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The present paper demonstrated an image processing technique of surface soil crack analysis. The geometric features of cracks, such as width, length, and surface area are estimated. These parameters are important, because they influence both the soil hydraulics and mechanics. The crack intensity factor was introduced as a descriptor of the extent of surficial cracking. The correlation analysis indicates that area-weighted mean ratio of soil-crack area to perimeter and index r has a much closed positive relationship with cracks intensity and the area weighted mean of crack fractal dimension declines continuously as the degree of development of soil cracks increases, indicating that the degree of complexity of the soil cracks also gradually decreases. However, traditional visual assessment, which is the primary method in use, is slow and expensive. The present works involve image processing technique for the automatic detection and analysis of cracks in the digital image of a concrete surface.
Cracks on upper surface of soil can appreciably influence the soil performance in a variety of agricultural, geotechnical and environmental sectors. Though wetting and drying cycle because of seasonal changes of weather can be a dynamic force for dehydration cracking, climate change could potentially exacerbate the harmful effects (Gore 2006; Tang et al. 2010). Soil cracking is a multifaceted process that persuades soil properties, plant growth, and the movement of water and solutes in soil (Bandyopadhyay et al. 2003; Xiong et al. 2009). Earlier studies suggested that soil cracks are directly connected to changes in soil structure (Velde et al. 1999; Bruand et al. 2001), infiltration capacity (Chenwuing et al. 2003), evaporative loss of soil water, volume shrinkage (Tang et al. 2011) and the special movement of soil solutes (Roberto 2002). Adrian et al. (2000) stated that soil cracks cause worsening in soil water quality and persuade several significant physical, chemical, and biochemical processes in the soil (Yoshida et al. 2004). Studying soil cracks has significant importance in understanding the soil degradation processes and subversive pollution of water and the expansion of re-vegetation practices (Xiong et al. 2008). Chertkov (2000) affirmed that crack networks in the soil directly depend upon the hydraulic properties of soil. Desiccation cracks are also observed on the surface of natural clayey soil slopes. These cracks expose the interior of soil slopes to climatic changes, thereby allowing further cracking to occur. Many researches indicated that soil-crack morphology qualitative descriptions, through complex network structure of soil cracks (Novak 1999; Vogel et al. 2005; Uday and Singh 2013) and it significantly influences the hydraulic properties of the soil.
Field survey was conducted near the Cossi River at Medinipur town, from August, 2014 to May, 2015 respectively. The physical properties of the study area are presented in Table 1. Soil cracking in the study area was divided into five grades, namely feeble development, slight development, medium development, intensive development and extremely intensive development, and quadrats investigations were carried out for each grade. A total 20 crack quads (Size 400 mm × 400 mm) were selected which represent the different degrees of development of soil cracks. The photos of the field were collected using normal digital camera (7.2 mega pixel) after clearing up all the weeds and the images were processed indoors.
A total 20 samples were taken between August, 2014 and May, 2015 to obtain bare soil images for estimation of cracks morphology. Images were taken from approximately 1 m height horizontally to the ground. The area for each image was about 0.1225 m2 (0.35 m × 0.35 m) and a reference scale was used to obtain similar soil surface areas for the difference soil cracks. All images were taken with identical camera setting having best shoot function using flash light, with out any zoom and having constant focus area (Bauer and Strass 2014). The images were further processed in laboratory (Fig. 3). The co-ordinate of the sample locations were collected through global positioning system (GPS). The images were analyzed through ERDAS v.8.software. Images were registered in ERDAS Imagine v8.5 using the GPS co-ordinate point based on 2nd order polynomial transformation and nearest neighbour resampling method. After coordinate correction, digital image processing and topological transformation, the geometric characteristics of crack patterns such as length, perimeter and area of each soil crack were extracted from the processed images (Liu et al. 2013; Lee et al. 2013; Jianhua et al. 2015). Figure 2 represents the flowchart of proposed methodology.
where, D c Soil-crack area density; a c the sum of all soil-crack areas in the typical cracked soil (in mm2), and A the total surface area of the typical cracked soil (in mm2).
Table 1 shows the geometrical characteristic of soil cracks. The average length was 127.0 mm with SD of 62.16 mm. In Fig. 4a correlation analysis indicates that AWMARP has a very close positive relationship with Dc (R2 = 0.727). This result shows the significant growth in the average width of soil cracks, especially in the stages of intensive development of soil cracks (Xiong et al. 2009).
Figure 4b presents the index r value against density of cracks, Dc. Generally, as Dc values increase, the index r also increases logarithmically, indicating that soil-crack connectivity grows continuously with increasing degree of development of soil cracks (Table 2). This reflects the fact that soil cracks do not develop in isolation but are interconnected. The number of interconnected soil cracks rises during the process of soil-crack development, resulting in enhanced connectivity. Soil-crack connectivity refers to the degree of connection between or spatial continuity of soil cracks. This is an important property related to the migration efficiency of water and solutes in soil. The index r is an indicator often used to measure the connectivity of a network (Xu 2002). Larger values of this index indicate greater connectivity of soil cracks. A correlation analysis indicates that index r has a significant relationship with Dc (correlation coefficient = 0.801).
Area-weighted mean ratio of soil-crack area to perimeter (AWMARP) is one of the crack fractal dimensions of soil. The ratio of soil-crack area to perimeter is defined as the ratio of the area of a soil crack to its perimeter. The mean value of AWMARP is 3.4 ± 1.95 (Table 3). Figure 4b indicated close positive relationship between AWMARP and D c (R2 = 0.727). This result shows the significant growth in the average area of soil cracks, especially in the stages of intensive development of soil cracks. Our results also corroborated with the previous findings (Xiong et al. 2009).
A computer aided image analysis program was used to determine geometric features of cracks, such as width, length, and surface area values, connectively and complexity from scanned photographs of the desiccation process. These parameters are important, because they influence both the soil hydraulics and mechanics. However, the development of cracks varies from soil to soil, even under the similar climatic condition. A decreasing trend was observed on connectivity throughout the cracking process, estimated by cracks intensity (Dc), area-weighted mean ratio of soil-crack area to perimeter (AWMARP) and the area weighted mean of crack fractal dimension (AWMFRAC) values, it may be due to the number of trim cracks is abridged by the progression of crack development. On the other hand, r index which expresses connectivity of soil crack is also steadily expanded in the study site. In depth study is required to explore the connection between soil fracture mechanics and shrinkage characteristics over a range of water contents. 2b1af7f3a8