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Reconstructing High-Precision Coral Reef Geomorphology from Active Remote Sensing Datasets: A Robust Spatial Variability Modified Ordinary Kriging Method

文献类型：期刊论文

作者Wang, Qi1; Xiao, Han4; Wu, Wenzhou2; Su, Fenzhen2; Zuo, Xiuling3; Yao, Guobiao1; Zheng, Guoqiang1
刊名REMOTE SENSING
出版日期2022
卷号14期号:2页码:19
关键词coral reefs geomorphological reconstruction active remote sensing data surface modeling spatial variability modification
DOI10.3390/rs14020253
通讯作者Su, Fenzhen(sufz@lreis.ac.cn)
英文摘要Active remote sensing technology represented by multi-beam and lidar provides an important approach for the effective acquisition of underwater coral reef geomorphological information. A spatially continuous surface model of coral reef geomorphology reconstructed from active remote sensing datasets can provide important geomorphological parameters for the research of coral reef geomorphological and ecological changes. However, the surface modeling methods commonly used in previous studies, such as ordinary kriging (OK) and natural neighborhood (NN), often represent a "smoothing effect", which causes the strong spatial variability of coral reefs to be imprecisely reflected by the reconstructed surfaces, thus affecting the accurate calculation of subsequent geomorphological parameters. In this study, a spatial variability modified OK (OK-SVM) method is proposed to reduce the impact of the "smoothing effect" on the high-precision reconstruction of the complex geomorphology of coral reefs. The OK-SVM adopts a collaborative strategy of global parameter transformation, local residual correction, and extremum correction to modify the spatial variability of the reconstructed model, while maintaining high local accuracy. The experimental results show that the OK-SVM has strong robustness to spatial variability modification. This method was applied to the geomorphological reconstruction of the northern area of a coral atoll in the Nansha Islands, South China Sea, and the performance was compared with that of OK and NN. The results show that OK-SVM has higher numerical accuracy and attribute accuracy in detailed morphological fidelity, and is more adaptable in the geomorphological reconstruction of coral reefs with strong spatial variability. This method is relatively reliable for achieving high-precision reconstruction of complex geomorphology of coral reefs from active remote sensing datasets, and has potential to be extended to other geomorphological reconstruction applications.
WOS关键词HABITAT COMPLEXITY ; ISLAND ; LIDAR ; NEARSHORE ; IMPACTS
资助项目Key Program of Frontier Science of Chinese Academy of Sciences[QYZDY-SSW-DQC019] ; Ph.D. Programs Foundation of Shandong Jianzhu University[XNBS1984] ; National Natural Science Foundation of China[42171435] ; Shandong Provincial Natural Science Foundation[ZR2021DQ021]
WOS研究方向Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology
语种英语
出版者MDPI
WOS记录号WOS:000758055900001
资助机构Key Program of Frontier Science of Chinese Academy of Sciences ; Ph.D. Programs Foundation of Shandong Jianzhu University ; National Natural Science Foundation of China ; Shandong Provincial Natural Science Foundation
源URL[http://ir.igsnrr.ac.cn/handle/311030/171276]  
专题中国科学院地理科学与资源研究所
通讯作者Su, Fenzhen
作者单位1.Shandong Jianzhu Univ, Sch Surveying & Geoinformat, Jinan 250101, Peoples R China
2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China
3.Guangxi Univ, Guangxi Lab Study Coral Reefs South China Sea, Nanning 530004, Peoples R China
4.Minist Agr & Rural Affairs, Acad Agr Planning & Engn, Beijing 100125, Peoples R China
推荐引用方式
GB/T 7714		 Wang, Qi,Xiao, Han,Wu, Wenzhou,et al. Reconstructing High-Precision Coral Reef Geomorphology from Active Remote Sensing Datasets: A Robust Spatial Variability Modified Ordinary Kriging Method[J]. REMOTE SENSING,2022,14(2):19.
APA Wang, Qi.,Xiao, Han.,Wu, Wenzhou.,Su, Fenzhen.,Zuo, Xiuling.,...&Zheng, Guoqiang.(2022).Reconstructing High-Precision Coral Reef Geomorphology from Active Remote Sensing Datasets: A Robust Spatial Variability Modified Ordinary Kriging Method.REMOTE SENSING,14(2),19.
MLA Wang, Qi,et al."Reconstructing High-Precision Coral Reef Geomorphology from Active Remote Sensing Datasets: A Robust Spatial Variability Modified Ordinary Kriging Method".REMOTE SENSING 14.2(2022):19.

入库方式： OAI收割

来源：地理科学与资源研究所

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