| Study of vegetation spectral anomaly behaviour in a porphyry copper mine area based on hyperspectral indices | |
He, Li1,2; Li, Ainong1 ; Nan, Xi1,3
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| Corresponding Author | Li, Ainong(ainongli@imde.ac.cn) |
| 2019-08-17 | |
| Source Publication | INTERNATIONAL JOURNAL OF REMOTE SENSING
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| ISSN | 0143-1161 |
| Pages | 18 |
| Abstract | Hyperspectral remote sensing is economical and fast, and it can reveal detailed spectral information of plants. Hence, hyperspectral data are used in this study to analyse the spectral anomaly behaviours of vegetation in porphyry copper mine areas. This analytical method is used to compare the leaf spectra and relative differences among the vegetation indices; then, the correlation coefficients were computed between the soil copper content and vegetation index of Quercus spinosa leaves at both the leaf scale and the canopy scale in the Chundu mine area with different geological backgrounds. Lastly, this study adopts hyperspectral data for the level slicing of vegetation anomalies in the Chundu mine area. The results showed that leaf spectra in the orebody and background area differed greatly, especially in the infrared band (750 nm - 1300 nm); moreover, some indices like the normalized water index (NWI) and normalized difference water index (NDWI) of Quercus spinosa and Lamellosa leaves are sensitive to changes in the geological background. Compared with the canopy, the leaf hyperspectral indices of Quercus spinosa in Chundu can better reflect soil cuprum (Cu) anomaly. In addition, the NWI and NDWI of Quercus spinosa are significantly correlated with the soil Cu content at both the canopy scale and the leaf scale. Consequently, the results of the vegetation anomaly level slicing can adequately reflect the plant anomalies from ore bodies and nearby areas, thereby providing a new ore-finding method for areas with a high degree of vegetation coverage. |
| DOI | 10.1080/01431161.2019.1651949 |
| Indexed By | SCI |
| WOS Keyword | PLANT-LEAVES ; WATER INDEX ; REFLECTANCE ; METAL ; NITROGEN ; STRESS ; WHEAT |
| Language | 英语 |
| WOS Research Area | Remote Sensing ; Imaging Science & Photographic Technology |
| WOS Subject | Remote Sensing ; Imaging Science & Photographic Technology |
| WOS ID | WOS:000481643400001 |
| Publisher | TAYLOR & FRANCIS LTD |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.imde.ac.cn/handle/131551/26962 |
| Collection | 山地表生过程与生态调控重点实验室 数字山地与遥感应用中心 |
| Corresponding Author | Li, Ainong |
| Affiliation | 1.Chinese Acad Sci, Inst Mt Hazards & Environm, Res Ctr Digital Mt & Remote Sensing Applicat, Chengdu 610041, Sichuan, Peoples R China 2.Univ Chinese Acad Sci, Beijing, Peoples R China 3.Chengdu Univ Technol, Coll Earth Sci, Chengdu, Sichuan, Peoples R China |
| First Author Affilication | 中国科学院水利部成都山地灾害与环境研究所 |
| Corresponding Author Affilication | 中国科学院水利部成都山地灾害与环境研究所 |
| Recommended Citation GB/T 7714 | He, Li,Li, Ainong,Nan, Xi. Study of vegetation spectral anomaly behaviour in a porphyry copper mine area based on hyperspectral indices[J]. INTERNATIONAL JOURNAL OF REMOTE SENSING,2019:18. |
| APA | He, Li,Li, Ainong,&Nan, Xi.(2019).Study of vegetation spectral anomaly behaviour in a porphyry copper mine area based on hyperspectral indices.INTERNATIONAL JOURNAL OF REMOTE SENSING,18. |
| MLA | He, Li,et al."Study of vegetation spectral anomaly behaviour in a porphyry copper mine area based on hyperspectral indices".INTERNATIONAL JOURNAL OF REMOTE SENSING (2019):18. |
| Files in This Item: | ||||||
| File Name/Size | DocType | Version | Access | License | ||
| Study of vegetation （2330KB） | 期刊论文 | 出版稿 | 开放获取 | CC BY-NC-SA | View Application Full Text | |
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