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Spectroscopy Letters
An International Journal for Rapid Communication
Volume 56, 2023 - Issue 6
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Research Articles

Spectral characteristics analysis of typical ground objects in Poyang Lake wetland based on “Zhuhai-1” hyperspectral data

ORCID Icon, , , &
Pages 293-308 | Received 16 Dec 2022, Accepted 21 Apr 2023, Published online: 11 May 2023
 

Abstract

Hyperspectral image data provides new ideas and methods for the fine classification of wetland. Research on wetland spectral characteristics lays the foundation for wetland classification and improves classification accuracy. Based on “Zhuhai-1” hyperspectral image data, combined with the Pure Pixel Index (PPI), this paper extracted the average spectral curves of 11 typical ground objects in Poyang Lake wetland. Two mathematical transformation methods, namely, the continuum removal and the first derivative, were used to analyze the spectral characteristics of the ground objects before and after transformation, in combination with spectral characteristic parameters. The method of combining the mean distance of ground objects with the range of data error was used to select characteristic wavelengths before and after spectral transformation. Finally, the Mahalanobis distance method was used to verify the recognition effect. The results demonstrate that: (1) Spectral transformation can effectively amplify the differences between ground objects. The continuum removal led to an increase in the characteristic bands of four types of vegetation and the emergence of characteristic bands of four types of other ground objects. The first derivative method extended the characteristic bands of four vegetation from red-edge to near-infrared. (2) The method of combining the mean distance and the data error range can effectively screened out the spectral characteristic bands of typical ground objects in Poyang Lake wetland, resulting in hyperspectral dimensionality reduction. (3) The Mahalanobis distance method validates the recognition effect of the characteristic bands. In the screened characteristic bands, the Mahalanobis distance between different ground objects is larger than that between the same ground object, except between shoaly land and road. This study offers valuable insights into spectral recognition and classification of freshwater lake wetlands, and also demonstrates the potential of “Zhuhai-1” hyperspectral image data in wetland research.

Acknowledgments

The authors thank Zhuhai Orbita Aerospace Science & Technology Co., Ltd. for providing “Zhuhai-1” hyperspectral remote sensing satellite data.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by the National Natural Science Foundation of China under Grant [41101322]; Science and Technology Research Project of the Education Department of Jiangxi Province under Grant [GJJ160617].

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