测绘通报 ›› 2018, Vol. 0 ›› Issue (8): 62-67.doi: 10.13474/j.cnki.11-2246.2018.0246

• 学术研究 • 上一篇    下一篇

利用Google Earth和SRTMGL1进行高分辨率遥感影像正射校正

徐鑫1, 张道军1, 侯现慧1, 马晓燕2, 汪静2   

  1. 1. 西北农林科技大学经济管理学院, 陕西 杨凌 712100;
    2. 青海省土地统征整理中心, 青海 西宁 810001
  • 收稿日期:2018-03-20 出版日期:2018-08-25 发布日期:2018-08-30
  • 通讯作者: 张道军。E-mail:cugzdj@gmail.com E-mail:cugzdj@gmail.com
  • 作者简介:徐鑫(1996-),女,研究方向为土地调查与评价。E-mail:xuxin4572@163.com
  • 基金资助:
    国家自然科学基金(41602336);林业公益性行业科研专项(201504424);中国博士后基金(2017T100773);陕西省自然科学基金(2017JQ7010);西北农林科技大学基本科研基金(2017RWYB08)

Orthorectification of High-resolution Remote Sensing Image Based on Google Earth and SRTMGL1

XU Xin1, ZHANG Daojun1, HOU Xianhui1, MA Xiaoyan2, WANG Jing2   

  1. 1. College of Economics and Management, Northwest A & F University, Yangling 712100, China;
    2. Land Acquisition and Consolidation Center of Qinhai, Xining 810001, China
  • Received:2018-03-20 Online:2018-08-25 Published:2018-08-30

摘要: 在无实测地面控制点情况下,本文提出了一套基于Google Earth和SRTMGL1的遥感影像正射校正流程。首先在ENVI5.3中,将待校正影像与参考影像(即Google Earth影像)进行同名地物点自动匹配,获得同名点文件(PTS);然后在ArcGIS 10.2平台下,根据参考点的X、Y坐标,将校正控制点表数据转换为ArcGIS点文件(SHP);最后将该点文件与SRTMGL1高程数据进行空间叠加,获得高程值,得到带有高程值的地面控制点文件,进而进行有控制点的正射校正。相较于无控制点的正射校正,本研究所采用的处理流程可以有效提高校正精度,为后续影像镶嵌奠定良好基础;镶嵌中误差为2.13.m,可满足1∶5000土地利用现状调查的技术要求。

关键词: Google Earth影像, SRTMGL1, 正射校正, 精度评价, 土地调查

Abstract: An orthorectified image correction process was proposed in this study based on Google Earth and SRTMGL1 data to address the absence of measured ground control points.Firstly,homonymous point auto-matching was performed between the warp image and the reference image (Google Earth image) in ENVI 5.3 to obtain a horizontal control point file (PTS).Secondly,under the ArcGIS 10.2 platform,Converting the corrected control point data to ArcGIS point file(SHP)according to the X and Y coordinates of the reference points.Finally,the shapefile data was added with elevation values through overlaying with the SRTMGL1,which made it possible to perform orthorectification with ground control points.Compared with the orthorectification without ground control points,the processing flow adopted in this research can effectively improve the accuracy of image correction and lay a good foundation for the subsequent image mosaic.The root mean square error for image is 2.13.m,which meets the technical standard of 1/5000 scale land use investigation.

Key words: Google Earth image, SRTMGL1, orthorectification, accuracy evaluation, land surveying

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