Adaptation Analysis of Measurement Techniques and Inversion Algorithms for Tea Tree LAI

Abstract

The leaf area index (LAI) is one of the most important biophysical parameters of vegetation canopy, which is of great significance for estimating the growth and yield of tea trees. In the present era, tea plantations are becoming increasingly densely packed. However, there is a lack of accurate methods for measuring the LAI of densely planted tea trees. To explore LAI measurement and inversion methods applicable to densely planted tea trees, this study used tea trees in Langxi County as a case study. Using two commonly used measurement methods for densely and sparsely grown row crops and a measurement method for densely grown tea trees proposed based on practice, three sets of tea tree LAI were measured and compared with the true LAI value obtained using direct measurements. Using the set with the best performance to construct a regression model with vegetation indices, the LAI during the new shoot period of tea leaves is inverted. The results are summarized as follows. 1) According to the analysis of the direct measurements, the proposed measurement method for densely grown tea trees is the closest LAI values to the true values for densely planted tea trees in Langxi. 2) According to the fitting analysis, the common vegetation indices were significantly correlated with the LAI. The vegetation indices constructed with green, red edge, and shortwave infrared bands exhibited a higher correlation with the LAI than those constructed without these bands. Among them, EVIre exhibited the highest fitting accuracy.

Keywords

• LAI-2200
• leaf area index (LAI)
• measurement techniques
• red edge
• vegetation indices