HYDROLOGICAL SOIL CLASSIFICATION – A FUZZY APPROACH
H.A.S Sandhu
Assistant Professor, PEC Chandigarh, Punjab, India
O.P. Dubey
Visiting Professor, IIT Roorkee, Roorkee India
84-95
Vol: 6, Issue: 2, 2016
Receiving Date:
2016-03-04
Acceptance Date:
2016-04-05
Publication Date:
2016-05-01
Download PDF
Abstract
Hydrological response of an area is influenced by the soil characteristics of that area. Hydrological Soil
Classification (HSC) refers to a group of soil series that can be considered homogeneous in respect of soil
characteristics that influence the run-off. The HSC is required for a spectrum of hydrological applications by
agriculturists, engineers and soil conservationists. The main soil parameters considered for the HSC are effective
depth, soil texture, clay percentage, and infiltration. It has been observed that generally uncertainty prevails in
various classification approaches.
In the present study hydrological soil classification has been carried out using Fuzzy Logic. Fuzzy Classification
deals with approximate modes of reasoning. Its chain of reasoning is short and everything in it is a matter of
degree. This degree is represented by membership function. This function can be generalized such that the values
assigned to the elements of a set fall within a range of 0 to 1.
During this work, it has been observed that while using Soil Conservation Services (SCS) approach for HSC, it is
difficult to draw definite conclusions. While Maximum Likelihood Classifier (MLC) yields a definite group but it
assumes soil boundaries to be crisp. This assumption is generally not valid in nature. To remove the uncertainty
present in the classification, Fuzzy Maximum Likelihood Classifier (FMLC) approach was used. For this
membership functions for various properties of the soil were generated in the MATLAB environment and these were
incorporated for soil classification..
Keywords:
Hydrological Soil Classification, Maximum Likelihood Classifier, Fuzzy Maximum Likelihood Classifier, Remote Sensing
References
- American Society of Photogrammetry (1975) 1st edition Manual of Remote Sensing, Vol 1,2, Falls Church, Virginia, U.S.A
- Batlivala. P.P and F.T.Ukaby (1977) Estimation of soil moistures with radar remote sensing envioronment, Vol 2, P 57-66
- Bedzeck,J.C., Robert Ehrlick and Willium Full, (1984), FCM : The Fuzzy c-mean clustering algorithm, computer and geosciences, 10,191-203
- Chethanambe. K.R (1999), A fuzzy Image Classification Package for Remotely Sensed Data, M.E. Thesis, IIT Roorkee.
- FANG Fuzzy Logic page, www.ie.ncsu.ed/fangroup/fuzzy.dir/indexfuzzyhtml
- F..A.O Soils Bulletin -42 “Soil Survey investigation for irrigation”, FAO Rome
- Fisher,P.F. and S.Pathirana, (1990), The fuzzy membership of land cover classes in the sub urban zone, Remote Sensing of Environment, 34, 121-132
- Food, G.M., (1916), Approaches for the production and evaluation of fuzzy land cover classification for remotely sensed data, International Journal of Remote Sensing 17, 1317-1340
- Fuzzy Logic and Fuzzy Expert System, available at www.cs.cmu.edu/Groups/AI/HTML/faqs/AI / fuzzy/faq-doc-0.html
- Fuzzy logic FAQ, www.mbhs.edu/-lpiper/ai99/fuzzy-logic/questions/html
- Fuzzy archive, www.dbai.tuwien.ac.at/marchives/fuzzy-mail97/0366.html
- Gebermann,A.H. and D.P.Nehar,(1979)- Reflectance of varying Mixtures of clay, soil, and Sand; Photogrammetric Engineering and Remote Sensing, No.45, No8, P 1145-1151
- Ghosh,J.K.,(1996), Mapping of Tea Garden from Satellite Imageries- A fuzzy knowledge based Image interpretation System, Ph.D Thesis, IIT Roorkee
- Gopal,S., and Woodock, C.,(1994) Theory and methods for accuracy assessment of thematic maps using fuzzy sets, PE & RS, 60, 180-181
- Goosen.D. (1967) Aerial Photo-interpretation in soil surveys, Soil Bulletin 6, FAO Rome
- Govindrajan,S.V. and H.G. Gopala Rao, (1978), Studies on soils of India.
- Hydrological Soil Classification (1985-86), NIH Report CS-15, National Institute of Hydrology, Roorkee
- Hydrological Soil Classification, available at http://www.mluri.sari.ac.uk/hstobn.htm
- Hydrology (Section) 1972 – Soil Conservation Services (SCS), National Engineering Aerial Book, USA (Chapter -7)
- Idmonds,D.T., R.D., Painter, G.D. Ashley,(1970) A semi-quantitative Hydrological classification of soils in North-East England, Journal of Soil SCIENCE.Vol 21(2), P 256-264
- Klier& Yuan (1997), Fuzzy Sets and Fuzzy Logic, PHI, India
- Lillesand and Keifer (1989), Remote Sensing and Image Interpretation, 3rd Edition, John Willy and Sons
- Page Soil Classification (1997), http://www.civil.colorado.edu/coursewaare/mosven/ce/3.2/ texts/ soil class.html
- Prakash and Jain (1990), Engineering Soil Testing, Nem Chand & Bros., Roorkee.
- PredGully,J.S.Roger and Jan Fuzzy logic tool box, MATLAB
- Punmia B.C. (1994), Soil Mechanics and Foundation Engineering, Laxmi Publications (P) Ltd.
- Raghunath,H.M., (1985) Principles, Analysis and design, Reference Hydrology, Wiley Eastern Limited, New Delhi
- Ragini Sinha (1998) Hydrological Soil Classification using GIS Techniques, M.E. Thesis., IIT Roorkee
- Simson,S. (1975) Soil Textonomy A basic system of Soil Classification for interpretaing soil surveys, Soil Surveys Staff USDA Handbook No 436., US Govt Printing Office,.D.C.
- Singh, Nirmal (2000) Fuzzy Logic A new Trend, The Tribune (News Paper) PP9
- Singh,Hukam, Yadav,S.K. and Roy,B.P. (1995-1996), Hydrological Soil Classification of SherBarewa River Doab (CS(AR)-215).,NIH., Roorkee
- Singh,Hukam., Singh Maohar and Kumar, Sudhir (CS(AR)-5/96-97), Hydrologiical Soil Classification of Sher Umar River Doab, NIH, Roorkee
- Shah (1987), Hydrological measurements, http://www.scas.cornell.edu/landeval.notes / s 48 ch6p.htm
- Soil Survey Manual of India (1970) India Agriculture Research Institute
- Sony B. and Mishra G.C. (1984-85) Hydrological Soil Classification, National Insutitute of Hydrology:RN-6, Roorkee,pp3-12
- Wang, F. (1990), Fuzzy supervised classification of remotely sensed images, IEEE Transaction on Geosciences and Remote Sensing, 28, 194-201
- Wang, F. (1990), Improving Remote Sensing Image Analysis through fuzzy, Information Representation, PE & RS, Vol 56, No8 , PP 1163-1169
- Zadeh,L.A (1965), Fuzzy sets, Information and Control, Vol 8 , pp 353-383
- Zadeh,L.A (1988), Fuzzy ligic, compiters, Vol21, No4, pp 83-93
- Zimmermann,H.J. (1988), Fuzzy Set Theory nd its applications, Prentice Hall India
Back
