The other socioeconomic assets described earlier (industrial zones, hotels, health care facilities, schools, powerplants and electrical substations) are in point formats. A hotel, for example, is represented by a latitude-longitude pair located at its center. However, it is not only at this center point at which danger of flooding is relevant, but also at the surrounding hotel buildings and recreational facilities. In order to take this into account, a circular buffer of a fixed length is defined for each asset type described by a point location. This buffer is chosen to approximate the typical size of each analyzed asset class. Flood exposure is then checked not only at the center point, but also at the buffered area around the point. The buffers assigned to assets are 100 meters in radius for hospitals, schools, electrical substations, and industrial areas, and 200 meters in radius for hotels and power plants. Flood exposure is determined as in the previous analyses, with the results computed and protection offsets applied for each province, return period, and set of flood maps.

4.4. Typhoon wind exposure of electricity transmission infrastructure The exposure of electricity transmission infrastructure to cyclones is computed similarly to the flood exposure analysis. For each cyclone return period, an overlay between the cyclone raster and the transmission lines in polygon form determine which parts of the network are affected by which wind speed.

But high wind speeds do not have the same effect everywhere. In fact, their disruptive impact on the power grid is mediated by forests. Outages during storms are often caused by trees that fall onto transmission lines and take out a section of the grid (Rentschler et al. 2019b). In order to identify sections of the power grid that are particularly threatened in this way, the land use data described in section 3.1 is incorporated into the analysis. Specifically, the area surrounding the transmission lines (within 100 meters on either side) is probed on whether it is forested or not. Then, each 1 kilometer section of the grid is classified as either located in a dense forest (at least 75 percent tree cover), located in a light forest (tree cover between 25 and 75 percent), or located in a non-forested area (figure 4.6).

According to this approach, 36 percent of the Vietnamese transmission grid is located in forests, and 15 percent is located in dense forests. The exposure to typhoon wind speeds is then determined individually for the sections of the transmission network located in heavy, light, and non-forested areas.

As mentioned in section 3.7, the digitization process of the power lines could have resulted in errors in the locations of certain sections of the grid. Given the resolution of the wind speed data of about 30km, this should not have a major effect on the overlay with the wind speed data. However, the classification of transmission line segments according to the forest cover in the surrounding area is more sensitive to such errors. Here, the vertical displacement of a power line section could lead to it being classified as nonforested when it is located in a forest or vice versa. Although this inaccuracy is somewhat reduced by looking not only at the area directly underneath a power line but also the area surrounding it, this caveat should be kept in mind when interpreting the results.

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