Typhoon No.13 in 2006 (Typhoon 0613) passed through Yamaguchi Prefecture, Japan on Sep.17, 2006. After being hit by it, many landscape trees, especially ginkgo in Yamaguchi City, showed symptoms of necrosis on the leaf tip and margin, and even the entire leaf. It clearly divided the crowns of some ginkgo trees into the green part and the non-green part. In order to quantitatively study this phenomenon, the normalized difference vegetation index (NDVI) near red edge for ginkgo leaves, measured by a pocket radiometer in the lab, was used to estimate leaf necrosis induced by Typhoon 0613. Based on this research, the optimum wavelength for calculation of the NDVI value of ginkgo leaves damaged by Typhoon 0613 is 679 and 755 nm, which sufficiently corresponds to variance in ginkgo leaf necrosis. By leaf necrosis investigation, the difference in the percentage of necrotic leaves between the windward and leeward sides made the crowns of damaged ginkgo trees show different colors on either side of the crown. An inverse linear relationship between the necrotic area percentage (NAP) and NDVI755nm/679nm was obtained for ginkgo leaves. By analysis of the NDVI using ratio (NDVIr) value of crowns, it was indicated that there were differences in leaf necrosis induced by Typhoon 0613 among sites of different distances away from the coastline and between ginkgo and other tree species. It has potential to be an alternative tool for evaluating the damage status of ginkgo trees hit by typhoons like Typhoon 0613.
In this paper the risk neutrality paradigm for government stocks and investments is challenged within the context of catastrophe risk. We focus on government’s ability to spread its natural disaster risk. Based on the classical approach of Arrow and Lind, the paper shows the weaknesses of and reformulates the risk neutral assumption for government decisions under uncertainty. The rationale that governments have kinked utility functions, which can arise from natural disaster events, is given through a network example and its implications explained considering also risk aversion and the benefits of different types of risk management strategies.
Mongolian wildland fires are a human-made disaster like some floods as shown by these fire disasters becoming prominent around the 1990s due to opening up of the country. The worst fire losses were in 1996, costing 192% of the GDP. This study reports recent wildland fire incidence and climate relationships analyzed using NASA-MODIS hotspots (fires) and NOAA weather data. Fires are categorized into spring fires from April to June in pasture areas, summer fires in July and August in forested areas, and autumn fires in September and October in forested areas. Fires frequently occur after 10 rainless days, while several millimeters of daily precipitation reduces the extent of fire. A weeklong effective humidity of below 35% coincided with large fires. In the seven most recent years, average temperatures increased by 3.4°C in July and summer precipitation decreased by about 50%, while the fire disaster intensity increased. The fires were mainly human caused, began at relatively low altitudes after the snow melt in April, and moved to higher-altitude areas in May. From 2001 to 2007, around 30% of forest areas were affected; the Selenge, Khentii, and Dornod provinces were the most fire prone. The severest spring and autumn fires occurred on May 5, 2007 and September 22, 2002.