deepcanopy

DeepCanopy is a software framework designed for large-scale analysis of ecological data, particularly focusing on forest structure and dynamics. Developed with the intention of processing remote sensing data, it enables researchers to extract detailed information about forest canopies, such as tree height, biomass, and species composition, from sources like LiDAR and high-resolution imagery. The framework is built to handle the computational demands of analyzing vast datasets, often covering extensive geographical areas.

The core of DeepCanopy lies in its ability to integrate various data sources and employ machine learning techniques. This allows for the automated identification and measurement of individual trees or canopy strata. Its modular design facilitates the incorporation of different algorithms and models, making it adaptable to diverse ecological research questions and data types. The primary goal of DeepCanopy is to provide a scalable and efficient platform for ecological monitoring and research, contributing to a better understanding of forest ecosystems and their response to environmental changes.