Application of Gumbel mixture extreme theory and maximum likelihood to estimate the seismic risk of the Chinese mainland

1995 ◽  
Vol 8 (2) ◽  
pp. 325-331 ◽  
Author(s):  
Hong Chen ◽  
Zhong-Xian Huang
Keyword(s):  
Maximum Likelihood ◽  
Seismic Risk ◽  
Chinese Mainland ◽  
The Chinese Mainland ◽  
Extreme Theory

scholarly journals A Potential Risk Index Dataset for Landfalling Tropical Cyclones over the Chinese Mainland (PRITC dataset V1.0)

2021 ◽  
Vol 38 (10) ◽  
pp. 1791-1802
Author(s):  
Peiyan Chen ◽  
Hui Yu ◽  
Kevin K. W. Cheung ◽  
Jiajie Xin ◽  
Yi Lu
Keyword(s):  
Tropical Cyclones ◽  
Potential Risk ◽  
Risk Index ◽  
Chinese Mainland ◽  
Current Version ◽  
Term Trend ◽  
The Chinese Mainland ◽  
Landfalling Tropical Cyclones ◽  
Long Term Trend

AbstractA dataset entitled “A potential risk index dataset for landfalling tropical cyclones over the Chinese mainland” (PRITC dataset V1.0) is described in this paper, as are some basic statistical analyses. Estimating the severity of the impacts of tropical cyclones (TCs) that make landfall on the Chinese mainland based on observations from 1401 meteorological stations was proposed in a previous study, including an index combining TC-induced precipitation and wind (IPWT) and further information, such as the corresponding category level (CAT_IPWT), an index of TC-induced wind (IWT), and an index of TC-induced precipitation (IPT). The current version of the dataset includes TCs that made landfall from 1949–2018; the dataset will be extended each year. Long-term trend analyses demonstrate that the severity of the TC impacts on the Chinese mainland have increased, as embodied by the annual mean IPWT values, and increases in TCinduced precipitation are the main contributor to this increase. TC Winnie (1997) and TC Bilis (2006) were the two TCs with the highest IPWT and IPT values, respectively. The PRITC V1.0 dataset was developed based on the China Meteorological Administration’s tropical cyclone database and can serve as a bridge between TC hazards and their social and economic impacts.

scholarly journals Nightlight as a Proxy of Economic Indicators: Fine-Grained GDP Inference Around Mainland China via Attention-Augmented CNN from Daytime Satellite Imagery

2021 ◽  
Vol 13 (11) ◽  
pp. 2067
Author(s):  
Haoyu Liu ◽  
Xianwen He ◽  
Yanbing Bai ◽  
Xing Liu ◽  
Yilin Wu ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Remote Sensing Data ◽  
Chinese Mainland ◽  
Economic Research ◽  
Official Method ◽  
County Level ◽  
Socioeconomic Indicators ◽  
Sensing Data ◽  
Fine Grained ◽  
The Chinese Mainland

The official method of collecting county-level GDP values in the Chinese Mainland relies mainly on administrative reporting data and suffers from high costs of time, money, and human labor. To date, a series of studies have been conducted to generate fine-grained maps of socioeconomic indicators from the easily accessed remote sensing data and achieved satisfactory results. This paper proposes a transfer learning framework that regards nightlight intensities as a proxy of economic activity degrees to estimate county-level GDP around the Chinese Mainland. In the framework, paired daytime satellite images and nightlight intensity levels were applied to train a VGG-16 architecture, and the output features at a specific layer, after dimensional reduction and statistics calculation, were fed into a simple regressor to estimate county-level GDP. We trained the model with data of 2017 and utilized it to predict county-level GDP of 2018, achieving an R-squared of 0.71. Furthermore, the results of gradient visualization confirmed the validity of the proposed framework qualitatively. To the best of our knowledge, this is the first time that county-level GDP values around the Chinese Mainland have been estimated from both daytime and nighttime remote sensing data relying on attention-augmented CNN. We believe that our work will shed light on both the evolution of fine-grained socioeconomic surveys and the application of remote sensing data in economic research.

scholarly journals A study on the genus Phaecasiophora Grote (Lepidoptera: Tortricidae: Olethreutinae) from the mainland of China, with descriptions of five new species

2006 ◽  
Vol 17 (1) ◽  
pp. 34-45
Author(s):  
Haili Yu ◽  
Houhun Li
Keyword(s):  
New Species ◽  
Chinese Mainland ◽  
New Synonyms ◽  
New Synonym ◽  
The Chinese Mainland ◽  
The Mainland Of China ◽  
Three New Species

Fourteen species of Phaecasiophora Grote from the Chinese Mainland are treated, including five new species (P. supparallelica sp. n., P. levis sp. n., P. curvicosta sp. n., P. lushina sp. n., and P. similithaiensis sp. n.) and three new species records for China. Phaecasiophora leechi is transferred from subgenus Megasyca to subgenus Phaecasiophora, and a new synonym of it, viz. P. obligata Kawabe, is proposed. Photographs of the adults, genitalia of the new species, and the species with new synonyms are provided. A key to the species from the Chinese Mainland based on genitalia is given.

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