Geospatial foundation models for image analysis: evaluating and enhancing NASA-IBM Prithvi’s domain adaptability

IF 4.3 1区地球科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS

International Journal of Geographical Information Science Pub Date : 2024-08-30 DOI:10.1080/13658816.2024.2397441

Chia-Yu Hsu, Wenwen Li, Sizhe Wang

引用次数: 0

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...

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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

地理空间基础模型（GFMs）研究已成为地理空间人工智能（AI）研究中的一个热门话题，因为它们具有实现高度泛化和领域化的潜力。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of Geographical Information Science 地学-计算机：信息系统

CiteScore

11.00

自引率

7.00%

发文量

审稿时长

9 months

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.