Abstract: Remote sensing data as an important spatial data source play an indispensable role in many areas.Promoting by the development of remote sensing information acquiring technology and expanding application fields，remote sensing information extraction method has also gained great achievements.As the continuing increase in artificial intelligence algorithms and successfully applications，the intelligent algorithms are gradually used in remote sensing information extraction for more efficient processing result.After making a thorough study of remote sensing information research advances，this paper analyzs the potential and advantage of swarm intelligent method that can be used in the research field.And applying particle swarm optimization（PSO） algorithm to remote sensing image classification，this paper demonstrates and implements the technical processing steps of remote sensing image classification，and gains ideal results.So，swarm intelligence algorithm can provide a new efficient method for remote sensing information extraction.

Key words: swarm intelligence method, remote sensing data, information extraction

摘要： 遥感数据作为重要的空间数据源，在众多领域发挥着不可或缺的作用。遥感信息获取技术的不断发展与遥感数据应用领域的不断扩展，促进了遥感信息提取方法的不断进步。随着人工智能算法不断被提出及成功应用，遥感信息提取领域也在逐步引入智能算法实现高效的信息提取。在对遥感信息提取方法的研究进展进行深入分析的基础上，剖析了群智能方法应用于遥感信息提取领域的潜力与优势。并应用微粒群优化方法进行遥感数据的分类，实现了微粒群优化方法应用于遥感数据分类的技术流程，取得了很好的实验结果。因此，群智能方法能够为遥感信息提取领域提供一种新的有效智能处理方法。

关键词: 群智能方法, 遥感数据, 信息提取