{"title":"用于图像分析的地理空间基础模型：评估和增强 NASA-IBM Prithvi 的领域适应性","authors":"Chia-Yu Hsu, Wenwen Li, Sizhe Wang","doi":"10.1080/13658816.2024.2397441","DOIUrl":null,"url":null,"abstract":"Research on geospatial foundation models (GFMs) has become a trending topic in geospatial artificial intelligence (AI) research due to their potential for achieving high generalizability and domain...","PeriodicalId":14162,"journal":{"name":"International Journal of Geographical Information Science","volume":null,"pages":null},"PeriodicalIF":4.3000,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Geospatial foundation models for image analysis: evaluating and enhancing NASA-IBM Prithvi’s domain adaptability\",\"authors\":\"Chia-Yu Hsu, Wenwen Li, Sizhe Wang\",\"doi\":\"10.1080/13658816.2024.2397441\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Research on geospatial foundation models (GFMs) has become a trending topic in geospatial artificial intelligence (AI) research due to their potential for achieving high generalizability and domain...\",\"PeriodicalId\":14162,\"journal\":{\"name\":\"International Journal of Geographical Information Science\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.3000,\"publicationDate\":\"2024-08-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Geographical Information Science\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://doi.org/10.1080/13658816.2024.2397441\",\"RegionNum\":1,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Geographical Information Science","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1080/13658816.2024.2397441","RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
Geospatial foundation models for image analysis: evaluating and enhancing NASA-IBM Prithvi’s domain adaptability
Research on geospatial foundation models (GFMs) has become a trending topic in geospatial artificial intelligence (AI) research due to their potential for achieving high generalizability and domain...
期刊介绍：
International Journal of Geographical Information Science provides a forum for the exchange of original ideas, approaches, methods and experiences in the rapidly growing field of geographical information science (GIScience). It is intended to interest those who research fundamental and computational issues of geographic information, as well as issues related to the design, implementation and use of geographical information for monitoring, prediction and decision making. Published research covers innovations in GIScience and novel applications of GIScience in natural resources, social systems and the built environment, as well as relevant developments in computer science, cartography, surveying, geography and engineering in both developed and developing countries.
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