Urban Trees - Ribeirao Preto

The Urban Trees – Ribeirão Preto dataset is a carefully curated collection of high-resolution, manually annotated images, focusing on tree canopies in urban areas of Ribeirão Preto, Brazil. Designed for semantic segmentation tasks, it provides valuable data for environmental monitoring, urban forestry, and climate resilience research.

Key Features

• High-Resolution Imagery: The dataset includes images with detailed tree canopy structures, ensuring high accuracy for machine learning models.

• Manual Annotations: Every image is annotated to mark tree canopies and vegetation areas, which helps in precise segmentation. The dataset covers a wide range of urban settings, from green parks to sparsely vegetated residential areas.

• Urban Context: The dataset represents a mix of vegetation types and urban landscapes. It reflects various urbanization levels, making it ideal for training models that understand how trees integrate into cities.

• Semantic Segmentation Focus: This dataset supports semantic segmentation, helping models identify and classify tree canopies in urban environments. It’s perfect for environmental and urban planning applications.

Applications

• Urban Green Space Analysis: Use this dataset to analyze green spaces in cities, supporting urban planning and sustainable development.

• Environmental Monitoring: Build models to track urban vegetation health and assess how urbanization impacts ecosystems.

• Climate Resilience: Study tree canopy coverage to improve urban climate resilience. It can help mitigate urban heat islands and improve air quality.

• Urban Forestry: Develop models for managing urban forests, optimizing tree planting strategies, and maintaining healthy green spaces.