Abstract
ABSTRACT Leaf area index (LAI) is one of the important variables for crop growth monitoring and yield estimating. In this article, the potato LAI was retrieved by several vegetation indices (VIs) and spectral parameters of the continuum removal method (SPCRM) to provide accurate estimates. A comparison of the two methods of retrieving precision was completed. The data source for computing VIs and SPCRM was hyperspectral reflectance data for the life cycle, derived from two potato cultivars, Favorite (early maturing variety) and Yanshu 4 (late maturing variety), through field experiments. Sensitive bands were identified to indicate seven VIs by correlation analysis. Additionally, seven SPCRM were computed. Based on these methods, the potato LAI was retrieved and tested. Meanwhile, a comparison of the retrieving precision was implemented. The results showed that compared with the filtered spectral reflectance and VIs, the correlation between the potato LAI and the continuum removal spectral reflectance and its retrieved SPCRM were higher. The determination coefficients (R 2) of the retrieving models of four parameters, the total area (S), the left area (Sl), the right area (Sr) and the depth area ratio (W), derived from the continuum removal method were all above 0.801, and their fitting coefficients (r) were all above 0.868, with the mean relative errors (MRE) all <0.14. It was identified that W was the most suitable parameter for retrieving the potato LAI. Although the effectiveness of SPCRM requires further research, this study manifests that SPCRM have the potential to accurately retrieve the potato LAI.
Highlights
Leaf area index (LAI), whose mathematical meaning is the sum of the area of a single side of a leaf per unit of surface area (Chen & Black, 2010), is a crucial parameter reflecting the biochemical status and physical processes of crop populations (Liu, Zhou, Wu, Xia, & Tang, 2016)
difference vegetation index (DVI), Normalized difference vegetation index (NDVI), enhanced vegetation index (EVI) and soil-adjusted vegetation index (SAVI) were moderately correlated with the potato LAI, while ratio vegetation index (RVI), green normalized difference vegetation index (GNDVI) and green ratio vegetation index (GRVI) were slightly correlated
It was found that DVI, NDVI, EVI and SAVI were moderately correlated with potato LAI, while RVI, GNDVI and GRVI were slightly correlated
Summary
Leaf area index (LAI), whose mathematical meaning is the sum of the area of a single side of a leaf per unit of surface area (Chen & Black, 2010), is a crucial parameter reflecting the biochemical status and physical processes of crop populations (Liu, Zhou, Wu, Xia, & Tang, 2016) It can provide vital theoretical indicators for the field management of crops, water and fertilizer regulation, growth monitoring and yield estimation. Hyperspectral remote sensing can obtain data and information from objects of interest with a number of very narrow electromagnetic wavebands (Du, Gong, et al, 2016) It provides a path for crop growth monitoring in real time and estimating crop agronomic parameters with its strong continuity and large amount of information generated.
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