A Correction Method of Spatial Scale Error of Leaf Area Index Based on Wavelet Transform

A leaf area index and wavelet transform technology, applied in the field of correction, can solve the problems of affecting the correction accuracy of scale errors, the estimation cannot be separated, and the large error of the nonlinearity of the inversion model. Effect of Remote Sensing Inversion Accuracy

CN107977338BActive Publication Date: 2018-11-09INST OF GEOGRAPHICAL SCI & NATURAL RESOURCE RES CAS +1
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Publication Date
2018-11-09

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Abstract

The invention discloses a leaf area index spatial scale error correction method based on wavelet transform. The method is mainly divided into the following six steps that: obtaining synchronous / nonsynchronous small-scale remote sensing data; estimating a scale transform error rate; estimating a wavelet transform detail loss ratio; carrying out correction regression coefficient least square calibration; estimating a spatial scale effect error; and correcting a large-scale leaf area index spatial scale error. Compared with an existing method, the method has the advantages of a simple and convenient implementation process, in addition, a scale error correction effect is irrelevant to the nonlinear degree of a remote sensing inversion model and is not limited to the continuous and derivable constraint limit of the inversion model, in addition, the assistance of synchronous small-scale prior data is not required, an application range can be effectively enlarged, and the remote sensing inversion accuracy of a large-scale leaf area index product is improved.
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Description

technical field

[0001] The invention relates to a correction method, in particular to a method for correcting leaf area index spatial scale errors based on wavelet transform. Background technique

[0002] Leaf area index is one of the most basic parameters to characterize vegetation canopy structure, and is also a key factor determining vegetation biomass and yield, and is an important data source for crop growth monitoring and yield estimation. Accurate determination of leaf area index is of great significance for understanding the biophysical processes of forests and crops, as well as the precise inversion of various parameters such as photosynthetically active radiation and crop yield, and monitoring of diseases and pests. Taking advantage of the wide coverage of satellite remote sensing data to quantitatively estimate large-area leaf area index not only saves time and effort, but also enables real-time, fast and accurate measurement and dynamic monitoring of large-scale ...

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Embodiment Construction

[0046] The present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0047] figure 1 A wavelet transform-based error correction method for leaf area index spatial scale is shown, which is to perform wavelet transform on the small-scale leaf area index products obtained from the inversion of synchronous / non-synchronous red light and near-infrared band surface reflectance data. Establishing the relationship between scale conversion error rate and wavelet transform detail loss rate to estimate the spatial scale error of leaf area index, so as to realize the error correction method of large-scale leaf area index products. The present invention is mainly divided into the following six steps: synchronous / asynchronous small-scale remote sensing data acquisition; scale conversion error rate estimation; wavelet transform detail loss rate estimation; correction regression coefficient least square rate determinat...