Mapping and Predicting Tree Mortality using High-resolution Nanosatellite Data for Improved Forest Management

This project will enable forest monitoring at previously inaccessible scales by combining daily, high resolution satellite imagery with deep learning algorithms and extensive field observations. The innovation in this proposal is not in developing any one of the approaches; high resolution imagery has previously been used to map tree mortality, and deep learning has been used for object detection in high resolution remote sensing data. The innovation is in applying these approaches to noisy, high frequency, and high resolution satellite imagery to consistently and accurately detect fine-scale ecological patterns to monitor change over time. These analyses can be usedto inform land use planning and forest management. These tree mortality maps will improve the coordination of forest management activities through precisely identifying areas facing the greatest fire risk, optimizing timber harvest strategies, and forecasting future risks.