VegClassify: A Hybrid Deep Learning–NDVI Greenspace Classification Tool and GUI

VegClassify is a hybrid, high-resolution greenspace classification tool integrating a fine-tuned deep learning model with automated NDVI threshold optimization. The tool improves accuracy and reduces subjectivity in vegetation classification using NAIP imagery. This graphical user interface (GUI) was developed to extend and simplify the use of the previously established greenspace image classification tool. The GUI provides an accessible, user‑friendly environment for running the VegClassify workflow without requiring users to interact directly with Python scripts or command‑line tools. It supports loading NAIP or other high‑resolution imagery, running deep‑learning–assisted NDVI threshold optimization, visualizing classification outputs, and exporting vegetation masks. The underlying Python codebase that implements the VegClassify hybrid deep learning–NDVI threshold method was originally published in: Wang, H., Zhao, X., Gholami, S., McGinty, C., Chamberlain, B., & Qi, X. (2026). A Hybrid Deep Learning and NDVI Threshold Approach for High-Resolution Urban Greenspace Classification. Urban Forestry & Urban Greening, 129332. This GUI serves as an application‑layer wrapper for that Python tool, enabling broader accessibility for research, planning, education, and applied landscape analysis.