不同地形校正方法对黑松分布遥感提取的影响
收稿日期: 2018-09-03
修回日期: 2018-10-22
网络出版日期: 2020-09-27
基金资助
国家重点研发计划(2016YFC0501601)
Effects of Different Topographic Correction Methods on the Distribution Extraction of Pinus thunbergii Using Remote Sensing Imagery
Received date: 2018-09-03
Revised date: 2018-10-22
Online published: 2020-09-27
以青岛黄岛区为研究区,利用资源三号卫星立体像对提取精细的DEM(Digital Elevation Model),使用5种地形校正模型(Teillet-回归,VECA,Cosine-C,C和SCS+C)对Quick Bird多光谱影像进行地形校正,并结合面向对象方法提取得到山区黑松的空间分布信息。结果表明:5种模型中,Quick Bird影像经VECA,SCS+C,C校正模型校正后山区阴影有较好的减弱效果,且山区黑松分布提取的精度均有所提高,其中以VECA模型的提取精度最佳,提取精度从70.25%提高到84.30%,提高了14.05%;Kappa系数从0.53提高到0.72,提高了0.19。本研究可为光学高分遥感影像在山区松树的分布提取上提供参考。
关键词： 地形校正; 数字高程模型; 黑松; 资源三号; Quick Bird影像
邓世晴 , 陶欢 , 李存军 , 刘荣 , 胡海棠 . 不同地形校正方法对黑松分布遥感提取的影响[J]. 林草资源研究, 2018 , 0(6) : 138 -145 . DOI: 10.13466/j.cnki.lyzygl.2018.06.022
Five topographic correction models (Teillet-regression,VECA,Cosine-C,C,and SCS+C) were employed in the present study in Huangdao,Qingdao to calibrate the Quick-Bird multispectral images combining with fine Digital Elevation Model (DEM) generated by stereo images of domestic ZY-3 satellite.Then,we examined and compared the results of 5 models to evaluate the effects of different topographic correction models on extracting the distribution of pine.The results show that Quick-Bird images corrected by a combination of 2m DEM and 3 models (VECA,C and SCS+C) can better maintain imagery’s spectral characteristic and weaken the effect of mountain shadows than the other 2.Quick-Bird images calibrated by these 3 models have significantly improved the extraction accuracy of Pinus thunbergii.Among these 3 models,VECA is the best one for its elevation of the overall accuracy by 14.05% (from 70.25% to 84.30%) and the Kappa coefficient by 0.19 (from 0.53 to 0.72).This research can provide a reference for the extraction of Pinus thunbergii distribution by using remote sensing imagery.
Key words： topographic correction; Digital Elevation Model (DEM); pine tree; ZY-3; Quick Bird
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