{"title":"利用云计算平台 \"谷歌地球引擎\",基于双偏振雷达对泰国北部严重受灾地区制作的冰雹地图进行空间评估","authors":"Nattapon Mahavik, Sarintip Tantanee, Fatah Masthawee","doi":"10.1007/s12518-024-00569-4","DOIUrl":null,"url":null,"abstract":"<div><p>The objective of this study was to use dual-polarimetric radar data to create an hourly hail product, which would then be analyzed using Google Earth Engine (GEE), a cloud computing platform. We used ground-based weather radar from the Thailand Meteorological Department’s Chiang Rai station in the north of Thailand. Dual-polarimetric weather radar data were analyzed at 15-minute intervals with Python-based open-source radar libraries such as PyArt and Wradlib. Hydrometeor classification was conducted using simulated atmospheric sounding data obtained from ERA5 reanalysis data, which had been classified into ten classes between 17.00 and 20.00 Local Time. At a 2-kilometer altitude grid, similar hydrometeor types with comparable solid-state characteristics were collected and presented in CAPPI format. Furthermore, we used JavaScript programming to conduct a localized impact study of the hailstorm in GEE in order to prove the preliminary damage assessment concept by comprising sophisticated spatial overlays with land use data, urban regions, farmland, population data, and counts of roofed homes. The analysis results in GEE reveal the potential damaging area prone to hailstorm passage. This is the first attempt in Thailand to create an hourly hailstorm product and integrate it into the Geographic Information System (GIS) using GEE’s cloud-based platform. This invention can annually support local organizations in disaster monitoring, impact assessment, and adaptation to hail-related events.</p></div>","PeriodicalId":46286,"journal":{"name":"Applied Geomatics","volume":null,"pages":null},"PeriodicalIF":2.3000,"publicationDate":"2024-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Spatial assessment of produced hailstorm maps in severely affected areas in Northern Thailand based on dual-polarimetric radar using the cloud computing platform Google Earth Engine\",\"authors\":\"Nattapon Mahavik, Sarintip Tantanee, Fatah Masthawee\",\"doi\":\"10.1007/s12518-024-00569-4\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>The objective of this study was to use dual-polarimetric radar data to create an hourly hail product, which would then be analyzed using Google Earth Engine (GEE), a cloud computing platform. We used ground-based weather radar from the Thailand Meteorological Department’s Chiang Rai station in the north of Thailand. Dual-polarimetric weather radar data were analyzed at 15-minute intervals with Python-based open-source radar libraries such as PyArt and Wradlib. Hydrometeor classification was conducted using simulated atmospheric sounding data obtained from ERA5 reanalysis data, which had been classified into ten classes between 17.00 and 20.00 Local Time. At a 2-kilometer altitude grid, similar hydrometeor types with comparable solid-state characteristics were collected and presented in CAPPI format. Furthermore, we used JavaScript programming to conduct a localized impact study of the hailstorm in GEE in order to prove the preliminary damage assessment concept by comprising sophisticated spatial overlays with land use data, urban regions, farmland, population data, and counts of roofed homes. The analysis results in GEE reveal the potential damaging area prone to hailstorm passage. This is the first attempt in Thailand to create an hourly hailstorm product and integrate it into the Geographic Information System (GIS) using GEE’s cloud-based platform. This invention can annually support local organizations in disaster monitoring, impact assessment, and adaptation to hail-related events.</p></div>\",\"PeriodicalId\":46286,\"journal\":{\"name\":\"Applied Geomatics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.3000,\"publicationDate\":\"2024-06-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Applied Geomatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s12518-024-00569-4\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"REMOTE SENSING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Geomatics","FirstCategoryId":"1085","ListUrlMain":"https://link.springer.com/article/10.1007/s12518-024-00569-4","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"REMOTE SENSING","Score":null,"Total":0}
Spatial assessment of produced hailstorm maps in severely affected areas in Northern Thailand based on dual-polarimetric radar using the cloud computing platform Google Earth Engine
The objective of this study was to use dual-polarimetric radar data to create an hourly hail product, which would then be analyzed using Google Earth Engine (GEE), a cloud computing platform. We used ground-based weather radar from the Thailand Meteorological Department’s Chiang Rai station in the north of Thailand. Dual-polarimetric weather radar data were analyzed at 15-minute intervals with Python-based open-source radar libraries such as PyArt and Wradlib. Hydrometeor classification was conducted using simulated atmospheric sounding data obtained from ERA5 reanalysis data, which had been classified into ten classes between 17.00 and 20.00 Local Time. At a 2-kilometer altitude grid, similar hydrometeor types with comparable solid-state characteristics were collected and presented in CAPPI format. Furthermore, we used JavaScript programming to conduct a localized impact study of the hailstorm in GEE in order to prove the preliminary damage assessment concept by comprising sophisticated spatial overlays with land use data, urban regions, farmland, population data, and counts of roofed homes. The analysis results in GEE reveal the potential damaging area prone to hailstorm passage. This is the first attempt in Thailand to create an hourly hailstorm product and integrate it into the Geographic Information System (GIS) using GEE’s cloud-based platform. This invention can annually support local organizations in disaster monitoring, impact assessment, and adaptation to hail-related events.
期刊介绍:
Applied Geomatics (AGMJ) is the official journal of SIFET the Italian Society of Photogrammetry and Topography and covers all aspects and information on scientific and technical advances in the geomatics sciences. The Journal publishes innovative contributions in geomatics applications ranging from the integration of instruments, methodologies and technologies and their use in the environmental sciences, engineering and other natural sciences.
The areas of interest include many research fields such as: remote sensing, close range and videometric photogrammetry, image analysis, digital mapping, land and geographic information systems, geographic information science, integrated geodesy, spatial data analysis, heritage recording; network adjustment and numerical processes. Furthermore, Applied Geomatics is open to articles from all areas of deformation measurements and analysis, structural engineering, mechanical engineering and all trends in earth and planetary survey science and space technology. The Journal also contains notices of conferences and international workshops, industry news, and information on new products. It provides a useful forum for professional and academic scientists involved in geomatics science and technology.
Information on Open Research Funding and Support may be found here: https://www.springernature.com/gp/open-research/institutional-agreements