地球信息科学学报 ›› 2018, Vol. 20 ›› Issue (7): 895-905.doi: 10.12082/dqxxkx.2018.170554
孟伟1(), 李润奎1,2, 段峥3, 徐江4, 宋现锋1,2,*(
)
收稿日期:
2017-11-21
修回日期:
2018-02-06
出版日期:
2018-07-20
发布日期:
2018-07-13
通讯作者:
宋现锋
E-mail:18811152566@163.com;xfsong@ucas.ac.cn
作者简介:
作者简介:孟 伟(1994-),男,硕士生,研究方向为空间数据挖掘。E-mail:
基金资助:
MENG Wei1(), LI Runkui1,2, DUAN Zheng3, XU Jiang4, SONG Xianfeng1,2,*(
)
Received:
2017-11-21
Revised:
2018-02-06
Online:
2018-07-20
Published:
2018-07-13
Contact:
SONG Xianfeng
E-mail:18811152566@163.com;xfsong@ucas.ac.cn
Supported by:
摘要:
数字高程模型(Digital Elevation Model, DEM)是一种至关重要的空间信息,广泛应用于各行各业。其中,ASTER GDEM与SRTM几乎覆盖了全球陆域,为地学研究提供了非常实用的高程数据支撑,但是由于二者传感器采集数据原理的不同,使得高程数据在不同地貌条件下的高程精度亦存在程度不一的误差。本文提出了一种新型的基于地貌特征的DEM融合方法,使得融合GDEM与SRTM后的DEM数据,消除了地貌特征的影响、显著地提高了DEM质量。该方法主要分为地理配准和高程融合2个步骤:①基于河流线对等线性地貌特征的位置数据,构建了GDEM与SRTM的水平偏移相关的误差评价函数,采用多级网格搜索法求得DEM间的水平偏移距离,实现对DEM的配准;②按照DEM高程值在不同地貌单元及边界线附近的高程变化特征,建立地貌分区的高程融合模型来融合两种地理配准后的DEM高程,尤其是实现了地貌单元边界线附近的高程平滑过渡。本文以怀柔北部地区为实验区,以1:5万地形图为参考,对2种DEM数据进行融合,统计结果表明:① 融合DEM在各地貌单元的误差均显著下降,地形表达较之融合前更加精确;② 高程差呈现正态分布,明显区别于融合前DEM不对称的多峰分布形态,说明地貌影响被有效地剔除;③ GDEM和SRTM数据的精度对坡度有较大依赖性,融合后DEM的精度在不同坡度范围下均优于GDEM和SRTM,显著降低了融合前DEM对坡度的依赖程度;④ 在不同坡向下,GDEM和SRTM的RMSE取值波动较大,融合DEM的RMSE取值在各方向表现稳定,高程精度较GDEM和SRTM有显著提高。
孟伟, 李润奎, 段峥, 徐江, 宋现锋. 基于地貌特征的数字高程模型融合方法[J]. 地球信息科学学报, 2018, 20(7): 895-905.DOI:10.12082/dqxxkx.2018.170554
MENG Wei,LI Runkui,DUAN Zheng,XU Jiang,SONG Xianfeng. Digital Elevation Model Fusion by Landform Characteristics[J]. Journal of Geo-information Science, 2018, 20(7): 895-905.DOI:10.12082/dqxxkx.2018.170554
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