Data-Driven Insights into the Spatial Distribution and Conservation Status of Protected Areas in the Philippines: A WEKA Case Study

Fallaria A Clrear; Joe Mari C Geli; Sanger G Santillana; Shane L Yujoco

Data-Driven Insights into the Spatial Distribution and Conservation Status of Protected Areas in the Philippines: A WEKA Case Study

Author(s)	Ms. Fallaria A Clrear, Mr. Joe Mari C Geli, Mr. Sanger G Santillana, Mr. Shane L Yujoco
Country	Philippines
Abstract	This study examined how data mining techniques in WEKA can be used to analyze patterns in the spatial distribution and conservation status of protected and conserved areas using the normalized protected_conserved_areas_wdpca_points dataset. The dataset is country-specific: all 144 records are coded to the Philippines using the ISO3 country code PHL. The records represent site-level protected and conserved areas, including internationally recognized protected areas, local conservation areas, and locally managed marine protected areas. The study analyzed 144 instances and 33 attributes through four clustering algorithms: EM, SimpleKMeans, HierarchicalClusterer, and FarthestFirst. The results show that the dataset contains a clear clustering structure dominated by a broad group of OECM-like or locally managed marine protection records, alongside a much smaller but highly distinct subset associated with formally designated protected areas and stronger international-recognition signals. Spatial-distribution proxies and conservation-status attributes such as realm, reported area, site type, designation, no-take category, and status year were important in explaining the observed groupings. Among the algorithms, EM provided the most informative and interpretable solution because it identified a three-cluster structure of 99, 37, and 8 records rather than only a coarse binary split. The findings further indicate that cluster-based analysis can support differentiated management review, data-quality checking, and reporting improvement. Overall, the study confirms that WEKA-based clustering is a practical exploratory tool for profiling protected/conserved area records when the goal is segmentation and interpretation rather than predictive classification.
Keywords	Protected Areas, Spatial Distribution, Conservation Status, Philippines, WEKA, Data Analysis
Field	Computer > Data / Information
Published In	Volume 8, Issue 3, May-June 2026
Published On	2026-05-13

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Data-Driven Insights into the Spatial Distribution and Conservation Status of Protected Areas in the Philippines: A WEKA Case Study

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