This repository is created for the class called Remote Sensing of Land Surfaces at Utah State University. The supervisor for this class is Dr. Alfonso Torres-Rua.

The materials for this repository come from research in Dr. Torres's group: LAI estimation across California vineyards using sUAS multi-seasonal multi-spectral, thermal, and elevation information and machine learning, which is appending to publish in a journal paper. If you are interested in this topic, please reach out to the resources online.

• "Demo_LAI_AggieAir.xlsx": pre-processed data from the AggieAir platform (a type of small unmanned aerial system).
• "PSC-CEE6003_RF-LAI.ipynb": random forest model for LAI estimation based on the provided dataset.
• "PSC-CEE6003_XGB-LAI.ipynb": XGBoost model for LAI estimation based on the provided dataset.
• "gfit.py": a model-evaluation model written by Rui Gao for his research. This one is used to get the metrics, such as RMSE to evaluate the machine learning model performance. Details can reach out to here