Building Typology Analysis

This project uses Faster R-CNN (Region-based Convolutional Neural Network), a deep learning object detection model, to detect and classify buildings based on their visual and geometric characteristics in high-resolution satellite imagery. Trained on annotated satellite images, the model locates individual buildings and assigns them to predefined morphological categories, such as rectangular, L-shaped, H-shaped, and other common building forms. By automating this process, the project provides an efficient and scalable approach to extracting building-level morphological information directly from satellite imagery.