VOLUME 17 (Supplement)

SciEnggJ%202024%20Special%20Issue%20148 154 Maarof%20et%20al

SciEnggJ 17 (Supplement) 517-536
available online: 31 December 2024
DOI: https://doi.org/10.54645/202417SupPOK-66

*Corresponding author
Email Address: krisrael@up.edu.ph
Date received: 19 February 2024
Date revised: 15 August 2024
Date accepted: 23 December 2024

ARTICLE

Forest restoration assessment in selected critical watersheds in the Philippines using NDVI and Google Earth Engine

Kyle Pierre R. Israel*1, Cristino L. Tiburan Jr.2, Enrique L. Tolentino Jr.2, and Nathaniel C. Bantayan2

1Department of Community and Environmental Resource Planning,
    College of Human Ecology, University of the Philippines
    Los Baños
2Institute of Renewable Natural Resources, College of Forestry and
    Natural Resources, University of the Philippines Los Baños

KEYWORDS: forest landscape restoration, NDVI, Landsat, Google Earth Engine, trend test

Forest cover in the Philippines has reduced drastically over the past decades. To address the problem, the government embarked on a massive forest restoration program called the National Greening Program (NGP) that started in 2011 and recently extended until 2028. The performance of NGP was evaluated using a cloud-based technique called Google Earth Engine (GEE). Landsat imageries were used within the cloud library of GEE, and vegetation index data were computed annually covering the period 1996 until 2021.

Reforestation sites were considered in the monitoring of vegetation quality using Normalized Difference Vegetation Index (NDVI). The annual trends in the vegetation index were analyzed for these sites. Sen’s slope and Mann-Kendall trend test were employed to assess the statistical significance of the trends. Results reveal that from 2011 onwards, areas implemented purely with NGP could not yield statistically significant trends in all the watersheds chosen for the study, with p-values of 0.0736 for Salug Daku and Padada watersheds and 0.1611 for Labangxan watershed. Ground truthing may reveal further insights into the effects of the program on the vegetation coverage. Further studies are recommended to observe the consistency of the results, as the duration of the time series used in this study is limited.

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