Exploring Soil Diversity and Land Use Patterns in Arid Tropical Zones: Employing K-Means Clustering in Kolar District, Karnataka
Abstract
This paper explores the crucial relationship between soil quality and agricultural productivity, emphasizing the pivotal role of soil in sustaining human life. Focusing on the agricultural heritage of Kolar District, Karnataka, India, and its contemporary challenges such as soil degradation, the study employs the clustering technique of data mining to analyze physicochemical soil properties. By applying K-means clustering, the research identifies distinct soil characteristics in various regions of Kolar, providing valuable insights for farmers to optimize agricultural practices. Through statistical analysis and evaluation using the Rattle tool of R-Analytics, the study elucidates practical strategies for improving soil fertility and enhancing crop yields. This work serves as a foundation for informed decision-making in agriculture, addressing the urgent need to understand and mitigate soil quality issues to ensure sustainable food production and livelihoods.
References
[1]
Karthick D, Vijayrekha K, and Manickkam V Land characterization based on soil properties using clustering techniques World Appl Sci J 2014 29 60-64
[2]
Vibha L, Harsha Vardhan GM, et al. A hybrid clustering and classification technique for soil data mining. In: IET-UK International Conference on Information and Communication Technology in Electrical Sciences (ICTES 2007), Dec 20–22, 2007. 2007. p. 1090–95.
[3]
Bhargavi P and Jyothi S Applying Naïve Bayes data mining techniques for classifications of agricultural soils Int J Comput Sci Netw Secur 2009 9 8 117-122
[4]
Mattson B, Cederberg C, and Blix L Agricultural land use in life cycle assessment (LCA): case studies of three vegetable oil crops J Clean Prod 2000 8 283-292
[5]
Siva Prasad PN, Subbarayappa CT, et al. Qualifying and mapping of major, secondary and micronutrient status of tomato growing soils in Kolar District, Karnataka using GIS and GPS approach Int J Plant Soil Sci 2020 32 14 14-27
[6]
Ganeshmurthy AN, Satisha GC, and Prakash P Potassium nutrition on yield and quality of fruit crops with special emphasis on banana and grapes Karnataka J Agric Sci 2011 24 1 29-38
[7]
Mishra A, Das D, and Saran S Preparation of GPS and GIS based soil fertility maps for Khurda District, Odisha Indian Agric J 2013 57 1 11-20
[8]
Satish A, Rmachandrappa BK, Devaraja K, Savitha MS, Thimmegowda MS, and Prashant KM Assessment of spatial variability in fertility status and nutrient status and recommendation in Alanatha Cluster Villages, Kanakpura Taluka, Ramnagara District using GIS techniques Int J Curr Microbiol Appl Sci. 2017 6 5 211-224
[9]
Padmavathi T, Muthukrishnan R, Mani S, and Sivasamy R Assessment of soil physical, chemical properties and micro nutrient status in Coimbatore district of Tamilnadu using GIS techniques Trends Bio Sci 2014 7 19 2879-2881
[10]
Cierniewski J, Kazimerowski C, et al. Unsupervised clustering of soil spectral curves to obtain their stronger correlation with soil properties. In: 2010 IEEE Explorer 978-1-4244-8907-7/10
[11]
Visara Rossel RA, Wavelvort DJJ, Mac Bartney AB, et al. Visible, near infrared mid infrared or diffuse reflectance spectroscopy simultaneous assessment of various oil properties Geoderma 2006 131 59-75
[12]
Hot E and Popovic-Burgarin V Soil data clustering using K means and fuzzy K means algorithm Teflor J 2016 8 1 56-61
[13]
GhoshS, Dubey SK. Comparative analysis of K-means and fuzzy C means algorithms. (IJACSA) Int J Adv Comput Sci Appl. 2013;4(4).
[14]
Suganya R and Shanthi R Fuzzy C means algorithm—a review Int J Sci Res Publ 2012 2 11 1
[15]
Chattopdhaya S, Kumar Pratihar D, and Sarkar SCD A comparative study of fuzzy c means algorithm and entropy based fuzzy clustering algorithm Comput Inform 2011 30 701-720
[16]
Rokach L, Marimon O. Clustering methods. In: The data mining and knowledge discovery handbook. 2005. p. 321–52.
[17]
Singearvelu S, Sherin A, Savitha S. Agglomerative fuzzy K-means clustering algorithm. Nehru E J Arts Sci College (NACS) Res Article.
[18]
Kumar A, Kannanathsan N. A survey on data mining and pattern recognition techniques for soil data mining. IJCSI Int J Comput Sci Issue. 2011;8(3).
[19]
Rajeshwari V, Arunesh K. Analysing soil data using data mining classification techniques. Indian J Sci Technol. 2016;9(19).
[20]
Jain AK, Murthy MN, and Flynn PJ Data clustering: a review ACM Comput Surv (CSUR) 1999 31 3 264-323
[21]
Berkin P A survey of clustering data mining techniques, Grouping multidimensional data 2006 Berlin Springer 25-71
[22]
Geetha M A survey on data mining techniques in agriculture Int J Innov Res Comput Commun Eng 2015 3 2 887-892
[23]
Fu Q, Wang Z, and Jiang Q Delineating soil nutrient management zones based on fuzzy clustering optimized by PSO Math Comput Model 2010 51 11 1299-1305
[24]
Murgan D, Maurya AK, Garg A, and Singh D A framework for high resolution soil moisture extraction using SCATSAT-1 scatterometer data Int Res J Pure Appl Chem. 2020 21 215-224
Index Terms
- Exploring Soil Diversity and Land Use Patterns in Arid Tropical Zones: Employing K-Means Clustering in Kolar District, Karnataka
Index terms have been assigned to the content through auto-classification.
Recommendations
Smart Soil Property Analysis Using IoT: A Case Study Implementation in Backyard Gardening
AbstractCrop growth and the agricultural ecosystem are both affected by inappropriate soil fertility ranges. Soil fertility management practices help to efficient use of fertilizer and organic compost and selecting appropriate crops based on soil ...
Delineation of management zones with soil apparent electrical conductivity to improve nutrient management
The apparent electrical conductivity (ECa) was measured in excessively drained to imperfect soils.The ECa was a potential estimator of soil properties and nutrients.The ECa measurements successfully delimited two homogeneous soil zones.The ECa maps have ...
Determination of management zones for a tobacco field based on soil fertility
Present nutrient management recommendations for flue-cured tobacco (Nicotiana tabacum) in Central China are typically uniform for large regions. This results in over-application in areas with high nutrient levels and under-application in areas with low ...
Comments
Please enable JavaScript to view thecomments powered by Disqus.Information & Contributors
Information
Published In
© The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
Publisher
Springer-Verlag
Berlin, Heidelberg
Publication History
Published: 30 September 2024
Accepted: 29 June 2024
Received: 08 June 2024
Author Tags
Qualifiers
- Research-article
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 0Total Downloads
- Downloads (Last 12 months)0
- Downloads (Last 6 weeks)0
Reflects downloads up to 20 Nov 2024
Other Metrics
Citations
View Options
View options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in