Abstract
In this study, an artificial intelligence-based system is being developed to detect tree locations using satellite and drone imagery. The system utilizes the YOLOv8 model to identify trees and processes location and altitude data obtained from the drone to determine the geographical coordinates of each tree. While the model performs successfully on static images, it also employs drone flight and camera parameters to achieve precise location calculations. Additionally, real-time tree detection and location estimation algorithms are being tested using drone-captured videos, with ongoing efforts to enhance the system. The accuracy of location calculations are being tested by comparing with Google Earth and other mapping tools are ongoing. This study aims to improve agricultural productivity, optimize forest management, and contribute to environmental sustainability.
| Translated title of the contribution | Determining Tree Locations via Satellite and Drone Data |
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| Original language | Turkish |
| Title of host publication | 33rd IEEE Conference on Signal Processing and Communications Applications, SIU 2025 - Proceedings |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (Electronic) | 9798331566555 |
| DOIs | |
| Publication status | Published - 2025 |
| Event | 33rd IEEE Conference on Signal Processing and Communications Applications, SIU 2025 - Istanbul, Turkey Duration: 25 Jun 2025 → 28 Jun 2025 |
Publication series
| Name | 33rd IEEE Conference on Signal Processing and Communications Applications, SIU 2025 - Proceedings |
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Conference
| Conference | 33rd IEEE Conference on Signal Processing and Communications Applications, SIU 2025 |
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| Country/Territory | Turkey |
| City | Istanbul |
| Period | 25/06/25 → 28/06/25 |
Bibliographical note
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