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Collecting and Processing Drone-based Remotely Sensed Data for Use in Forest Recovery Monitoring
Published on: October 24, 2025
454
Automated forest land division using deep learning and drone imagery.
Kushagra Umesh Borse1, Ninad Nilesh Sugandhi1, Chirayu Batra1
1School of Computer Science and Engineering, Vellore Institute of Technology, Chennai, India.
Plos One
|October 31, 2025
Summary
This study presents an automated drone-based system for accurate tree counting in forest land division. This technology improves efficiency and supports sustainable forest management.
Area of Science:
- Forestry
- Remote Sensing
- Computer Vision
Background:
- Traditional tree enumeration methods are labor-intensive and prone to inaccuracies.
- Efficient forest land division requires precise tree data.
Purpose of the Study:
- To develop an automated tree enumeration system for forest land division.
- To leverage drone imagery and computer vision for accurate tree detection.
Main Methods:
- Utilizing drone-captured imagery.
- Applying advanced computer vision algorithms for tree crown detection.
- Developing an automated processing pipeline.
Main Results:
- Demonstrated accurate detection of tree crowns from drone images.
- Provided a quantifiable method for tree enumeration.
- Showcased the system's potential for practical application.
Conclusions:
- The automated solution offers a significant improvement over traditional tree counting methods.
- This technology facilitates informed decision-making in forest land management.
- The system promotes sustainability and efficient resource utilization in forestry.
