Jinhui Li: WIDEFIRE RISK ANALYSIS FOR NEW ZEALAND WITH ARTIFICIAL INTELLIGENCE

<p dir="ltr">This study focuses on applying artificial intelligence (AI) techniques to enhance wildfire risk analysis in New Zealand. Given the country’s unique ecosystems, increasing temperatures, and changing land-use patterns, the frequency and intensity of wildfires have been rising. Traditional risk assessment models often struggle to capture the complex spatial–temporal interactions among climate, vegetation, and human factors. By integrating satellite remote sensing, meteorological data, and machine learning models, this research aims to predict high-risk areas and identify early indicators of ignition. Advanced deep learning architectures—such as convolutional and transformer-based networks—will be used to analyze multi-source data cubes and improve prediction accuracy. The outcome will contribute to more effective fire management strategies, early warning systems, and environmental resilience in New Zealand’s vulnerable regions, supporting sustainable land management and national disaster preparedness. </p>