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A Time-Series Data Reconstruction Method of Vegetation Index Based on Wavelet Multi-scale Decomposition

A multi-scale decomposition and time-series data technology, applied in the direction of electrical digital data processing, special data processing applications, instruments, etc., can solve the problems of non-stationarity of vegetation index time-series data, unsuitable for stationarity methods, etc., to achieve a wide range of applications, high precision effect

Active Publication Date: 2017-08-11
FUZHOU UNIV
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Problems solved by technology

These methods all have certain rationality and practical promotion value, but their shortcoming is that the vegetation index time series data are generally non-stationary, so it is not suitable to use the stationary method, so there are inevitably certain limitations

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  • A Time-Series Data Reconstruction Method of Vegetation Index Based on Wavelet Multi-scale Decomposition
  • A Time-Series Data Reconstruction Method of Vegetation Index Based on Wavelet Multi-scale Decomposition
  • A Time-Series Data Reconstruction Method of Vegetation Index Based on Wavelet Multi-scale Decomposition

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Embodiment Construction

[0008] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0009] The method for reconstructing vegetation index time series data based on wavelet multi-scale decomposition in the present invention, such as figure 1 As shown, using wavelet transform, the original vegetation index signal is decomposed into high-frequency and low-frequency components corresponding to half-moon, month, bimonthly, season, half-year, and inter-annual scales, and further based on the vegetation index on each scale Time-series data change law Select the appropriate model to reconstruct the vegetation index time-series data, and finally integrate the time-series data of different scales to realize the reconstruction of the vegetation index time-series data.

[0010] Specifically, the reconstruction method of vegetation index time-series data based on wavelet multi-scale decomposition in this embodiment further includes the f...

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Abstract

The invention relates to a reconstruction method of vegetation index time-series data based on wavelet multi-scale decomposition, which is characterized in that: the method is based on the vegetation index time-series data, and uses wavelet transform to decompose the vegetation index and the original time-series data of climate factors into corresponding half moons According to the time-series data of vegetation index on each scale, the time-series data of climate factors on the corresponding scales are selected, and the appropriate model is selected to carry out different scales. Finally, the time series data of vegetation index on all scales are integrated to realize the reconstruction of the original time series data of vegetation index. The invention has the characteristics of high precision, wide application range and the like.

Description

technical field [0001] The present invention relates to the technical field of time series analysis, in particular to a reconstruction method for vegetation index (Vegetation index, VI) time series data based on wavelet multi-scale decomposition. Background technique [0002] The time series data of remote sensing vegetation index are widely used in the monitoring of dynamic changes in forest and crop vegetation. In the process of remote sensing data collection and image processing, due to the interference of various factors such as observation angles and clouds, the quality of the generated vegetation index time series data is not ideal. Therefore, it is necessary to further denoise and reconstruct the original vegetation index time series data. [0003] There are many methods for denoising and reconstructing vegetation index time series data, such as best slope index extraction (Bestslope extraction, BISE), Fourier analysis, multivariate least squares, geostatistics, nonli...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F19/00
Inventor 邱炳文钟鸣
Owner FUZHOU UNIV