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Crop leaf area index remote sensing inversion method and system under plot spatial-temporal feature constraint

A leaf area index, spatiotemporal feature technology, applied in image data processing, image analysis, image enhancement and other directions, can solve problems such as poor effect, achieve the effect of good effect and reduce uncertainty

Pending Publication Date: 2022-06-24
GUANGZHOU UNIVERSITY
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Problems solved by technology

[0005] The present invention provides a method and system for remote sensing inversion of crop leaf area index under the constraints of time and space characteristics of plots, aiming to solve the problem of poor effect of existing crop leaf area index inversion methods

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  • Crop leaf area index remote sensing inversion method and system under plot spatial-temporal feature constraint
  • Crop leaf area index remote sensing inversion method and system under plot spatial-temporal feature constraint
  • Crop leaf area index remote sensing inversion method and system under plot spatial-temporal feature constraint

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Embodiment Construction

[0023] The specific embodiments of the present invention will be further described below with reference to the accompanying drawings. It should be noted here that the descriptions of these embodiments are used to help the understanding of the present invention, but do not constitute a limitation of the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0024] see figure 1 The schematic flowchart shown in the embodiment of the present invention provides a remote sensing inversion method for crop leaf area index under the constraints of spatial and temporal characteristics of a plot, which includes the following steps:

[0025] S101. Based on the PROSAIL radiative transfer model, simulate canopy directional reflection under the conditions of different leaf physical and chemical parameters, canopy structure parameters...

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Abstract

The invention discloses a crop leaf area index remote sensing inversion method under the constraint of land parcel spatial-temporal characteristics, and the method comprises the steps: simulating canopy directional reflection under the conditions of different leaf physical and chemical parameters, canopy structure parameters and soil properties based on a PROSAIL radiation transmission model, and constructing a lookup table of a land parcel; based on the normalized vegetation index time sequence data, extracting growth starting date features of crops in the land parcels; the crop leaf area index priori knowledge is constructed by combining the growth starting date characteristics of the crops in the land parcels and the MODIS leaf area index product; and then obtaining a lookup table subset of the land parcel, and performing inversion on the leaf area index of the land parcel through a cost function about crop parameter spatial autocorrelation to obtain an inversion result. According to the method, a new cost function is designed from the characteristic that the leaf area index of the crop changes along with the phenology of the crop and the spatial autocorrelation of the crop parameters in the land parcel, the leaf area index is inverted through the lookup table method, the effect is better, and the obtained result is higher in precision.

Description

technical field [0001] The invention relates to the technical field of agricultural automation, in particular to a remote sensing inversion method and system for crop leaf area index under the constraints of space-time characteristics of a plot. Background technique [0002] Leaf area index (LAI) is an important crop canopy structure parameter, which controls the biophysical processes of crop photosynthesis, respiration, and transpiration. Due to differences in planting types, farming practices, soil conditions and other conditions, the leaf area index of crops in different plots showed differences. Obtaining the leaf area index of crops in farmland plots quickly and accurately is of great significance for precise farmland management. [0003] At present, there are two types of crop LAI inversion methods based on satellite remote sensing: empirical statistical methods and mechanistic model methods. The empirical statistical method needs to establish the mathematical statis...

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Application Information

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IPC IPC(8): G06T7/62
CPCG06T7/62G06T2207/30188
Inventor 杨颖频吴志峰黄启厅骆剑承
Owner GUANGZHOU UNIVERSITY
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