Assessing tree toppling vulnerability through image processing : an application of python programming in disaster risk mitigation

Date

5-2026

Adviser

Kharisa Mae M. Pasion

Principal

Buela, Mabel S.

Abstract

While several countermeasure efforts such as early warning systems, hazard maps, and live news reports exist to minimize or totally prevent hydrometeorological hazards within the Philippines, highlighting the implementation of a specific interactive program catered to analyzing tree structure for infrastructure safety will help civilians play a role in their local community through disaster risk reduction and management with the common tools such as a mobile device equipped with a functioning camera. The Philippines is a country that often suffers at the hands of devastating hydrometeorological events such as harsh winds brought by devastating typhoons disrupting the essential functioning of a community. The study focused on creating a Python program trained by TensorFlow and YOLOv8 AI models for image classification, and OpenCV for image processing. The program fulfilled the objective of classifying tree species, extracting their angle of inclination and diameter, and ultimately providing an overall assessment of tree susceptibility to being uprooted or knocked over when subjected to strong winds in relation to a given angle of inclination, and diameter. This study aims to mitigate the dangers posed by hazardous and unregulated trees often leading to road blockage, power outages, infrastructure damage, and even fatal accidents through equipping individuals without qualifications, experience, or knowledge of dealing with hazardous trees with the accessible program. For future works, the study can be developed as a stand-alone mobile application that civilians may use to send direct reports and requests to their respective local government units to coordinate with Department of Environmental and Natural Resources (DENR) protocol in cutting and removing hazardous trees

Language

English

Location

Up Rural High School

Document Type

Capstone

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