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In situ measurement of soil macropores by dye tracing and image analysis

文献类型： 外文期刊

作者： Qiu, Lin 1 ; Chen, Xiaomin 2 ; Pan, Jianjun 2 ;

作者机构： 1.Jiangsu Acad Agr Sci, Inst Agr Econ & Informat, Nanjing, Jiangsu, Peoples R China

2.Nanjing Univ Agr, Coll Resources & Environm Sci, Nanjing, Jiangsu, Peoples R China

关键词： soil macropores;dye tracing;Image analysis

期刊名称：2013 SECOND INTERNATIONAL CONFERENCE ON AGRO-GEOINFORMATICS (AGRO-GEOINFORMATICS)

ISSN： 2334-3168

年卷期： 2013 年

页码：

收录情况： SCI

摘要： Soil macropores are the main migration passage for water and air in soil. Their existence in soil with proper quantity can enhance soil permeability, improve rhizospheric environment, and increase water retention capacity. But excessive soil macropores will result in a waste of rainfall and irrigation water, loss of soil nutrient and fertilizer, and pollution of ground water. It is necessary to know the quantity and spatial distribution of soil macropors, which is the key point for studying the mechanism of soil solute transportation, and for the monitoring of ground water quality. Measurement of soil macropores is difficult because of its geometrical diversity and intricately spatial distribution in soil. In this paper we try to develop a measurement technique in situ to quantify soil macropores by dye tracing and image analysis (DTIA) with paddy soil from the Tai Lake region as a case for study. The brilliant blue solution, which was selected as dye solution, was poured onto the soil of study area. After one day's dyeing, vertical soil profiles were dug and photographed. Stained regions in the soil profile are places where soil pores exist. The bigger the aperture size of a pore is, the more the dye solution inpours, and the darker the color of the stained region is. Images of soil profiles were photographed with digital camera, and processed for classification of soil pores with functions of remote sensing image processing software ERDAS IMAGINE9.0, such as geometric correction, mask, unsupervised classification, supervised classification and so on. Soil pores were classified to 10 levels. Level 1 to 4, which were considered as soil macropores, were picked out for computing the quantity. The results show that the content of soil macropores consistents with the variation of soil porosity, soil clay content and soil saturated conductivity from top to bottom of the soil profile. Compared to content of soil macropores computed by soil moisture characteristic curves (SMCC), quantity by DTIA is bigger but more realistic. Finally, factors that influence the DTIA were discussed, such as digging of soil profile, photographing of image, resolution of image and background color of soil profile so on.

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