ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Download
Publications Copernicus
Download
Citation
Articles | Volume X-3/W1-2022
https://doi.org/10.5194/isprs-annals-X-3-W1-2022-9-2022
https://doi.org/10.5194/isprs-annals-X-3-W1-2022-9-2022
27 Oct 2022
 | 27 Oct 2022

ANALYSIS OF THE SUPER TYPHOON RAI-INDUCED INFRASTRUCTURE DAMAGE IN SEVERELY AFFECTED AREAS OF CARAGA REGION, PHILIPPINES USING SENTINEL-1 SAR IMAGERIES

K. P. Bolanio, M. M. Bermoy, A. C. Gagula, J. G. Vernante, A. M. Boligor, and J. M. Cabañelez

Keywords: Sentinel-1 SAR, Coherence Change Detection (CCD), Normalized Difference Built-Up Index (NDBI), Damage Assessment, Typhoon Rai

Abstract. The Philippines is prone to typhoons because of how it is geographically located around the globe. A recent event that devastated many parts of Mindanao and Visayas was super typhoon Odette with the international name “Rai.” It was estimated that damage to infrastructures equates to over P17.71 billion as of January 10, 2022, and that Caraga Region has suffered the most significant loss totalling more than P12.82 billion. Due to the large-scale incurred damages, the number of people who were affected and suffered heavy economic loss, it is necessary to find ways that would provide spatial information to help decision-makers, stakeholders, and emergency respondents to prioritize areas which need the utmost concern. Over the past years, damage assessment maps were derived from optical images, which are weather-dependent and free. However, appropriate satellite images are hard to come by, especially during typhoons where clouds are prominent. Sentinel-1 SAR imagery was used because of its unique characteristics. It is not weather-dependent, before and after images from the event are available, and it is an open-source data. Damage maps were generated by detecting the change in the complex coherence between pre-and co-typhoon stacked images. Results were validated using high-resolution satellite images from reliable sources, finding out that there is good correspondence between the coherence-based change images and ground data depicted from high-resolution satellite images. It is concluded that Sentinel-1 SAR imagery could capture the extent of damages and help provide timely and accurate geospatial information during catastrophic events.