Water body index variable coefficient-based rice sub-pixel recognition method

A technology of water body index and coefficient of variation, which is applied in the field of agricultural remote sensing, can solve the problems of low recognition and do not consider the sub-pixel problem of rice, and achieve the effects of high classification accuracy, stable and reliable results, and easy operation.

Inactive Publication Date: 2017-10-20
SUN YAT SEN UNIV
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Problems solved by technology

However, none of the above methods consider the sub-pixel problem of rice, and the recognition deg

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  • Water body index variable coefficient-based rice sub-pixel recognition method
  • Water body index variable coefficient-based rice sub-pixel recognition method
  • Water body index variable coefficient-based rice sub-pixel recognition method

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Embodiment 1

[0037] A method for automatic identification of rice sub-pixels based on the coefficient of variation of water body index, specifically comprising the following steps:

[0038] Step S1: Construct vegetation index, water body index, surface temperature time series data set;

[0039] Firstly, NDVI (bands 1 and 2) and LSWI (bands 2 and 6) are calculated based on the reflectance products synthesized by MOD09A1 for 8 days. Using Savitzky-Golay filter and other denoising methods to smooth and denoise the original intra-year time series data set. Calculate nighttime surface temperature based on MYD11A2 product. A total of 46 time-series data sets within a year were obtained as the basis for rice sub-pixel identification.

[0040] Step S2: Eliminate non-cultivated land pixels in the research area;

[0041] According to the distribution characteristics of the vegetation index value range, the sparse vegetation (including water body, building land, saline-alkali land, etc.) and natur...

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Abstract

The invention discloses a water body index variable coefficient-based rice sub-pixel recognition method. The method comprises the following steps of: S1, constructing a water body index, vegetation index and surface temperature time series data set; S2, getting rid of non-cultivated land pixels in a research area; S3, determining a period of a crop growth season according to a surface temperature; S4, calculating variable coefficients of water body indexes in each pixel growth season; S5, determining a relationship between water body index variable coefficients and rice planting area proportions; and S6, calculating a rice planting area proportion according to the variable coefficients of the water body indexes. According to the method, by utilizing the water requiring property of rice, the water body index variable coefficients are reduced along with the increase of the rice planting area proportions, and the water body index variable coefficients and the rice planting area proportions have prominent linear dependence. Through designing the variable coefficients of the water body indexes to recognize rice sub-pixels and calculating the planting area proportion, the method has the characteristics of being independent of prior knowledge, good in robustness, high in classification precision and strong in knowledge ability.

Description

technical field [0001] The invention belongs to the technical field of agricultural remote sensing. More specifically, it relates to a rice sub-pixel identification method based on the coefficient of variation of water body index. Background technique [0002] Changes in the spatial distribution of rice planting are crucial to my country's agricultural industrial structure adjustment, water resource monitoring, and greenhouse gas emissions. As the largest rice producing country in the world, rapid and accurate monitoring of the spatial distribution of rice is of great significance for ensuring food security and climate change research. Due to the limitations of data availability and computing power, high-precision optical remote sensing and synthetic aperture radar are difficult to apply to regional rice area mapping. At present, most of the regional or national-scale rice area mapping uses medium-resolution remote sensing data, which have high time resolution and are rela...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06Q50/02
CPCG06Q50/02G06V20/188
Inventor 袁文平刘伟
Owner SUN YAT SEN UNIV
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