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Reseach Article

Comparative Analysis of Soil Properties for Influence of Fertilizers using Remote Sensing Techniques

by Vipin Y. Borole, Sonali B. Kulkarni
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 174 - Number 21
Year of Publication: 2021
Authors: Vipin Y. Borole, Sonali B. Kulkarni
10.5120/ijca2021921111

Vipin Y. Borole, Sonali B. Kulkarni . Comparative Analysis of Soil Properties for Influence of Fertilizers using Remote Sensing Techniques. International Journal of Computer Applications. 174, 21 ( Feb 2021), 24-34. DOI=10.5120/ijca2021921111

@article{ 10.5120/ijca2021921111,
author = { Vipin Y. Borole, Sonali B. Kulkarni },
title = { Comparative Analysis of Soil Properties for Influence of Fertilizers using Remote Sensing Techniques },
journal = { International Journal of Computer Applications },
issue_date = { Feb 2021 },
volume = { 174 },
number = { 21 },
month = { Feb },
year = { 2021 },
issn = { 0975-8887 },
pages = { 24-34 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume174/number21/31798-2021921111/ },
doi = { 10.5120/ijca2021921111 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:22:44.179465+05:30
%A Vipin Y. Borole
%A Sonali B. Kulkarni
%T Comparative Analysis of Soil Properties for Influence of Fertilizers using Remote Sensing Techniques
%J International Journal of Computer Applications
%@ 0975-8887
%V 174
%N 21
%P 24-34
%D 2021
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Soil properties assessment is critical for agricultural, environmental management. Regular soil assessment laboratory methods are very time consuming and expensive. For this work ground based remote sensing methods using spectroscopy technique was used in laboratory for soil properties assessment. Whereas spectral signature obtaining the diffused reflectance from spectroradiometer data is used. The different statistical methods are used for get the quantitative results of the acquired spectral data. By using this innovative technique comparative analysis of collected soil samples in premonsoon and postmonsoon was execute for finding the influence of fertilizers in different seasons. Soil samples are collected in context of surface and subsurface in premonsoon and post monsoon season for analyzing the influence of fertilizers on soil quality in banana and cotton crops soil. Soil properties analysis including chemical properties like nitrogen, phosphorus, potash, carbon, pH as well as physical properties like sand, silt, clay, soil organic matter (SOM), moisture were measured. The major difference is found in the availability of soil contents are higher in premonsoon season than postmonsoon season soil samples. Thus, this study implied that spectroscopic ground based remote sensing data based method provided great potential to analyze the soil properties.

References
  1. Okoffo E. D., Ofori A., Nkoom M., Bosompem O.A., “ Assessment of the physicochemical Characterristics of soils in major Cocoa producing areas in the dormaa west district of Ghana”, International Journal of Scientific & Technology Research , Vol. 5, issue 02, feb. 2016, PP. 62-68
  2. Vipin Y. Borole, Sonali B. Kulkarni, Pratibha R. Bhise, “Effect of fertilizers on soil properties for different crops in pre-monsoon season using spectroradiometer for raver tehsil of jalgaon district”, International Journal of Scientific and Technology Research, Volume 9, Issue 2, February 2020, PP. 844-849
  3. Suzana Romeiro Araujo, Jose Alexandre Melo Dematte, Henrique Bellinaso, “ Analysing the effect of applying agricultural lime to soils by VNIR spectral sensing:a quantitative and quick method”, International Journal of Remote sensing, Tylor &Francis, Vol.34, no. 13, PP. 4570-4584
  4. Huan Yu, Bo Kong, Guangxing Wang, Rongxiang Du, Guangping Qie, “Prediction Of Soil Properties Using A Hyperspectral Remote Sensing Method”, Archives Of Agronomy And Soil Science, Taylor & Francis Group, 2017
  5. Tarik Mitran, T. Ravisankar, M.A. Fyzee, Janaki Rama Suresh, G. Sujatha & K. Sreenivas, “Retrieval of soil physicochemical properties towards assessing salt-affected soils using Hyperspectral Data”, Geocarto International, 30:6,2015, PP.701-721
  6. Naxin Cui, Min Cai, Xu Zhang, Ahmed A. Abdelhafez, Li Zhou, Huifeng Sun, Guifa Chen, Guoyan Zou, Sheng Zhou, “Runoff loss of nitrogen and phosphorus from a rice paddy field in the east of China: Effects of long-term chemical N fertilizer and organic manure applications”, Global Ecology and Conservation, Elsevier,22 , March 2020, PP.1-12
  7. Bhise Pratibha.R, Kulkarni Sonali.B “Remote Sensing and Data Mining Techniques Applied on Soil Characteristics Data Classification”, IOSR Journal of Computer Engineering (IOSR-JCE), PP. 83-91
  8. P.R. Bhise, S.B. Kulkarni, “Evaluation of Soil Physical/Chemical Parameters for Agriculture Production in Vaijapur Taluka Using VNIR-SWIR Reflectance Spectroscopy”, International Journal of Computer Sciences and Engineering, Vol.-6, Issue-12, Dec 2018, PP. 43-48
  9. Vipin Y. Borole, Sonali B. Kulkarni, “Soil quality assessment for analyzing the effect of chemical fertilizers on agriculture field using Spectroradiometer: A review”, International Conference on Electrical, Communication, Electronics, Instrumentation and Computing (ICECEIC), IEEE, 2019
  10. Mansour Chaternour, Ahmad Landi, Ahmad Farrokhian Firouzi, Aliakbar Noroozi, Hosseinali Bahrami, “Spectral behavior modeling of soil texture over dust center of Khuzestan Province using hyperspectral images and Random Forest (RF) model”, Vol 9 (4), Oct 2019, PP.466-479
  11. Ramdas D. Gore, Sunil S. Nimbhore, Bharti W.Gawali, “Understanding Soil Spectral Signature Though RS and GIS Techniques”, International Journal of Engineering Research and General Science Volume 3, Issue 6, November-December, 2015, pp. 866-872
  12. Pratibha R.Bhise , Sonali B.Kulkarni, “Estimation of Soil Macronutrients From Spectral Signatures Using Hyperspectral Non-Imaging Data”, International Conference on Electrical, Communication, Electronics, Instrumentation and Computing (ICECEIC), IEEE, 2019
  13. Pratibha R.Bhise , Sonali B.Kulkarni, “Review on Analysis and Classification Techniques of Soil Study in Remote Sensing and Geographic Information System”, International Journal of Emerging Trends & Technology in Computer Science (IJETTCS), Volume 6, Issue 1, pp.124-138
  14. Pratibha R.Bhise , Sonali B.Kulkarni, Vipin Y. Borole.,” Preprocessing and statistical analysis of soil parameters using conventional laboratory techniques and non-imaging spectral techniques for Vaijapur taluka”, International Journal of Recent Technology and Engineering, Volume 8, Issue 2, July 2019, PP. 3092-3096
  15. Tiezhu Shi, Junjie wang, Huizeng Liu, Guofeng Wu, “Estimating leaf nitrogen concentration in heterogeneous crop plants from hyperspectral reflectance”, International Journal of Remote Sensing, Vol. 36, No. 18, Oct 2015, PP.4652-4667
  16. Nataliia Ridei, Vita Strokal, Maryna Strokal, “Soil Quality classes for characterizing the soil potential to produce biologically and ecologically valuable crops”, Archives of Agronomy and soil Science, Vol. 58, No. S1. Oct 2012 PP. 219-225
  17. Vipin Y. Borole, Sonali B. Kulkarni, Pratibha R. Bhise, “Soil spectral signature analysis for influence of fertilizers on two differen crops in raver Tahshil”, International Journal of Recent Technology and Engineering, Volume-8, Issue-3, Sep-2019, pp. 659-663
  18. Ramdas D. Gore, Reena H. Chaudhari, and Bharti W. Gawali , “Creation of Soil Spectral Library for Marathwada Region” , International Journal of Advanced Remote Sensing and GIS, Volume 5, Issue 6,2016, pp. 1787-1794
  19. GUO Wei, Mathias N Andersen, QI Xue-bin, LI Ping, LI Zhong-yang, FAN Xiang-yang, ZHOU Yuan, “Effects of reclaimed water irrigation and nitrogen fertilization on the chemical properties and microbial community of soil”, Journal of Integrative Agriculture, Elsevier, Volume16, issue 3, 2017, PP, 679–690
  20. Offer Rozenstein, Tarin Paz-Kagan, Christoph Salbach, and Arnon Karnieli, “Comparing the Effect of Preprocessing Transformations on Methods of Land-Use Classification Derived From Spectral Soil Measurements”, IEEE Journal Of Selected Topics In Applied Earth Observations And Remote Sensing, PP 1-12
  21. Talli Ilani, Ittai Herrmann, Arnon Karnieli, Gilboa Arye, “Characterization of the biosolids composting process by hyperspectral analysis”, Elsevier Ltd., Waste Management 48, 2016, pp.106–114
  22. Haijun Qi, Tarin Paz-Kagan, Arnon Karnieli, Shaowen Li, “Linear Multi-Task Learning for Predicting Soil Properties Using Field Spectroscopy”, Remote Sens. 2017
  23. Haijun Qi, Tarin Paz-Kagan, Arnon Karnieli, Xiu Jin, Shaowen Li, “Evaluating calibration methods for predicting soil available nutrients using hyperspectral VNIR data”, Soil & Tillage Research, issue 175, 2018, pp.267–275
  24. Vipin Y. Borole, Sonali B. Kulkarni, “Spectral data analysis methods for soil properties assessment using remote sensing”, IOSR Journal of Computer Engineering (IOSR-JCE), Volume 23, Issue 1, Jan. – Feb. 2021, PP 14-18
  25. S.K. Reza, D.C. Nayak, T. Chattopadhyay, S. Mukhopadhyay, S.K. Singh & R. Srinivasan, “Spatial distribution of soil physical properties of alluvial soils: a geostatistical approach”,Archives Of Agronomy And Soil Science, Taylor & Francis, Vol. 62, NO. 7, Page No. 972–981, 2016
  26. Amol D. Vibhute, K. V. Kale, Rajesh K. Dhumal, S. C. Mehrotra, “Soil Type Classification and Mapping using Hyperspectral Remote Sensing Data”, International Conference on Man and Machine Interfacing (MAMI), IEEE, 2015.
  27. Vipin Y.Borole, Sonali B.Kulkarni, Pratibha R. Bhise.” Soil Properties Assessment In Surface And Subsurface Using Spectroradiometer For Raver Tehsil Of Jalgaon District”, Journal of critical reviews 7(18), 2020, PP. 2487-2495
Index Terms

Computer Science
Information Sciences

Keywords

Crops Chemical properties Fertilizers Physical properties Remote Sensing Spectroradiometer