Spectral Characteristics and Identification of Degraded Alpine Meadow in Qinghai-Tibetan Plateau Based on Hyperspectral Data

NWIPB OpenIR

	Spectral Characteristics and Identification of Degraded Alpine Meadow in Qinghai-Tibetan Plateau Based on Hyperspectral Data
	Qian, Dawen; Li, Qian; Fan, Bo; Zhou, Huakun; Du, Yangong; Guo, Xiaowei
	2024
发表期刊	REMOTE SENSING
卷号	16 期号:20
摘要	Grassland degradation poses a significant challenge to achieving the Sustainable Development Goals (SDGs) on the Qinghai-Tibetan Plateau (QTP). Effective monitoring of grassland degradation is essential for ecological restoration. Hyperspectral technology offers efficient and accurate identification of degradation. However, the influence of observation time, data analysis methods and classification techniques on the accuracy of identifying alpine grasslands remains unclear. In this study, the spectral reflectance of degraded alpine meadow, alpine meadow, alpine shrub and Tibetan barley was measured from May to September 2023 using a ground spectrometer in the northeastern QTP. First-order derivatives (FDR) and continuum removal were applied to the spectra, and characteristic parameters and vegetation indices were calculated. Support vector machine (SVM), random forest (RF), artificial neural network (ANN) and decision tree (DT) were then used to compare the classification accuracy between different months, transformation methods and characteristic parameters. The results showed that the spectral reflectance peaked in July, with significant differences in the near infrared (NIR) bands between alpine meadow and degraded alpine meadow. Alpine shrub and Tibetan barley showed greater differences in reflectance compared to other vegetation types, especially in the NIR bands. Data transformations improved reflectance and absorption characteristics in the NIR and visible bands. Indices such as DVI, RVI and NDGI effectively differentiated vegetation types. Optimal accuracy for the identification of degraded alpine meadow in July was achieved using FDR transformations and ANN or SVM for classification. This study provides methodological insights for monitoring grassland degradation on the QTP.
收录类别	SCIE
文献类型	期刊论文
条目标识符	http://210.75.249.4/handle/363003/61939
专题	中国科学院西北高原生物研究所
推荐引用方式 GB/T 7714	Qian, Dawen,Li, Qian,Fan, Bo,et al. Spectral Characteristics and Identification of Degraded Alpine Meadow in Qinghai-Tibetan Plateau Based on Hyperspectral Data[J]. REMOTE SENSING,2024,16(20).
APA	Qian, Dawen,Li, Qian,Fan, Bo,Zhou, Huakun,Du, Yangong,&Guo, Xiaowei.(2024).Spectral Characteristics and Identification of Degraded Alpine Meadow in Qinghai-Tibetan Plateau Based on Hyperspectral Data.REMOTE SENSING,16(20).
MLA	Qian, Dawen,et al."Spectral Characteristics and Identification of Degraded Alpine Meadow in Qinghai-Tibetan Plateau Based on Hyperspectral Data".REMOTE SENSING 16.20(2024).