测绘通报 ›› 2024, Vol. 0 ›› Issue (12): 132-136.doi: 10.13474/j.cnki.11-2246.2024.1222

• 技术交流 • 上一篇    下一篇

海岛开发利用遥感智能解译技术研究与应用

谭军辉1, 颜志宇2, 关国翔1, 陈琼1, 刘璐铭3   

  1. 1. 广东绘宇智能科技有限公司, 广东 广州 510665;
    2. 珠海航宇微科技股份有限公司, 广东 珠海 519080;
    3. 珠海欧比特卫星大数据有限公司, 广东 珠海 519085
  • 收稿日期:2024-08-20 发布日期:2024-12-27
  • 通讯作者: 颜志宇,E-mail:176035791@qq.com E-mail:176035791@qq.com
  • 作者简介:谭军辉(1976-),男,高级工程师,主要研究方向为遥感GIS一体化技术。E-mail:47593983@qq.com
  • 基金资助:
    广东省科学技术厅广东省微纳高光谱遥感卫星大数据处理与应用企业重点实验室项目(2023B1212020009)

Research and application of remote sensing intelligent interpretation platform for island development and utilization

TAN Junhui1, YAN Zhiyu2, GUAN Guoxiang1, CHEN Qiong1, LIU Luming3   

  1. 1. Guangdong Huiyu Intelligent Technology Co., Ltd., Guangzhou 510665, China;
    2. Zhuhai Aerospace Micro Technology Co., Ltd., Zhuhai 519080, China;
    3. Zhuhai Obit Satellite Big Data Co., Ltd., Zhuhai 519085, China
  • Received:2024-08-20 Published:2024-12-27

摘要: 本文针对广东省海岛开发利用精细化管理的需求,应用高分辨率卫星遥感影像及无人机影像,结合GIS手段与人工智能技术,开展海岛开发利用遥感智能解译平台研究与应用。通过构建用岛方式智能解译样本库及变化检测样本库,基于深度学习分别训练海岛开发利用遥感智能解译模型和海岛开发利用变化检测模型,对不同时期的遥感数据进行监测分析,输出专题产品及分析报告。研究成果提升了海量遥感数据的自动化处理效率和监测精度,为广东省海域海岛开发利用和保护提供了强有力的技术支撑。

关键词: 海量遥感数据, 算法模型, 智能解译, 样本库, 深度学习

Abstract: In response to the need for refined management of island development and utilization in Guangdong province, the application of high-resolution satellite remote sensing images and unmanned aerial vehicle images, combined with GIS methods and artificial intelligence interpretation technology, has been incorporated to carry out research and application of remote sensing intelligent interpretation platform for island development and utilization. The platform constructs an intelligent interpretation sample library and a change detection sample library based on island-based methods. It trains remote sensing intelligent interpretation models for island development and utilization, as well as change detection models for island development and utilization, using deep learning. By monitoring and analyzing remote sensing data from different periods, the platform outputs thematic products and analysis reports. The research results improve the automated processing efficiency and monitoring accuracy of massive remote sensing data, and provide strong technical support for the development, protection of sea areas and islands in Guangdong province.

Key words: massive remote sensing data, algorithm model, intelligent interpretation, sample library, deep learning

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