Published June 12, 2021 | Version v1
Dataset Restricted

Dataset of Tropical cyclone risk assessment in Guangdong

Authors/Creators

  • 1. Guangzhou Institute of Geochemistry

Description

The dataset uses multi-source datasets (TC, remote sensing, meteorological, vector, and socioeconomic data) from various domestic and international data platforms and institutions .The TC best track data was obtained at the Japan Meteorological Agency (JMA) (http://www.jma.go.jp/jma/jma-eng/jma-center/rsmc-hp-pub-eg/besttrack.html) and Japan typhoon Digital Center (http://agora.ex.nii.ac.jp/digital-typhoon ).Tropical cyclone information for past tropical cyclones includes the position, central pressure, moving velocity, duration time ,moving distance and intensity of each TC from 1951-2018 for every six hour. Remote sensing data include digital elevation model (DEM), normalized difference vegetation index (NDVI), land use, and land cover. Meteorological data include the wind speed and total precipitation.Total precipitation and wind speed is in the period of 2010-2018 , collected respectively from China Meterological Administration(http://data.cma.cn),.Socioeconomic data include the population density, GDP, and historical disaster loss.The data of population density, GDP and vegetation index were obtained from spatial grid datasets of the Chinese population, GDP and vegetation index based on 1km spatial resolution.Land use and cover data was from multi period land use and cover remote sensing datasets in China (CNLUCC), and all these datasets is available at Resource and Environment data Cloud Platform provided by Institute of geography, resources and environment, Chinese Academy of Sciences(http://www.resdc.cn). DEM data  was deprived  from Aster GDEM v2 at 30 m resolution, available at United States Geological Survey (USGS Earth Explorer site in Center for Earth Observation.The indicator of Slope is calculated from the DEM data..Vector data include road networks, railway networks, water networks, coastlines and point of interest (POI) data such as the medical, public, and educational infrastructure and charitable organizations in the cities of Guangdong.The Indicator of coastline,river density ,railway were deprived from 1: 1 million National basic geographic information dataset (2017 version)in National Basic Geographic Information Center.

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