基于光谱指数的不同叶倾角分布下玉米冠层叶绿素含量反演

doi:10.3964/j.issn.1000-0593(2019)07-2257-07

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Abstract Remote sensing is the main approach to carry out non-invasive detection of plant chlorophyll information on the ground/near ground, airborne and spaceborne levels. At present, spectral index for multi-band calculation has been widely used in empirical/semi-empirical estimation of canopy chlorophyll content. Taking the difference of leaf inclination angle distribution (LAD) between different crops and different varieties of homogeneous crop into consideration, this study analyzed the influence of LAD on retrieving chlorophyll content, and selected chlorophyll-related spectral indices that are insensitive to the variation of LAD and researched canopy chlorophyll retrieval model. PROSAIL radiative transfer model was used for simulating the canopy reflectance corresponding to different leaf chlorophyll content (LCC), leaf area index (LAI) and LAD. The simulation results showed that under the same LAI and LCC conditions, the canopy reflectance corresponding to different LAD was significantly different, and the canopy reflectance decreased with the increase of the average LAD. By calculating the correlation coefficient of 12 common chlorophyll-related spectral indices with CCC, the sensitivity of spectral indices in retrieval of chlorophyll content under different LAD was evaluated, consequently, four spectral indices that are insensitive to variation of LAD were selected: MTCI, MNDVI1, CI_red-edge and MNDVI8.80 measured corn samples were utilized to model and validate the estimation models of CCC. Model establishment and verification results showed MNDVI8 was the most insensitive to variation of LAD, thus it was the best spectral index for estimating chlorophyll content with the coefficient of determination (R²) of 0.70 and the root mean square error (RMSE) of 22.47 μg·cm^-2. The precision of CIred-edge (R²=0.63, RMSE=24.06 μg·cm^-2), MNDVI (R²=0.66, RMSE=24.07 μg·cm^-2) and MTCI (R²=0.65, RMSE=26.76 μg·cm^-2) retrieval model was relatively close but was weaker than that of MNDVI8. Through analyzing the retrieval results, it was concluded that different spectral indices had different sensitivities to variation of LAD. The preferred spectral indices generally had the best correlation and highest sensitivity to chlorophyll content, among which MNDVI8 was least affected by LAD and can be used to retrieve CCC in corn under different LAD types. Although retrieval capabilities of MTCI，CI_red-edge and MNDVI1 were slightly weaker than MNDVI8, they were less affected by variation of LAD and also had good retrieval capabilities. This paper researched the influence of LAD on retrieving chlorophyll content based on spectral indices, and the results from measured corn data were in accordance with those from simulated data. Based on the sensitivity analysis and validation results of canopy chlorophyll content retrieval models under different LAD types, this paper has a certain reference significance for remote sensing application of estimation of chlorophyll content in crop without prior knowledge of LAD in large scale.

Key words：Retrieval of chlorophyll content; Spectral indices; Leaf inclination angle distribution; Leaf area index

Received: 2018-05-30 Accepted: 2018-10-09

ZTFLH:

S127

Corresponding Authors: JIAO Quan-jun E-mail: jiaqj@radi.ac.cn

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https://www.gpxygpfx.com/EN/10.3964/j.issn.1000-0593(2019)07-2257-07 OR https://www.gpxygpfx.com/EN/Y2019/V39/I07/2257

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