• 遥感科学与应用技术 •

### 基于包络检波和STFT谱分析的探地雷达土壤分层信息识别

1. 1. 中国农业大学土地科学与技术学院,北京 100083
2. 中国农业大学信息与电气工程学院,北京 100083
3. 农业农村部农业灾害遥感重点实验室,北京 100083
4. 中国地质大学（北京）土地科学技术学院,北京 100083
• 收稿日期:2019-05-30 修回日期:2019-09-16 出版日期:2020-02-25 发布日期:2020-04-13
• 通讯作者: 朱德海 E-mail:zhudehai@263.net
• 作者简介:李 俐（1976&#x02014; ）,河南南阳人,副教授,主要从事微波农业应用研究。E-mail: lilixch@163.com
• 基金资助:
中国农业大学基本业务费项目(2019TC117)

### Soil Layer Identification based on Envelope Detector and STFT Spectrum Analysis of Ground Penetrating Radar Signals

LI Li1,3, FU Xue2, CUI Jia2, ZHANG Chao1,3, ZHU Dehai1,3,*(), WU Kening4

1. 1. College of Land Science and Technology, China Agricultural University, Beijing 100083, China
2. College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China
3. Key Laboratory of Remote Sensing for Agri-Hazards, Ministry of Agriculture and Rural Affairs, Beijing 100083, China
4. School of Land Science and Technology, China University of Geosciences, Beijing 100083, China
• Received:2019-05-30 Revised:2019-09-16 Online:2020-02-25 Published:2020-04-13
• Contact: ZHU Dehai E-mail:zhudehai@263.net
• Supported by:
The Fundamental Research Funds for the Central Universities(2019TC117)

Abstract:

Soil stratification information, especially surface soil structure, has important impact on land productivity and is an important index for evaluating soil quality. The present study aimed to obtain the information of soil layers quickly and accurately, for which Ground Penetrating Radar (GPR) technology was used. The echo signals of GPR were processed in both the time and frequency domains. In the time domain, the envelope detection method was used to determine the transience of the echo signals and therefore to get the location of soil layers on the time axis. To get the soil layer location in spatial coordinates, the velocity of electromagnetic wave propagation in soil was needed. Considering the velocity of electromagnetic wave propagation in soil layers varying with the soil dielectric constants, the Short-Time Fourier Transform (STFT) method was applied to the echo signals for dielectric constant analysis in the frequency domain. Soil layers with different dielectric constant exhibited different characteristics in the STFT signals. After clustering analysis of the soil layers, the relationship between STFT characteristic value and dielectric constant in a certain layer was established based on regressive analysis. Then, the velocity of electromagnetic wave propagation in each soil layer was determined using the dielectric constants. After the electromagnetic wave velocity of Ground Penetrating Radar (GPR) was estimated, the location of layers' interface was further determined and then the thickness of each soil layer was computed. To valid the effect of the above-mentioned methods, the echo signals of soil, for both the ideal simulated experimental environment which has obvious layered interface and the farmland environment whose layers have changed naturally, were collected. The experimental results show that, with the envelope detection method, layers not deeper than 70cm in the ideal simulated experimental environment were 100% detected and for both the ideal simulated experimental environment and the farmland environment, the detection rate of ground penetrating radar echo information reached 94.5%. The estimation of ground penetrating radar echo velocity using STFT spectrum analysis shows that the calculation error of soil thickness above 70 cm depth was mostly below 10%. Our findings suggest that the proprosed methodology can effectively identify the stratification information of shallow soil and estimate the thickness of the soil. However, surface vegetation, film mulching, soil voids, soil salinity, moisture heterogeneity, gradual change of soil layers, and soil layer depth will all affect the accuracy of the detection. For example, with the increase of soil depth, the error becomes larger. So, if the data acquisition spot is selected rationally, the proposed methodology can be applied to plough layer thickness detection in practical fileds.