Method for measuring soil water content

Abstract

The invention discloses a method for measuring soil water content, which comprises the following steps of: S1, calculating a TVDI (Temperature Vegetation Dryness Index) by utilizing remote sensing data of visible light and near infrared and thermal infrared wave bands to obtain a first TVDI characteristic space; S2, setting different soil water contents according to ground meteorological observation data, then, inputting the data of the soil water contents into an ecological process model, and calculating vegetation temperature and surface temperature under the condition of different soil water contents; S3, inputting vegetation structural parameters and soil water contents into a radiation transmission model, and calculating a reflective spectrum of the visible light and the near infrared wave bands of vegetations under the condition of different soil water contents; S4, calculating the TVDI according to the vegetation temperature, the surface temperature and the reflective spectrum of the visible light and the near infrared wave bands to obtain a second TVDI characteristic space, and then carrying out slope division on the second TVDI characteristic space; S5, establishing a quantitative relationship equation between a slope and the soil water content Y; and S6, obtaining a space continuous coverage soil water content distribution result. The method for measuring the soil water content disclosed by the invention is capable of quantitatively measuring the soil water content and is high in precision.

Description

technical field [0001] The invention relates to the technical field of soil water content detection, in particular to a method for measuring soil water content. Background technique [0002] With the continuous development of remote sensing science and technology, vegetation drought monitoring using visible light, near-infrared and thermal infrared remote sensing data has received extensive attention. [0003] The main methods are: (1) Using visible and near-infrared data alone, constructing remote sensing indices related to the water deficit of vegetation itself, and finally indirectly estimating soil drought conditions through remote sensing indices. This method is affected by the physiological process of vegetation. In most cases, this indirect relationship is difficult to establish. That is, when the vegetation performs well, the surface soil moisture may have begun to lack, and there is a "time difference" between vegetation moisture and soil moisture, which leads to th...

AI Technical Summary

Problems solved by technology

[0005] (1) Existing soil drought monitoring methods based on visible light, near-infrared or thermal infrared remote sensing data are all qualitative and relative trend expressions, and cannot obtain actual soil moisture content

[0006] (2) Lack of relevant model support, the obtained vegetation or soil drought results have low accuracy, poor reliability, and low practical value

[0007] (3) Not making full use of the feature space information of visible light, near-infrared and thermal infrared remote sensing indices

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