基于光谱特征的北京市冬季城市森林滞尘分布反演研究

doi:10.3964/j.issn.1000-0593(2020)06-1696-07

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Abstract Urban forests affect the filtration and adsorption of airborne particulate matter, which can minimize the harmful effects on human health caused by airborne particulate pollution. Evergreen plants in urban forests play a major role in absorbing dust and purifying the air, especially in winter. In this study, Euonymus japonicus, the main evergreen vegetation in winter in Beijing, was used as the research object. Three types of sampling space were set up, and 1 410 leaves were collected to measure the hyperspectral data before and after cleaning and the amount of dust absorption (ADA) on the surface of the leaf. The sensitive band was determined by analyzing the response of spectral reflectance to the amount of dust retention, and the regression model was established between the vegetation index ratio and ADA before and after cleaning. The Sentinel-2 remote sensing image was used to obtain the dust distribution of the evergreen vegetation, and the inversion results were verified. The result showed that in the range of 510～700 and 758～1 480 nm, the average spectral reflectance of the blade before dust removal is less than that of the clean blade. The change of average spectral reflectance before and after cleaning in the closed zone is less than that in the semi-closed zone, and the change in the open zone is the largest. And the red band and nearinfrared band are most sensitive to dust. The inversion model established using the Normalized Difference Phenology Index (NDPI) is: x=0.939 69y^{-0.145 04}(x represents the value of R_NDPI, and y represents the amount of dust retention), and the determination coefficient (R²) reached 0.879. The inversion results show that the mean ADA in the enclosed area is smaller than that in semi-enclosed and open areas, and the regional distribution of high ADA in the urban area of Beijing was higher in the south with a tendency of the ADA to decrease from city centre to the surrounding area. Study the spatial distribution of leaf dust retention and provide a reference for rapid monitoring of dust pollution intensity and distribution in urban areas, and exploring the dust retention effect of evergreen shrubs are important for scientifically guiding urban forest construction and improving the living environment of cities in winter.

Key words：Remote sensing; Hyperspectral; Amount of dust absorption; Urban forests; Euonymus japonicus; Winter

Received: 2019-05-21 Accepted: 2019-09-12

ZTFLH:	X87
	X513

Corresponding Authors: YUE De-peng E-mail: yuedepeng@126.com

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https://www.gpxygpfx.com/EN/10.3964/j.issn.1000-0593(2020)06-1696-07 OR https://www.gpxygpfx.com/EN/Y2020/V40/I06/1696