GIS Mapping of Bamboo Resources in Sta. Rita and Matuguinao, Samar with RF Algorithm and Convolutional Neural Network (CNN) – Phase 2
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Abstract
This research mapped bamboo resources in selected areas of Sta. Rita and Matuguinao, Samar to estimate bamboo area, determine species composition, and support sustainable resource planning. The study integrated Geographic Information Systems (GIS) with machine learning techniques, specifically Random Forest and Convolutional Neural Network algorithms, to improve the accuracy of bamboo resource mapping. Drone imagery, satellite validation, and ground surveys were utilized to analyze plantation distribution and generate detailed spatial data. Results demonstrated that combining GIS and machine learning methods …
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Cite This Research
F Gomba, R Tabiongan, N Palomas, E Celada (2024). GIS Mapping of Bamboo Resources in Sta. Rita and Matuguinao, Samar with RF Algorithm and Convolutional Neural Network (CNN) – Phase 2. College of Engineering, Samar State University. Retrieved from https://gov-aideas.ssu.edu.ph/research/gis-mapping-of-bamboo-resources-in-sta-rita-and-matuguinao-samar-with-rf-algorithm-and-convolutional-neural-network-cnn-phase-2
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Research Information
- Research Type
- Applied Research
- Sector
- Environment & Disaster Resilience
- College
- College of Engineering
- Published
- March 06, 2026
- Last Updated
- March 06, 2026
- Access Level
- Public
- File Size
- 6.5 MB