Identification of vegetation under natural gas leakage by spectral index based on feature selection

ABSTRACT

The leakage of natural gas storage has a significant impact on economy, personal safety and natural environment. When the leakage is slight, the effect of direct detection is not ideal. Hyperspectral remote sensing can detect it indirectly through the spectral changes of surface vegetation. In this study, wheat, bean and grass were used as surface experimental objects to analyse the variation characteristics of canopy spectrum and physiological and biochemical parameters of vegetation under natural gas leakage. The results showed that with the increase of natural gas concentration in the soil, the spectral reflectance of vegetation increased significantly in the visible region, and decreased significantly in the near infrared region. The natural gas identification index (NGII) $(R_{622}-R_{532})/(R_{622}+R_{532})$ was constructed according the optimal weight index screened by Relief-F algorithm. The quantitative test by Jeffries-Matusita (JM) distance showed that NGII can identify (JM > 1.8) stressed vegetation under natural gas leakage in a short time. This study can provide technical reference for detecting leakage of underground natural gas storage.

KEYWORDS:

• Natural gas leakage
• hyperspectral
• relief-F
• vegetation index

Disclosure statement

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

Additional information

Funding

The National Natural Science Foundation of China (41871341, 41571412) supported this work