---
title: "Digital Tree Passport Annotation for Forest Mapping"
description: "How do you annotate 200,000 trees with species, height, and crown data from aerial imagery to enable precise forest monitoring?"
url: "https://unidata.pro/cases/digital-tree-passport-annotation-for-forest-mapping/"
date_modified: "2026-02-11T11:00:01+03:00"
language: "en-US"
---
Task
----

The client needed annotated data to train and validate models for automated tree detection and species recognition based on aerial photos. Each tree had to be identified with coordinates, height, crown shape, and species class. The task involved handling a large volume of objects with subtle visual distinctions and structuring data for digital “tree passports.”

Key challenges included:

- Filtering out objects shorter than 2.5 meters to avoid misclassification
- Managing tens of thousands of individual trees with diverse canopy shapes and colors
- Accurately matching tree species based on visual crown characteristics requiring manual expert annotation

Solution
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### Preparation and guidelines

- Developed annotation guidelines defining species-specific crown shapes, color patterns, and height thresholds
- Combined automated HD-Forest recognition with manual validation for a balanced approach
- Created a standardized format for “Digital Tree Passports” including geolocation, species, height, and canopy data

### Annotation process

- Automated detection and initial classification of trees using aerial imagery processing software
- Manual review and correction of ambiguous cases and species assignments based on visual traits
- Structured metadata tagging for height, vertical layering, and canopy complexity

### Quality control

- Performed selective validation checks on random samples for species and parameter accuracy
- Provided annotators with regular feedback based on error analysis and consistency reviews
- Ensured dataset quality met standards for forestry monitoring applications and model training

The Result
----------

- Accurately annotated 200.000 trees across 10 species classes
- Created detailed digital passports for each tree, supporting scalable forest monitoring
- Established a robust dataset enabling improved species recognition and ecosystem management

## Hero

**Industry and Use Case:** Forestry Monitoring & GIS **Data:** 200,000 trees, 10 species classes **Project Duration:** 2 months

## Main Title

Digital Tree Passport Annotation for Forest Mapping

## Description

We developed a scalable annotation pipeline to automate tree identification and species classification from aerial imagery, enabling precise forest monitoring and management. For an environmental monitoring client, we annotated over 128,000 individual trees, combining automated detection with manual validation to create detailed digital passports for each tree. This project laid the foundation for advanced forestry GIS applications and scalable ecosystem analysis.

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