高光谱反射率的滨海地区土壤全磷含量反演

doi:10.3964/j.issn.1000-0593(2022)02-0517-07

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Abstract Spectral characteristics are the inherent attributes of ground objects. Analyzing spectrum is help to improve the accuracy of ground objects recognition and a basis of quantitative remote sensing. However, limited by scale effect, the spectrum acquired in near-earth space is often quite different from that of remote sensing pixels. Therefore, revealing the spectral characteristics of typical wetland landscapes on the scale of remote sensing pixels is useful to improve the accuracy of large-scale wetland remote sensing classification and inversion of vegetation parameters. Based on the satellite-borne EO-1 Hyperion data, the reflectance of lotus field, reed land, woodland, paddy, highland, construction land, river，lake and pond were extracted from Lake Nanyang, one of the grass lake wetlands in North China Plain.The spectral characteristics of the pixel-scale ground objects were quantitatively analyzed by using the first derivative of the spectrum and calculating a variety of hyperspectral vegetation indexes. The results showed that: (1) The reflectance spectrumof eight wetland landscapes were significantly different, andthere were also differences in the 5 vegetation types. The reflectance of the lotus field was significantly higher than that of other landscapes in the whole wave-band range. It sreflective peak in the green band and absorptive valley in the red band was the most obvious. The reflectance spectrum of the reed field and paddy were similar in visible light and red edge region. The reflectivity curves of paddy and upland farms were different, and the green paddy’s reflective peak was higher than that of upland. (2) The first derivative spectrum of eight landscapes were obviously different at the blue, yellow, and red edge regions, especially at the red edge.The red edge slope of the lotus field was the largest, and the red edge position was obviously blue shift (712 nm), indicates that it has high chlorophyll content and the best health condition. The red-edge slope of woodland was the second, but its red edge position was an obvious red-shift (722 nm). (3) Woodland hadthe highest vegetation index, the vegetation index of water bodies and construction mode rate landscapes land was low, and other. There was no significant difference in the mean values of indexes related to normalized difference vegetation index (NDVI) among reed land, paddy, upland and lotus fields, but only in the Enhanced Vegetation Index (EVI) and Chlorophyll Index RedEdge 710. It suggested that EVI and Chlorophyll Index RedEdge 710 index can more effectively indicate the difference of greenness and coverage between wetland vegetation types. The research has great significance for the high-precision classification wetland of and inversion of vegetation parameters.

Key words：Lake Nanyang; Hyperion; Hyperspectral remote sensing; Spectral analysis; Wetland landscape

Received: 2020-12-29 Accepted: 2021-01-28

ZTFLH:

S153.6

Corresponding Authors: YU Quan-zhou E-mail: zgh@nuist.edu.cn

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http://www.gpxygpfx.com/EN/10.3964/j.issn.1000-0593(2022)02-0517-07 OR http://www.gpxygpfx.com/EN/Y2022/V42/I02/517

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