Abstract
Abstract. Forest disturbance induced by tropical cyclone often has significant and profound effects on the structure and function of forest ecosystem. Detection and analysis of post-disaster forest disturbance based on remote sensing technology has been widely applied. At present, it is necessary to conduct further quantitative analysis of the magnitude of forest disturbance with the intensity of typhoon. In this study, taking the case of super typhoon Rammasun (201409), we analysed the sensitivity of four common used remote sensing indices and explored the relationship between remote sensing index and corresponding wind speeds based on pre-and post- Landsat-8 OLI (Operational Land Imager) images and a parameterized wind field model. The results proved that NBR is the most sensitive index for the detection of forest disturbance induced by Typhoon Rammasun and the variation of NBR has a significant linear dependence relation with the simulated 3-second gust wind speed.
Highlights
As a major part of terrestrial ecosystem, forest frequently suffers from dual influences of natural disasters and human activities and has dynamic changes at all time
The objective of this study is to explore whether there is a correlation between typhoon wind field distribution and magnitude of forest disturbance
Four commonly used normalized remote sensing indices were used for the detection of forest disturbance, they are normalized differential vegetation index (NDVI) (Rouse, 1973; Rouse et al, 1974), enhanced vegetation index (EVI) (Liu and Huete, 1995), normalized differential moisture index (NDMI) (Wilson amd Sader, 2002), and normalized burn ratio (NBR) (Key and Benson 1999), which can be expressed mathematically as follows: (2)
Summary
As a major part of terrestrial ecosystem, forest frequently suffers from dual influences of natural disasters and human activities and has dynamic changes at all time. High wind is one of the main hazards of TC, often causes extensive damage to the trees (e.g., breakage and uprooting) and brings about great property loss to forestry. Detecting the forest disturbance and evaluating the loss caused by typhoon are of great significance for deeply understanding the dynamic changes of forest ecosystems and having sustainable management, conservation and development of forestry. The remote sensing image has been an important data source for forest multi-disaster loss assessment due to its advantages such as wide coverage and dynamic real-time monitoring. Researches of forest disaster based on remote sensing data are limited to the quantitative detection of visual phenomena or the comparative analysis of vegetation indexes with environmental factors such as elevation, slope and aspect (Wang and Zhou, 2013; Guo et al, 2014). Some progress has been made in several studies that the different wind speed interval durations (Ramsey et al, 2001) and the distance away from the centre of hurricane (Ayala - Silva and Twumasi, 2004) have good correlations with the variations of NDVI, there exists plenty of room to study the relationship of hazard and exposure based on the remote sensing technology and hazard analysis method
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