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Turkish Journal of Agriculture and Forestry

DOI

10.55730/1300-011X.3177

Abstract

Soil is the main influencing factor for plant growth, reproduction, and distribution. With the acceleration of industrialization and the intensification of human activities, the problem of heavy metal pollution in agricultural soil is becoming increasingly prominent. Heavy metals in soil are toxic and easily absorbed by plants, and consuming contaminated crops poses a great threat to human health. Therefore, it is necessary to monitor the content of heavy metals (HMs for short here) in soil. Hyperspectral Remote Sensing (HRS for short here) has great application prospects in obtaining quantitative information of soil organic matter, minerals and other components due to its ultra-high Spectral resolution. Compared with traditional detection methods, soil heavy metal inversion based on HRS has the advantages of fast, convenient, and large-scale on-site monitoring, and has important application value. This article studies the monitoring mechanism and feature extraction of HRS technology by analyzing the calculation methods of soil and HMs content. In the experimental section, the content of HMs in rice, corn crops, paddy soil, and lime soil from 2017 to 2020 was analyzed. Through experimental comparative analysis, it was found that the HMs enrichment coefficients in 2017, 2018, and 2020 were 0.987, 1.154, and 0.186, respectively. It can be seen that the enrichment coefficient of HMs was the smallest in 2020, and the highest in 2018. The use of HRS image processing can improve the accuracy of HMs content calculation, which is of great significance for the analysis of soil agricultural potential.

Keywords

Heavy Metal Content, Agricultural Potential Analysis, Hyperspectral Remote Sensing, Image Processing

First Page

239

Last Page

249

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