基于GF-3全极化SAR影像的水域提取与监测分析  被引量:3

Water Area Extraction and Monitoring Analysis Based on GF-3 Fully Polarized SAR Image

在线阅读下载全文

作  者:徐广东 胡兆国[1] 高升[1] 姬晴川 王铭远 张永三[1] XU Guangdong;HU Zhaoguo;GAO Sheng;JI Qingchuan;WANG Mingyuan;ZHANG Yongsan(Geological Exploration Institute of Shandong Zhengyuan,China Metallurgical Geology Bureau,Jinan 250014,China)

机构地区:[1]中国冶金地质总局山东正元地质勘查院,山东济南250014

出  处:《地理空间信息》2023年第6期53-57,共5页Geospatial Information

基  金:中国冶金地质总局山东局青年科技基金资助项目(SDYJ-QNKY202111)。

摘  要:GF-3作为我国首颗高分辨率C波段雷达卫星,能够及时获取高质量的高分辨率遥感影像数据,为充分发掘GF-3全极化SAR影像数据在水域变化分析和应急监测评估中的应用潜力,以龙湖水域为例,基于GF-3全极化影像数据,开展水体面向对象分类、叠置分析等关键问题研究,并提出了一种基于GF-3全极化SAR数据的水域提取与变化检测的方法。结果表明,提出的方法在波浪较大和泥沙混杂的水域表现出良好的适应性,能够做到正确的判识和保留,最终成功获取了两期空间分辨率为8 m的水域分布图,可为进一步推动相关研究及后续应用提供借鉴和参考。As our country’s first high-resolution C-band radar satellite,the GF-3 radar satellite can obtain high-quality high-resolution remote sensing image data in time.In order to fully explore the application potential of GF-3 fully polarized SAR image data in water area change analysis and emergency monitoring and evaluation,taking the waters of Long Lake as the experimental object,based on GF-3 fully polarized SAR image data,we carried out research on key issues such as object-oriented classification and superposition analysis of water bodies,and proposed a water area extraction and change detection method based on GF-3 fully polarized SAR data.The experimental results show that the proposed method has good adaptability in the waters with large waves and mixed sediment,and can correctly identify and retain the water information.Finally,we ob-tained water distribution maps with a spatial resolution of 8 m in the two phases,which could provide a certain degree of reference for further pro-moting related research and practical applications.

关 键 词:高分三号 水域提取 全极化Freeman-Durden分解 面向对象分类 叠置分析 变化检测 

分 类 号:P237[天文地球—摄影测量与遥感]

 

参考文献:

正在载入数据...

 

二级参考文献:

正在载入数据...

 

耦合文献:

正在载入数据...

 

引证文献:

正在载入数据...

 

二级引证文献:

正在载入数据...

 

同被引文献:

正在载入数据...

 

相关期刊文献:

正在载入数据...

相关的主题
相关的作者对象
相关的机构对象