[MIS05-P05] Remote Sensing Assessment of Typhoon-Induced Vegetation Damage over the Philippines
Keywords:Typhoon, damage asessment, Philippines, Landsat
Remote Sensing is a cost-effective tool in analyzing areas that are challenging to observe with field surveys. With the presence of numerous satellites equipped with high resolution and multi-spectral sensors, images of areas hit by natural calamities are easily obtained few days after the disaster struck. Comparison of the Normalized Difference Vegetation Index (NDVI) method obtained pre- and post-storm is commonly used by numerous researches in detecting damages after a storm's passing.
In this research we examine typhoon-induced damage to vegetation by utilizing NDVI and relating it to the typhoon's features: wind and rainfall, and to the characteristic of the area hit: elevation, aspect and land cover type. This research is in support of the goal of rapid post-typhoon assessment in the Philippines with the use of its microsatellite, Diwata. In the future, we want to use images taken by Diwata in post disaster assessment.
Two typhoons were analyzed, Typhoons Haiyan and Koppu. Both hit the Philippines and brought devastating damages to the country. The area analyzed are the provinces of Leyte and Nueva Ecija for Typhoon Haiyan and Koppu, respectively. The main difference between these two storms is that Typhoon Haiyan carried with it strong winds more than heavy rainfall while Typhoon Koppu, on the other hand, carried more heavy rain than strong winds. In both cases the NDVI significantly decreased after the typhoon hit with values of -0.12 +- 0.13 (mean +- standard deviation) and -0.14 +- 0.14 with paired t-test p values < 0.001 for Typhoons Haiyan and Koppu, respectively. Damage as a function of rainfall, aspect, land cover type and elevation were analyzed for each case. We also calculated the influence of each variable to the measured damage using Artificial Neural Network. We found that the elevation is the strongest influence, followed by aspect, rainfall and lastly land cover.