| 姚宏岗.不同植被覆盖区无人机遥感影像矿化蚀变特征识别[J].矿产勘查,2023,14(2):229-236 |
| 不同植被覆盖区无人机遥感影像矿化蚀变特征识别 |
| Recognition of mineralization and alteration characteristics of UAV remote sensing images in different vegetation coverage areas |
| 投稿时间：2022-01-24 |
| DOI：10.20008/j.kckc.202302008 |
| 中文关键词: 植被覆盖度 矿化蚀变特征 无人机遥感影像 几何纠正 混合像元分解 主成分分析 |
| 英文关键词: vegetation coverage mineralization alteration characteristics uav remote sensing image geometric correction mixed pixel decomposition principal component analysis |
| 基金项目:本文受中国地质调查局地质调查项目(12120113061400)及河南省两权价款地质科研项目(豫国土函[2015]258号,04)联合资助。 |
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| 中文摘要: |
| 为了提升不同植被覆盖区矿化蚀变特征的识别效果,本文旨在研究不同植被覆盖区无人机遥感影像矿化蚀变特征识别技术。通过几何纠正与辐射纠正预处理无人机遥感影像；利用混合像元分解法提取预处理后遥感影像内的干扰端元,去掉干扰端元后,重建遥感图像光谱,降低植被覆盖度对矿化蚀变特征识别的影响；通过主成分分析法提取光谱重建后遥感图像内的矿化蚀变特征分量,完成矿化蚀变特征识别。实验证明该方法可有效提取干扰端元,重建的遥感图像光谱相关系数在0.91~1.00之间,ERGAD值在0~2.7之间,重建质量较佳。同时该方法可精准识别不同植被覆盖度时的矿化蚀变特征,提升矿化蚀变特征的识别效果。 |
| 英文摘要: |
| In order to improve the recognition effect of mineralization and alteration features in different vegetation coverage areas, this paper studies the recognition technology of mineralization and alteration features in UAV remote sensing images in different vegetation coverage areas. The UAV remote sensing image is preprocessed by geometric correction and radiation correction; The mixed pixel decomposition method is used to extract the interfering end elements in the pre processed remote sensing image. After removing the interfering end elements, the remote sensing image spectrum is reconstructed to reduce the impact of vegetation coverage on the recognition of mineralization alteration features; The feature components of mineralization and alteration in the remote sensing image after spectral reconstruction are extracted by principal component analysis to complete the recognition of mineralization and alteration features. The experiment shows that this method can effectively extract the interfering end elements, the spectral correlation coefficient of the reconstructed remote sensing image is 0.91 to 1.00, and the ERGAD value is 0 to 2.7, so the reconstruction quality is better. At the same time, this method can accurately identify the characteristics of mineralization and alteration under different vegetation coverage, and improve the recognition effect of mineralization and alteration characteristics. |
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