Remote sensing data-based leaf area index inversion method for winter wheat in different growth periods

Abstract

The invention discloses a remote sensing data-based leaf area indexes (LAI) inversion method for winter wheat in different growth periods. The method comprises the following steps of obtaining LAI actual measurement data; obtaining remote sensing data and performing preprocessing; dividing the whole growth period of the winter wheat into three stages, selecting five vegetation indexes NDVI, EVI, EVI2, RVI and OSAVI to perform LAI inversion of the winter wheat in the whole growth period and the different growth periods, and analyzing a relationship, in unary linear, exponential, logarithmic and power function forms, between the LAI actual measurement data and each vegetation index; comparing different index inversion results of the winter wheat in the different growth periods; and obtaining an optimal index inversion and fitting model of the winter wheat in the different growth periods according to the comparison of the different index inversion results of the winter wheat in the different growth periods. The method shows that GF-1 data has a very good application prospect in crop growth remote sensing research, and the situation that Chinese agricultural remote sensing monitoring depends on foreign data for a long term can be effectively improved.

Description

technical field [0001] The invention relates to a method for retrieving leaf area indices of winter wheat at different growth stages based on remote sensing data (GF-1 satellite data). Background technique [0002] Leaf Area Index (LAI) is a key indicator reflecting individual and group characteristics of crop growth, and has become one of the main indicators of crop growth monitoring. [1] . Remote sensing technology has become the main means of crop LAI monitoring due to its advantages of being timely, effective and non-destructive. [2]、[3] . The GF-1 satellite successfully launched by my country in 2013 takes into account both high time and high spatial resolution, which can break the heavy dependence on foreign satellites such as LandSat in principle. GF-1 satellite has played an important role in agricultural remote sensing, such as in the survey of crop planting area, Liu Guodong et al. [4] According to the crop phenology calendar, a remote sensing sampling survey m...

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Problems solved by technology

[0003] During the different growth periods of winter wheat, the vegetation and soil background information in the observation field are constantly changing, which makes the spectral reflectance of wheat constantly changing, and the use of a single remote sensing index cannot well invert the crop growth information. [12]、[13]

However, there are few studies considering different growth stages of crops in monitoring crop growth based on GF-1 data

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