change if implemented carefully.
Forests are the lung of our mother nature. Unfortunately, we are losing forests every second. In addition to the direct carbon loss (as biomass) from the forest ecosystem, it has been estimated that 15% of total greenhouse gas emissions are caused by deforestation. Greenhouse gas emissions should be minimized to fight climate change, and trees must be planted to mitigate damage caused by deforestation. Forest data should be captured and analyzed intelligently to make an appropriate tree plantation policy. Satellites are already there to capture data, but processing this enormous data is a big challenge, where AI/ML can be effectively used.
An ML model is very suitable for such a scenario, which can continuously intake data and process it. Existing data can be used to train the model, and the model can perform different tasks, alerting deforestation, unwanted activities etc. It can also calculate tree density, identify spots with fewer trees. This information will help policymakers to make more effective policies. Besides, if the model is intelligence-enabled, it can be more valuable and helpful. With AI, such a model can output different recommendations for policymakers. ML/AI is can also be used in species distribution models to determine the impacts of climate change on a single species. These tools also can predict different pathways of the forest carbon cycle under different climate warming scenarios.
While AI/ML techniques are beneficial for combating/studying climate change, their continued expansion is constrained by a shortage of adequate data and a somewhat higher threshold of applications. However, the combination of numerous algorithms and enhanced communication and collaboration between environmental scientists and AI/ML developers continue to pose significant challenges for future climate change research. There is no single tool to contain climate change; we should use all possible techniques and tools to fight it.
Md Abdul Halim