| 人机融合智能的遥感解译生产新方法 |
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| 引用本文： | 刘立,董先敏,刘娟,文学虎.人机融合智能的遥感解译生产新方法[J].测绘通报,2022,0(7):118. |
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| 作者姓名： | 刘立 董先敏 刘娟 文学虎 |
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| 作者单位： | 自然资源部第三地理信息制图院, 四川 成都 610100 |
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| 基金项目： | 四川省重点研发计划(2022YFS0450);国家质量基础的共性技术研究与应用(2018YFF0215006);自然资源技术融合研究与应用示范(121204007000204101) |
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| 摘 要： | 以深度学习与测绘生产技术深度融合为基本理念,本文阐述了测绘地理信息技术跨界融合发展给现有遥感解译生产流程带来的变革,分析了现有软硬件环境下智能化生产面临的关键问题,提出了一种人机融合智能的遥感解译生产新方法。该方法突破了多GPU并行训练、滚动反馈训练和分布式微服务应用等多项关键技术,研发出了自然资源深度学习遥感智能解译平台和自然资源深度学习动态解译插件,并在全球地理信息资源建设与维护更新等测绘工程项目中的关键生产环节,进行了规模化的生产应用。经过多个项目实践验证,机器智能与人类智能在遥感解译生产中,通过渐进式人机交互操作进行高效融合,不仅大幅减轻了生产人员工作量,还提升了遥感解译的科学性和时效性,为测绘生产和自然资源调查监测工作提供了强有力的技术支撑。
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| 关 键 词： | 遥感解译 人机融合 深度学习 测绘生产 自然资源调查监测 |
| 收稿时间： | 2021-09-16 |
| 修稿时间： | 2021-12-27 |
A new method of remote sensing interpretation production based on integration of human-machine and intelligence |
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| LIU Li,DONG Xianmin,LIU Juan,WEN Xuehu.A new method of remote sensing interpretation production based on integration of human-machine and intelligence[J].Bulletin of Surveying and Mapping,2022,0(7):118. |
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| Authors: | LIU Li DONG Xianmin LIU Juan WEN Xuehu |
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| Institution: | The Third Geographical Information Mapping Institute of Natural Resources Ministry, Chengdu 610100, China |
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| Abstract: | Based on the basic concept of deep learning and the deep integration of surveying and mapping production technology, this paper explains the changes in the existing remote sensing interpretation production process brought about by the cross-border integration of surveying and mapping geographic information technology, and analyzes the challenges faced by intelligent production in the existing software and hardware environment. A new method of remote sensing interpretation production based on human-computer fusion intelligence is proposed, which breaks through multiple key technologies such as multi-GPU parallel training, rolling feedback training, and distributed micro-service applications, and developed a natural resource deep learning remote sensing intelligent solution. Translation platform and natural resources deep learning dynamic interpretation plug-in, and large-scale production applications have been carried out in key production links of surveying and mapping engineering projects such as the construction, maintenance and update of global geographic information resources. Through multiple projects, it has been verified that machine intelligence and human intelligence can be efficiently integrated through progressive human-computer interaction in remote sensing interpretation production, which greatly reduces the workload of production personnel and improves the scientificity and timeliness of remote sensing interpretation. It provides strong technical support for surveying and mapping production and natural resource survey and monitoring work. |
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| Keywords: | remote sensing interpretation human-machine integration deep learning surveying and mapping production natural resources survey and monitoring |
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