بررسی گروه‌بندی خاک با استفاده از مدل‌های خوشه‌بندی مرسوم و مدرن در بخش‌هایی از دشت قزوین

نوع مقاله : مقاله پژوهشی

نویسندگان

1 گروه علوم و مهندسی خاک، دانشکده کشاورزی، دانشکدگان کشاورزی و منابع طبیعی، دانشگاه تهران، کرج، ایران

2 عضو هیأت علمی گروه مهندسی علوم خاک، پردیس کشاورزی و منابع طبیعی دانشگاه تهران

3 بخش علوم و مهندسی خاک، دانشکده کشاورزی-دانشگاه شهیدباهنر کرمان

چکیده

خاک به عنوان یکی از اجزای اصلی دستیابی به اهداف توسعه پایدار، نقش مهمی در مدیریت مسائل محیط زیستی دارد. بنابراین، تفکیک خاک‌های با نیازهای مدیریتی مشابه ضروری می‌باشد. این امر باعث شده است که دانشمندان خاک‌شناسی از مدل‌های طبقه‌بندی عددی برای گروه‌بندی خاک‌ها بر اساس میزان شباهت آن‌ها استفاده کنند. از میان مدل‌های کمی ارائه‌ شده در این زمینه، مطالعه حاضر دو مدل خوشه‌بندی مرسوم و مدرن را برای گروه‌بندی خاک‌های اراضی قسمت‌هایی از دشت قزوین بکار برده است. بدین منظور، 297 خاکرخ مطالعه شده در منطقه بر اساس طیف گسترده‌ای از ویژگی‌های ریخت‌شناسی، فیزیکی-شیمیایی و محیطی آن‌ها با استفاده از مدل‌های خوشه‌بندی یک‌طرفه و دوطرفه مورد گروه‌بندی قرار گرفتند. گروه‌بندی‌های بدست آمده از این دو مدل بر اساس شاخص‌های ارزیابی درونی و بیرونی (با در نظر گرفتن نقشه توزیع زیرگروه‌های خاک به عنوان نقشه مرجع واقعیت زمینی) مورد بررسی قرار گرفت. نتایج نشان داد، مدل خوشه‌بندی سلسله مراتبی با میزان کم‌تر شاخص دویس-بولدین (38/1DB:) و افزایش میزان شاخص‌ رند تعدیل‌شده (49/0ARI: ) نسبت به مدل خوشه‌بندی دوطرفه کارایی بهتری دارد. با این حال، گروه‌بندی‌های بدست آمده از مدل خوشه‌بندی دوطرفه به میزان قابل قبولی با تغییرات پستی‌ و بلندی و تغییرات خاک‌ها در منطقه تطابق دارند. این امر با میزان شاخص تفرق شانن بیشتر در مدل خوشه‌بندی دوطرفه (82/1) نسبت به مدل خوشه‌بندی سلسله مراتبی (62/1) تایید می‌شود. بطورکلی یافته‌های این پژوهش، بر استفاده از مدل خوشه‌بندی دوطرفه به عنوان یک مدل داده کاوی مدرن در گروه‌بندی خاک‌ها و یافتن الگوی تشابه مدیریتی آن‌ها تاکید دارند.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Investigating soil grouping using conventional and modern clustering models in some parts of Qazvin plain

نویسندگان [English]

  • zahra rasaei 1
  • Fereydoon Sarmadian 2
  • Azam Jafari 3
1 Soil Science Department, Faculty of Agricultural, University College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran
2 soil science department< faculty of agricultural engineering and technology, university of Tehran
3 Department of Soil Science, Faculty of Agriculture, Shahid Bahonar University of Kerman
چکیده [English]

Soil is a crucial component in achieving sustainable development goals due to its significant role in addressing environmental challenges. It is essential to differentiate soils that have similar management requirements. This necessity has prompted soil scientists to employ numerical classification models to categorize soils based on their similarities. In this study, we utilized two types of clustering models, traditional and modern, to classify soils from certain areas of the Qazvin Plain. Using one-way and two-way clustering models, we grouped 297 soils from the region based on a comprehensive set of their morphological, physicochemical, and environmental attributes. The classifications derived from these two models were assessed using internal and external evaluation indicators, with the distribution map of soil subgroups serving as a ground truth reference map. The results indicated that the hierarchical clustering model, with a lower Davis-Bouldin index (DB: 1.38) and a higher adjusted Rand index (ARI: 0.49), outperformed the biclustering model. However, the classifications from the bidirectional clustering model corresponded reasonably well with the topographical and soil changes in the region, as evidenced by the higher Shannon’s difference index in the bidirectional clustering model (1.82) compared to the hierarchical clustering model (1.62). Overall, the study’s findings underscore the utility of the co-clustering model as a contemporary data mining technique for soil classification and identification of soil management similarity patterns.

کلیدواژه‌ها [English]

  • Co-clustering
  • Digital soil mapping
  • Hierachical clustering

EXTENDED ABSTRACT

Introduction

The classification of soils is crucial for their proper management and identification. Soil scientists have recognized the importance of numerical classification models for soil grouping. Creating continuous maps using digital mapping models allows for a better understanding of soil class distribution, aiding in improved soil management. Traditional clustering methods group soils based on their distinct properties, while two-way clustering methods group soils within subsets of similar characteristics. This study aims to compare the effectiveness of one-way and two-way clustering models in soil grouping and in identifying relationships between different soils.

Materials and Methods

This study utilized a dataset of 297 soil samples from some parts of the Qazvin plain. A broad spectrum of morphological, physicochemical, and environmental variables was used for soil grouping. The hierarchical clustering method was employed for one-way soil grouping, and the two-way clustering method was used for co-clustering of them. The Davis-Bouldin (DB) index was used to evaluate the groupings obtained from these models based on the degree of soil separation and intra-group variance. The Adjusted Rand Index (ARI) was used for external evaluation of groupings, with the distribution map of soil subgroups serving as a ground truth reference. Shannon’s entropy index was used to assess the efficiency of these models in representing soil variability in the study area.

Results and Discussion

The study found that both models were successful in differentiating the region's soils based on topographical and physiographic unit changes. However, the two-way clustering model demonstrated a slightly different pattern in soil separation, particularly in the central and southern parts of the study area. A numerical comparison of the results showed that the one-way clustering model provided better soil separation and less variance (DB: 1.38), and was more congruent with the distribution map of soil subgroups in the region (ARI: 0.49). The two-way clustering model effectively represented the pattern of soil changes in the study area, as evidenced by a higher Shannon index (1.82) compared to the hierarchical clustering model (1.62).

Conclusion

Although numerical comparative evaluations of the groupings reveal the superior efficiency of the hierarchical clustering model in separating soil groups, the two-way clustering model successfully grouped the region's soils according to their changes and the region's physiographic changes. This model also effectively represented soil changes in the region, as indicated by a higher Shannon entropy index. The study's findings affirm the efficacy of the two-way clustering model as a modern data mining technique in identifying similar soils and, consequently, in their grouping and modeling in digital soil mapping studies. The use of this model is recommended for examining soils in different parts of the country

Author Contributions

Conceptualization, Z.R., F.S. and A.J.; methodology, Z.R., and A.J.; software, Z.R.; validation, Z.R., and A.J.; formal analysis, Z.R.; investigation, Z.R., F.S. and A.J.; resources, Z.R. and F.S.; data curation, F.S.; writing—original draft preparation, Z.R.; writing—review and editing, Z.R., F.S. and A.J.; visualization, Z.R., F.S. and A.J.; supervision, F.S.; project administration, F.S.; funding acquisition, Z.R. All authors have read and agreed to the published version of the manuscript.

Data Availability Statement

Not applicable.

Acknowledgements

This work is based on research funded by the Iran National Science Foundation (INSF) under project No. 4024343. The first author would like to express her appreciation to the INSF for its financial support of this project, and to the University of Tehran for providing the conditions necessary for the completion of this project.

Ethical considerations

The study was approved by the Ethics Committee of the University of ABCD (Ethical code: IR.UT.RES.2024.500). The authors avoided data fabrication, falsification, plagiarism, and misconduct. 

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تحقیقات آب و خاک ایران
دوره 55، شماره 8
آبان 1403
صفحه 1273-1295

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