IMHE OpenIR  > 山地表生过程与生态调控重点实验室
Study of vegetation spectral anomaly behaviour in a porphyry copper mine area based on hyperspectral indices
He, Li1,2; Li, Ainong1; Nan, Xi1,3
Corresponding AuthorLi, Ainong(ainongli@imde.ac.cn)
2019-08-17
Source PublicationINTERNATIONAL JOURNAL OF REMOTE SENSING
ISSN0143-1161
EISSN1366-5901
Pages18
SubtypeArticle
AbstractHyperspectral 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.
DOI10.1080/01431161.2019.1651949
Indexed BySCI
WOS KeywordPLANT-LEAVES ; WATER INDEX ; REFLECTANCE ; METAL ; NITROGEN ; STRESS ; WHEAT
Language英语
Quartile3区
TOP
WOS Research AreaRemote Sensing ; Imaging Science & Photographic Technology
WOS SubjectRemote Sensing ; Imaging Science & Photographic Technology
WOS IDWOS:000481643400001
PublisherTAYLOR & FRANCIS LTD
Citation statistics
Document Type期刊论文
Identifierhttp://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 AuthorLi, Ainong
Affiliation1.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.
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