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Response of plant reflectance spectrum to simulated dust deposition and its estimation model

Authors :
Weijun He
Ruirui Wang
Xinna Zhang
Xuemei Yan
Qiang Yu
Chengyang Xu
Huaguo Huang
Qun’ou Jiang
Jiyou Zhu
Source :
Scientific Reports, Vol 10, Iss 1, Pp 1-12 (2020), Scientific Reports
Publication Year :
2020
Publisher :
Nature Publishing Group, 2020.

Abstract

To quantitatively reflect the relationship between dust and plant spectral reflectance. Dust from different sources in the city were selected to simulate the spectral characteristics of leaf dust. Taking Euonymus japonicus as the research object. Prediction model of leaf dust deposition was established based on spectral parameters. Results showed that among the three different dust pollutants, the reflection spectrum has 6 main reflection peaks and 7 main absorption valleys in 350–2500 nm. A steep reflection platform appears in the 692–763 nm band. In 760–1400 nm, the spectral reflectance gradually decreases with the increase of leaf dust coverage, and the variation range was coal dust > cement dust > pure soil dust. The spectral reflectance in 680–740 nm gradually decreases with the increase of leaf dust coverage. In the near infrared band, the fluctuation amplitude and slope of its first derivative spectrum gradually decrease with the increase of leaf dust. The biggest amplitude of variation was cement dust. With the increase of dust retention, the red edge position generally moves towards short wave direction, and the red edge slope generally decreases. The blue edge position moved to the short wave direction first and then to the long side direction, while the blue edge slope generally shows a decreasing trend. The yellow edge position moved to the long wave direction first and then to the short wave direction (coal dust, cement dust), and generally moved to the long side direction (pure soil dust). The yellow edge slope increases first and then decreases. The R2 values of the determination coefficients of the dust deposition prediction model have reached significant levels, which indicated that there was a relatively stable correlation between the spectral reflectance and dust deposition. The best prediction model of leaf dust deposition was leaf water content index model (y = 1.5019x − 1.4791, R2 = 0.7091, RMSE = 0.9725).

Details

Language :
English
ISSN :
20452322
Volume :
10
Issue :
1
Database :
OpenAIRE
Journal :
Scientific Reports
Accession number :
edsair.doi.dedup.....2a6f3ff476861aa904a4de72dabedb1d