International Journal on Advanced Science, Engineering and Information Technology, Vol. 12 (2022) No. 2, pages: 621-626, DOI:10.18517/ijaseit.12.2.15003
A Baseline Assessment of the Multi-Hazard Early Warning Systems in the Province of Batangas, Philippines
Marlon Era, Edgar Vallar, Abdul Jhariel Osman, Ruben Paul Borg, Glorianne Borg Axisa, Ignacio Aguirre Ayerbe, Maria Merino Gonzalez-Pardo, Boyko RanguelovAbstract
Batangas is a first-class province of the Philippines located on the southwestern part of Luzon in the CALABARZON region. Its capital is Batangas City and the provinces of Cavite and Laguna border it to the north and Quezon to the east. Across the Verde Island Passages to the south is the island of Mindoro and to the west lies the South China Sea. Geographically, Batangas is a combination of plains and mountains, including the world’s smallest volcano, Mt. Taal, with an elevation of 600 meters, located in the middle of the Taal Lake. Other important peaks in Batangas include Mt. Makulot with an elevation of 830 m, Mt. Talamitan with 700 m, Mt. Pico de Loro with 664 m, Mt. Batulao with 811 m, Mt. Manabo with 830 m, and Mt. Daguldol with 672 m. The province has many beaches and is famous for its excellent diving spots. It has the second largest international seaport in the Philippines after Metro Manila. The city's identification as an industrial growth center in the region and the focal point of the CALABARZON program resulted in the increasing number of business establishments in the city’s Central Business District (CBD) and numerous industries operating at the province’s industrial parks. Given the geographical nature of the province and its current development, the present study was envisioned to assess its preparation for any forms of an imminent natural disaster. In particular, the study assessed the usage of multi-hazard early warning systems in the province using survey interviews with various stakeholders. The results of the 30 survey interviews showed that there is a limited multi-hazard early warning system in the province although the majority of the participants have experienced natural disasters in their respective areas.
Keywords:
Media Analytics; GDELT; Disaster News; Earthquake; Indonesia
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