Assessment of Factors of Mangrove Extent Growth in Eastern Leyte, Philippines
Authors
Sarah Jane Cabral
1College of Engineering, Eastern Visayas State University, Tacloban City, Leyte 6500, Philippines 2 DIT Candidate, La Consolacion University Philippines, Malolos, Bulacan 3000 Philippines (PH)
Jayson M. Victoriano
College of Information and Communications Technology, Bulacan State University, Malolos, Bulacan 3000, Philippines (PH)
Article Information
DOI: 10.51583/IJLTEMAS.2025.140500066
Subject Category: Eastern Leyte Philippines
Volume/Issue: 14/5 | Page No: 623-639
Publication Timeline
Submitted: 2025-06-16
Published: 2025-06-16
Abstract
Abstract: Recent satellite imagery analysis in the Eastern Leyte province indicates significant growth in mangrove forests following the destruction of approximately 86% of these forests during Typhoon Yolanda (Haiyan) in 2013. However, there are no studies that explore the process of mangrove expansion in the region and the factors influencing its growth. This study aims to investigate and analyze the climatological and anthropogenic factors contributing to the expansion of mangrove forests in the area. Using the mangrove index derived from Sentinel-2A satellite imagery, a percentile-based threshold segmentation was applied to classify and identify mangrove extent. Annual mangrove area data from 2017 to 2023 were calculated and correlated with climatological variables and anthropogenic factors. The result of the analysis shows a strong positive correlation between mangrove coverage and sea level with a variance of r2=0.90 and α<0.001 which is statistically significant. The relationship of the population to the mangrove coverage shows the model has a variance of r2=0.64 and α=0.030. In contrast, the rainfall shows a very weak and has no significant relationship with the mangrove coverage with a variance of r2= 0.022 and α=0.05. The findings reveal the significant role of sea level and population in the mangrove expansion. This study provides significant insights into accurate rehabilitation plans and strategies for mangrove preservation and conservation in the province.
Keywords
Mangrove, Remote Sensing, Mangrove Index, Linear Regression, Correlation Analysis
This article is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
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