{"@context":{"@vocab":"https://cir.nii.ac.jp/schema/1.0/","rdfs":"http://www.w3.org/2000/01/rdf-schema#","dc":"http://purl.org/dc/elements/1.1/","dcterms":"http://purl.org/dc/terms/","foaf":"http://xmlns.com/foaf/0.1/","prism":"http://prismstandard.org/namespaces/basic/2.0/","cinii":"http://ci.nii.ac.jp/ns/1.0/","datacite":"https://schema.datacite.org/meta/kernel-4/","ndl":"http://ndl.go.jp/dcndl/terms/","jpcoar":"https://github.com/JPCOAR/schema/blob/master/2.0/"},"@id":"https://cir.nii.ac.jp/crid/1362257544118386048.json","@type":"Article","productIdentifier":[{"identifier":{"@type":"DOI","@value":"10.3390/ijgi8070309"}},{"identifier":{"@type":"URI","@value":"https://www.mdpi.com/2220-9964/8/7/309/pdf"}}],"resourceType":"学術雑誌論文(journal article)","dc:title":[{"@value":"VS30 Seismic Microzoning Based on a Geomorphology Map: Experimental Case Study of Chiang Mai, Chiang Rai, and Lamphun, Thailand"}],"description":[{"type":"abstract","notation":[{"@value":"<jats:p>Thailand is not known to be an earthquake-prone country; however, in 2014, an unexpected moderate earthquake caused severe damage to infrastructure and resulted in public panic. This event caught public attention and raised awareness of national seismic disaster management. However, the expertise and primary data required for implementation of seismic disaster management are insufficient, including data on soil character which are used in amplification analyses for further ground motion prediction evaluations. Therefore, in this study, soil characterization was performed to understand the seismic responses of soil rigidity. The final output is presented in a seismic microzoning map. A geomorphology map was selected as the base map for the analysis. The geomorphology units were assigned with a time-averaged shear wave velocity of 30 m (VS30), which was collected by the spatial autocorrelation (SPAC) method of microtremor array measurements. The VS30 values were obtained from the phase velocity of the Rayleigh wave corresponding to a 40 m wavelength (C(40)). From the point feature, the VS30 values were transformed into polygonal features based on the geomorphological characteristics. Additionally, the automated geomorphology classification was explored in this study. Then, the seismic microzones were compared with the locations of major damage from the 2014 records for validation. The results from this study include geomorphological classification and seismic microzoning. The results suggest that the geomorphology units obtained from a pixel-based classification can be recommended for use in seismic microzoning. For seismic microzoning, the results show mainly stiff soil and soft rocks in the study area, and these geomorphological units have relatively high amplifications. The results of this study provide a valuable base map for further disaster management analyses.</jats:p>"}]}],"creator":[{"@id":"https://cir.nii.ac.jp/crid/1382257544118386049","@type":"Researcher","foaf:name":[{"@value":"Patcharavadee Thamarux"}],"jpcoar:affiliationName":[{"@value":"Department of Architecture and Building Engineering, School of Environment and Society, Tokyo Institute of Technology, Yokohama 226-8502, Japan"},{"@value":"Survey Division, Department of Survey, Electricity Generating Authority of Thailand, 53 Moo 2 Charansanitwong Road, Bang Kruai, Nonthaburi 11130, Thailand"}]},{"@id":"https://cir.nii.ac.jp/crid/1382257544118386052","@type":"Researcher","foaf:name":[{"@value":"Masashi Matsuoka"}],"jpcoar:affiliationName":[{"@value":"Department of Architecture and Building Engineering, School of Environment and Society, Tokyo Institute of Technology, Yokohama 226-8502, Japan"}]},{"@id":"https://cir.nii.ac.jp/crid/1382257544118386048","@type":"Researcher","foaf:name":[{"@value":"Nakhorn Poovarodom"}],"jpcoar:affiliationName":[{"@value":"Department of Civil Engineering, Faculty of Engineering, Thammasat University, Pathumthani 12120, Thailand"}]},{"@id":"https://cir.nii.ac.jp/crid/1420564276179538176","@type":"Researcher","personIdentifier":[{"@type":"KAKEN_RESEARCHERS","@value":"90391698"},{"@type":"NRID","@value":"1000090391698"},{"@type":"NRID","@value":"9000365014190"},{"@type":"NRID","@value":"9000002194104"},{"@type":"NRID","@value":"9000021959141"},{"@type":"NRID","@value":"9000018415160"},{"@type":"NRID","@value":"9000319056828"},{"@type":"NRID","@value":"9000002250399"},{"@type":"NRID","@value":"9000339174392"},{"@type":"RESEARCHMAP","@value":"https://researchmap.jp/Junko_IWAHASHI"}],"foaf:name":[{"@value":"Junko Iwahashi"}],"jpcoar:affiliationName":[{"@value":"Geospatial Information Authority of Japan, Geography and Crustal Dynamics Research Center, Ibaraki 305-0811, Japan"}]}],"publication":{"publicationIdentifier":[{"@type":"EISSN","@value":"22209964"}],"prism:publicationName":[{"@value":"ISPRS International Journal of Geo-Information"}],"dc:publisher":[{"@value":"MDPI AG"}],"prism:publicationDate":"2019-07-18","prism:volume":"8","prism:number":"7","prism:startingPage":"309"},"reviewed":"false","dcterms:accessRights":"http://purl.org/coar/access_right/c_abf2","dc:rights":["https://creativecommons.org/licenses/by/4.0/"],"url":[{"@id":"https://www.mdpi.com/2220-9964/8/7/309/pdf"}],"createdAt":"2019-07-18","modifiedAt":"2025-10-11","foaf:topic":[{"@id":"https://cir.nii.ac.jp/all?q=microzoning%20map","dc:title":"microzoning map"},{"@id":"https://cir.nii.ac.jp/all?q=Geography%20(General)","dc:title":"Geography (General)"},{"@id":"https://cir.nii.ac.jp/all?q=soil%20characteristics","dc:title":"soil characteristics"},{"@id":"https://cir.nii.ac.jp/all?q=time-averaged%20shear%20wave%20velocity%20at%2030%20m%20(V%3Csub%3ES30%3C/sub%3E)","dc:title":"time-averaged shear wave velocity at 30 m (V<sub>S30</sub>)"},{"@id":"https://cir.nii.ac.jp/all?q=G1-922","dc:title":"G1-922"},{"@id":"https://cir.nii.ac.jp/all?q=geomorphology%20classification","dc:title":"geomorphology classification"}],"project":[{"@id":"https://cir.nii.ac.jp/crid/1040282256968918784","@type":"Project","projectIdentifier":[{"@type":"KAKEN","@value":"18H00769"},{"@type":"JGN","@value":"JP18H00769"},{"@type":"URI","@value":"https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-18H00769/"}],"notation":[{"@language":"ja","@value":"水文分析と深層学習を加えた全球の地形分類の高度化と構造化"},{"@language":"en","@value":"Advanced and Structured Global Terrain Classification with Hydrological Analysis and Deep Learning"}]}],"relatedProduct":[{"@id":"https://cir.nii.ac.jp/crid/1360009142817776896","@type":"Article","resourceType":"学術雑誌論文(journal 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