文献类型：期刊文献

中文题名：Forest Height Extraction Using GF-7 Very High-Resolution Stereoscopic Imagery and Google Earth Multi-Temporal Historical Imagery

作者：Wenjian Ni[1,2] Zijia Li[1,2] Qiang Wang[3] Zhiyu Zhang[1] Qingwang Liu[4] Yong Pang[4] Yating He[5] Zengyuan Li[4] Guoqing Sun[6]

第一作者：Wenjian Ni

机构：[1]State Key Laboratory of Remote Sensing Science,Aerospace Information Research Institute,Chinese Academy of Sciences,Beijing 100101,China;[2]University of Chinese Academy of Sciences,Beijing 100049,China;[3]Department of Surveying Engineering,Heilongjiang Institute of Technology,Harbin 150040,China;[4]Research Institute of Forest Resource Information Techniques,Chinese Academy of Forestry,Beijing 100091,China;[5]Research Institute of Forest Policy and Information,Chinese Academy of Forestry,Beijing 100091,China;[6]Department of Geographical Sciences,University of Maryland,College Park,MD 20742,USA

年份：2024

卷号：4

期号：1

起止页码：344-355

中文期刊名：Journal of Remote Sensing

外文期刊名：国际遥感学报(英文)

基金：sponsored by the National Natural Science Foundation of China(Grant Nos.42022009 and 42090013);the National Key Research and Development Program of China(2020YFE0200800).

语种：英文

中文关键词：forest height extraction;regional applications;very high resolution imagery;ground control points gcps collecting;forest stands;multi temporal imagery;stereoscopic imagery;geometric processing;

分类号：S771.8

摘要：With the advent of very high-resolution(VHR)imaging satellites,it is possible to measure the heights of forest stands or even individual trees more accurately.However,the accurate geometric processing of VHR images depends on ground control points(GCPs).Collecting GCPs through fieldwork is time-consuming and labor-intensive,which presents great challenges for regional applications in remote or mountainous regions,particularly for international applications.This study proposes a promising approach that leverages GF-7 VHR stereoscopic images and Google Earth’s multi-temporal historical imagery to accurately extract forest heights without the need for fieldworks.Firstly,an algorithm is proposed to collect GCPs using Multi-temporal Averaging of historical imagery provided by Google Earth(GE),known as MAGE.Digital surface model(DSM)is then derived using GF-7 stereoscopic imagery and MAGE GCPs in Switzerland.Forest heights are finally extracted by subtracting ground surface elevations from GF-7 DSM.Results show that absolute coordinate errors of MAGE GCPs are less than 2.0 m.The root mean square error(RMSE)of forest heights extracted from GF-7 DSM,derived using the original geolocation model,is 12.3 m,and the determination coefficient(R^(2))of linear estimation model is 0.72.When the geolocation model is optimized using MAGE GCPs,the RMSE is reduced to 1.5 m and the R^(2)increases to 0.95.These results not only demonstrate the effectiveness of MAGE GCPs but,more importantly,also reveal the significance of precise geometric processing of VHR stereoscopic imagery in forest height estimations.