tree-species-classification

Implementation code of the paper "MS-DGCNN++: Multi-Scale Dynamic Graph Convolution with Scale-Dependent Normalization for Robust LiDAR Tree Species Classification"

Transformers and LSTM for Tree Species Classification from Satellite Image Time Series

Morphometrics of buds of common forest species

Tree Species Segmentation in High-Resolution Aerial Imagery

My code for my master thesis - includes a automatic pipeline to evaluate the clustering capabilities of single tree crown images.

Quality-control and automation tools for geospatial AI workflows in utility vegetation management: model-output QC, imagery preparation and spatial network operations. Standalone Python, tested, with runnable demos. Satellite, aerial and drone imagery; vector and raster.

This project is done in view of 4-weeks Shell-Edunet Skills4Future Internship. For Week - 2 By~ Samuel Lazar

AI-based allergenic tree species detection and classification in urban environments using aerial imagery and LiDAR data.

Open-source geospatial automation tools: imagery cleanup, vegetation extraction, spatial snapping, delivery-time estimation, shapefile delta QC, dataset splitting, geometry repair, tile prioritization, and drift detection — each with a standalone mode and a verified demo.