Quantitative Evaluation of Post-Tillage Soil Structure Based on Close-Range Photogrammetry

Soil tillage is essential for improving soil structure, enhancing fertility, promoting crop growth, and increasing yield. However, precise and efficient standardized methods for quantitatively evaluating post-tillage soil structure are still absent. This study aims to develop a general quantitative evaluation method for post-tillage soil structure using close-range photogrammetry. Six soil surface sample plots of different scales were selected, and two image acquisition methods and three platforms were chosen for image capture and 3D reconstruction. Geomagic Wrap was used for post-processing the models, with indicators such as clod sizes, surface flatness, and cumulative percentage used for quantitative description. Model accuracy was validated using traditional needle plate and vernier caliper measurements. The most effective combinations of image acquisition methods and 3D reconstruction platforms were identified based on modeling efficiency and quality. The results showed that combining image acquisition, 3D reconstruction platforms, and post-processing software enables high-precision 3D reconstruction and accurate digital information retrieval. Image Acquisition Method One and the AgisoftMetashape platform demonstrated the best combination in terms of model completeness, texture detail, and overall quality. This combination is recommended for the 3D reconstruction and digital information retrieval of soil surfaces. This study provides a method for evaluating post-tillage soil structure, including image acquisition, 3D reconstruction, model post-processing, and quantitative metrics.

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Publication Details

Journal
Agriculture
Published
2024-11-23
DOI
https://doi.org/10.3390/agriculture14122124
Citations
3
Primary Topic
Remote Sensing and Land Use
Type
article
Field-Weighted Citation Impact
1.13

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article

Quantitative Evaluation of Post-Tillage Soil Structure Based on Close-Range Photogrammetry

Qishuo Ding, Gaoming Xu, MA Guo-xin, Ruiyin He et al.
3 citations
Agriculture
Remote Sensing and Land Use
1.13
article

Quantitative Evaluation of Post-Tillage Soil Structure Based on Close-Range Photogrammetry

Qishuo Ding, Gaoming Xu, MA Guo-xin, Ruiyin He, Yun Feng Guo, Xinxin Chen, Jianping Hu, Wei Liu
article en
3 citations

Abstract

Soil tillage is essential for improving soil structure, enhancing fertility, promoting crop growth, and increasing yield. However, precise and efficient standardized methods for quantitatively evaluating post-tillage soil structure are still absent. This study aims to develop a general quantitative evaluation method for post-tillage soil structure using close-range photogrammetry. Six soil surface sample plots of different scales were selected, and two image acquisition methods and three platforms were chosen for image capture and 3D reconstruction. Geomagic Wrap was used for post-processing the models, with indicators such as clod sizes, surface flatness, and cumulative percentage used for quantitative description. Model accuracy was validated using traditional needle plate and vernier caliper measurements. The most effective combinations of image acquisition methods and 3D reconstruction platforms were identified based on modeling efficiency and quality. The results showed that combining image acquisition, 3D reconstruction platforms, and post-processing software enables high-precision 3D reconstruction and accurate digital information retrieval. Image Acquisition Method One and the AgisoftMetashape platform demonstrated the best combination in terms of model completeness, texture detail, and overall quality. This combination is recommended for the 3D reconstruction and digital information retrieval of soil surfaces. This study provides a method for evaluating post-tillage soil structure, including image acquisition, 3D reconstruction, model post-processing, and quantitative metrics.

AgricultureVol. 14(12)
Jiangsu University (CN), Nanjing Agricultural University (CN), Jiangmen Polytechnic (CN)
National Natural Science Foundation of China
Life in Land
Openalex Percentile: Top 23%
Remote Sensing and Land Use
1.13
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