New Remote Sensing Findings from International Research Center Published (Drought Vulnerability Curves Based on Remote Sensing and Historical Disaster Dataset): Technology – Remote Sensing

2023 FEB 28 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- Fresh data on remote sensing are presented in a new report. According to news reporting from Beijing, People’s Republic of China, by NewsRx journalists, research stated, “As drought vulnerability assessment is fundamental to risk management, it is urgent to develop scientific and reasonable assessment models to determine such vulnerability. A vulnerability curve is the key to risk assessment of various disasters, connecting analysis of hazard and risk.”

Funders for this research include Strategic Priority Research Program of The Chinese Academy of Sciences; National Natural Science Foundation of China.

Our news reporters obtained a quote from the research from International Research Center: “To date, the research on vulnerability curves of earthquakes, floods and typhoons is relatively mature. However, there are few studies on the drought vulnerability curve, and its application value needs to be further confirmed and popularized. In this study, on the basis of collecting historical disaster data from 52 drought events in China from 2009 to 2013, three drought remote sensing indexes were selected as disaster-causing factors; the affected population was selected to reflect the overall disaster situation, and five typical regional drought vulnerability curves were constructed. The results showed that (1) in general, according to the statistics of probability distribution, most of the normalized difference vegetation index (NDVI) and the temperature vegetation drought index (TVDI) variance ratios were concentrated between 0 and ~0.15, and most of the enhanced vegetation index (EVI) variance ratios were concentrated between 0.15 and ~0.6. From a regional perspective, the NDVI and EVI variance ratio values of the northwest inland perennial arid area (NW), the southwest mountainous area with successive years of drought (SW), and the Hunan Hubei Jiangxi area with sudden change from drought to waterlogging (HJ) regions were close and significantly higher than the TVDI variance ratio values. (2) Most of the losses (drought at-risk populations, DRP) were concentrated in 0~0.3, with a cumulative proportion of about 90.19%. At the significance level, DRP obeys the Weibull distribution through hypothesis testing, and the parameters are optimal. (3) The drought vulnerability curve conformed to the distribution rule of the logistic curve, and the line shape was the growth of the loss rate from 0 to 1. It was found that the arid and ecologically fragile area in the farming pastoral ecotone (AP) region was always a high-risk area with high vulnerability, which should be the focus of drought risk prevention and reduction.”

According to the news editors, the research concluded: “The study reduces the difficulty of developing the vulnerability curve, indicating that the method can be widely used to other regions in the future. Furthermore, the research results are of great significance to the accurate drought risk early warning or whether to implement the national drought disaster emergency rescue response.”

For more information on this research see: Drought Vulnerability Curves Based on Remote Sensing and Historical Disaster Dataset. Remote Sensing, 2023,15(858):858. (Remote Sensing - http://www.mdpi.com/journal/remotesensing/). The publisher for Remote Sensing is MDPI AG.

A free version of this journal article is available at https://doi.org/10.3390/rs15030858.

Our news journalists report that more information may be obtained by contacting Huicong Jia, International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, People’s Republic of China. Additional authors for this research include Fang Chen, Enyu Du, Lei Wang.

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