24006 Geocomplexity Learning for Spatial Prediction

Project Title: Geocomplexity Learning for Spatial Prediction

Key Words: Geocomplexity ,Spatial Prediction

Research Topics: Geospatial Modelling

Mentor: Yongze Song, Curtin University, yongze.song@curtin.edu.au

Project Description:

This project aims at developing a geocomplexity learning approach for more accurate spatial prediction. The geocomplexity learning is an integration of local spatial complexity as explained in https://doi.org/10.1080/13658816.2023.2203212 and machine learning. The study will be published in a top journal.

Tasks and Responsibilities:

• Good English communication and writing skills
• Be familiar with spatial statistical approaches
• Will be evaluated through an assessment about theories and methods about spatial statistics and mathematical geosciences before joining the project.

Minimum qualifications:

• R/Python programming
• GIS
• Literature search

Term of the Project:

• May to Dec 2024

Deliverables:

• A set of visualizations (maps, charts) showcasing key insights.
• A comprehensive report detailing findings, interpretations, and recommendations.
• Documentation of the workflow, methodology, and tools used for reproducibility.
• Presentation of key findings and insights to the research team and stakeholders.