Skip to main content
Log in

Distribution and evolutionary of turfy soil identified by remote-sensing images based on fuzzy evaluation

  • Published:
Multimedia Tools and Applications Aims and scope Submit manuscript

Abstract

Turfy soil is a kind of special soil accumulated by undecomposed plants which is detrimental to the engineering. In this paper, particular identified patterns for the turfy soil in the northeast of China was raised including the method of extracting threshold value, block analysis and fuzzy evaluation. And field investigations were undertaken to verify the accuracy of identification by remote sensing, and the correlation of field result and remote sensing result was summarized so as to analyze the regularities of distribution and evolutionary mechanism of turfy soil. The result shows that the combination of extracting threshold value, block analysis and fuzzy evaluation are effective methods to predict the distribution of the turfy soil; with the correlation of membership degree and field result, we can analyze the evolutionary mechanism of turfy soil affected by both nature factors and human activities, which is beneficial for the preservation of the turfy soil and also shows significant environmental ecological benefit.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

Similar content being viewed by others

References

  1. Bai X, He B (2015) Potential of Dubois model for soil moisture retrieval in prairie areas using SAR and optical data. Int J Remote Sensing 36 (22)

  2. Bai X, He B, Xing M (2015) Method for soil moisture retrieval in arid prairie using TerraSAR-X data. J Appl Remote Sens 9(1)

  3. Bocco M, Sayago S, Willington E (2015) Neural network and crop residue index multiband models for estimating crop residue cover from Landsat TM and ETM+ images. Int J Remote Sensing 35 (10)

  4. Boughrara H, Chtourou M, Chokri BA (2016) Facial expression recognition based on a mlp neural network using constructive training algorithm. Multimed ToolsAppl 75(2):709–731

    Article  Google Scholar 

  5. Boylan N et al (2008) Peat slope failure in Ireland. Q J Eng Geol Hydrogeol 41:93–108

    Article  Google Scholar 

  6. Bricker SH et al (2014) Controls on the basin-scale distribution of hydraulic conductivity of superficial deposits: a case study from the Thames Basin, UK. Q J Eng Geol Hydrogeol 47(3):223–236

    Article  Google Scholar 

  7. Campbell J (1996) Introduction to remote sensing, 2nd edn. Taylor and Francis, London

    Google Scholar 

  8. Canters F (1997) Evaluating the uncertainty of area estimates derived from fuzzy land-cover classification. Photogramm Eng Remote Sens 63:403–414

    Google Scholar 

  9. Chapin F III, Zavaleta E, Eviner V, Naylor R, Vitousek P, Reynolds H, Hooper D, Lavorel S, Sala O, Hobbie S, Mack M, Diaz S (2000) Consequences of changing biodiversity. Nature 405:234–242

    Article  Google Scholar 

  10. Chen N, Li J, Zhang X (2015) Quantitative evaluation of observation capability of GF-1 wide field of view sensors for soil moisture inversion. J Appl Remote Sens 9(1)

  11. Du Y, Lu X, Chen L (2016) An interval type-2 T-S fuzzy classification system based on PSO and SVM for gender recognition. Multimed Tools Appl 75(2):987–1007

    Article  Google Scholar 

  12. Dykes A et al (2008) Peat slope failures and other mass movements in western Ireland. Q J Eng Geol Hydrogeol 44:5–16

    Article  Google Scholar 

  13. Friedl M, McIver D, Hodges J, Zhang X, Muchoney D, Strahler A (2002) Global land cover mapping from MODIS: algorithms and early results. Remote Sens Environ 83(1):287–302

    Article  Google Scholar 

  14. Godio A et al (2014) Coupling ground-penetrating radar and flowmeter investigations for the characterization of a fissured aquifer. Q J Eng Geol Hydrogeol 47(4):351–361

    Article  Google Scholar 

  15. Goodin, DG, Anibas KL, Bezymennyi M (2015) Mapping land cover and land use from object-based classification: an example from a complex agricultural landscape. Int J Remote Sensing 36(18)

  16. Gropius M (2010) Numerical groundwater flow and heat transport modelling of open-loop ground source heat systems in the London Chalk. Q J Eng Geol Hydrogeol 43(1):23–32

    Article  Google Scholar 

  17. Guellala R, Abidi M, Balti N (2016) Geophysical prospecting for groundwater exploration in northwestern Tunisia. Hydrol Sci J-J Des Sciences Hydrol 61(3):636–645

    Article  Google Scholar 

  18. Han Y, Shi X, Che G (2012) Experimental study on the frost heaving characteristics of turfy Soil Foundation. Inform Bus Intell 267(599-605)

  19. Hao L, Zhao X, Boorder D, Hu G (2014) Origin of PGE depletion of Triassic magmatic Cu-Ni sulfide deposits in the central-southern area of Jilin province. NE Chin, ORE Geol Rev 63:226–237

    Article  Google Scholar 

  20. He T, Sun Y, Xu J (2015) Enhanced land use/cover classification using support vector machines and fuzzy k-means clustering algorithms. J Appl Remote Sens 8(1)

  21. Hu C, Xu Z et al (2015) Video structured description technology for the new generation video surveillance system. Front Comput Sci 9(6):980–989

    Article  Google Scholar 

  22. Huang Z, Chau K (2007) A new image thresholding method based on Gaussian mixture model. Appl Math Comput 205(2):899–907

    MathSciNet  MATH  Google Scholar 

  23. Işık Y et al (2015) Rock mass parameters based doline susceptibility mapping in gypsum terrain. Q J Eng Geol Hydrogeol 48:124–134

    Article  Google Scholar 

  24. Jenicka S, Suruliandi A (2014) Fuzzy texture model and support vector machine hybridization for land cover classification of remotely sensed images. J Appl Remote Sens 8(1)

  25. Kalra G, Singh S (2016) Efficient digital image denoising for gray scale images. Multimed Tools Appl 75(8):4467–4484

    Article  Google Scholar 

  26. Krankina O, Pflugmacher D, McGuire HAD, Hansen MC, Häme T, Elsakov V, Nelson P (2011) Vegetation cover in the eurasian arctic: distribution, monitoring, and role in carbon cycling. In: Gutman G, Reissell A (eds) Eurasian Arctic Land Cover and Land Use in a Changing Climate. Springer, New York, pp 79–108

    Google Scholar 

  27. Kumar P, Gupta DK, Mishra, VN (2015) Comparison of support vector machine, artificial neural network, and spectral angle mapper algorithms for crop classification using LISS IV data. Int J Remote Sensing 36 (6)

  28. Lee E, Fooke P (2015) A note on the origins of engineering geomorphology in the UK. Q J Eng Geol Hydrogeol 10(1144):147–156

    Article  Google Scholar 

  29. Lei N, Su Z (2015) Study on mineral distribution of peat soil in Northeast of China. Asian J Chem 25(18):10150–10152

    Google Scholar 

  30. Liao K, Xu S, Wu J (2013) Spatial estimation of surface soil texture using remote sensing data. Soil Sci Plant Nutri 59(4):488–500

    Article  Google Scholar 

  31. Liu Y, Cao G, Meng Y (2014) study on the microstructure feature and strength mechanism of the Tien Lake peat soil. Environ Eng 864-867(2695-2702)

  32. Liu T, Miao Q, Xu P (2016) Color topographical map segmentation Algorithm based on linear element features. Multimed Tools Appl 75(10):5417–5438

    Article  Google Scholar 

  33. Lv Y, Nie L, Xu K (2012) Study on the difference between turfy soil and normal peat soil in China. Vibration, Struct Eng Measurement I, 105–107 ( 1551–1554)

  34. Maxwell AE, Warner TA (2015) Differentiating mine-reclaimed grasslands from spectrally similar land cover using terrain variables and object-based machine learning classification. Int J Remote Sensing 36 (17)

  35. Meyer W, Turner B II (eds) (1994) Changes in land use and land cover: a global perspective. Cambridge University Press, Cambridge, pp 437–471

    Google Scholar 

  36. Michael L, Boylan N (2013) Predictions of settlement in peat soils. Q J Eng Geol Hydrogeol 46(3):303–322

    Article  Google Scholar 

  37. Nie L et al (2012) Influence of organic content and degree of decomposition on the engineering properties of a peat soil in NE China. Q J Eng Geol Hydrogeol 45(4):435–446

    Article  Google Scholar 

  38. Osinowo Olawale O, Olayinka AI (2012) Very low frequency electromagnetic (VLF-EM) and electrical resistivity (ER) investigation for groundwater potential evaluation in a complex geological terrain around the Ijebu-Ode transition zone, southwestern Nigeria. J Geophys Eng 9(4):374–396

    Article  Google Scholar 

  39. Pont D, Kimberley MO, Brownlie RK (2015) Calibrated tree counting on remotely sensed images of planted forests. Int J Remote Sensing 36 (15)

  40. Reschke J, Bartsch A, Schlaffer S, Schepaschenko D (2012) Capability of C-Band SAR for operational wetland monitoring at high latitudes. Remote Sens 4(10):2923–2943

    Article  Google Scholar 

  41. Saha S, Basu S, Nasipuri M (2015) iLPR: an Indian license plate recognition system. Multimed Tools Appl 74(23):10621–10656

    Article  Google Scholar 

  42. Sela S, Svoray T, Assouline S (2014) Soil surface sealing effect on soil moisture at a semiarid hillslope: implications for remote sensing estimation. Remote Sens 6(8):7469–7490

    Article  Google Scholar 

  43. Singh PP, Garg RD (2014) Classification of high resolution satellite images using spatial constraints-based fuzzy clustering. J Appl Remote Sens 8(1). doi:10.1117/1.JRS.8.083526

  44. Tang S, Nie L, Qiao D (2012) Study on the difference between multipotiential surface model and Duncan-Chang model based on the triaxial test of Heda highway turfy soil. Mater Process Technol II, 538-541(965-970)

  45. Wang Y, Wang S, Yang S (2014) Using a remote sensing driven model to analyze effect of land use on soil moisture in the Weihe River Basin, China. IEEE J Select Topics Appl Earth Observ Remote Sens 7(9):3892–3902

    Article  Google Scholar 

  46. Xu H, Jin Y, Liu X (2006) The climatic effect of Carex. meyeriana mire in the Changbai Mountain valley. Ecol Environ 15(1):120–123

    Google Scholar 

  47. Xu C, Sui H, Li H (2015) An automatic optical and SAR image registration method with iterative level set segmentation and SIFT. Int J Remote Sensing 36 (15)

  48. Xu Z et al (2015) Semantic based representing and organizing surveillance big data using video structural description technology. J Syst Software 102:217–225

    Article  Google Scholar 

  49. Xu Z et al (2016) Semantic enhanced cloud environment for surveillance data management using video structural description. Computing 98(1-2):35–54

    Article  MathSciNet  MATH  Google Scholar 

  50. Yan Y, Zhu J, Yan Q (2014) Modeling shallow groundwater levels in Horqin Sandy Land, North China, using satellite-based remote sensing images. J Appl Remote Sens 8(1):083647

    Article  Google Scholar 

  51. Zakeri F, Zoej MJ (2015) Adaptive method of speckle reduction based on curvelet transform and thresholding neural network in synthetic aperture radar images. J Appl Remote Sens 9(1)

  52. Zhang T, Jiang L, Zhao T (2014) Soil temperature independent algorithm for estimating bare surface soil moisture. J Appl Remote Sens 8(1):083558

    Article  Google Scholar 

  53. Zhu A, Qi F, Moore A (2010) Prediction of soil properties using fuzzy membership values. Geoderma 158(3-4):199–206

    Article  Google Scholar 

Download references

Acknowledgments

This project was financially supported by the National Natural Science Foundation of China (Grant NO. 41502272, Grant NO.41572254), the Basic Research Foundation of Jilin University (Grant NO.450060491447), Science and Technology Development Program of Jilin Province (Grant NO.20150520077JH) and China Postdoctoral Science Foundation (Grant No. 2014M551453). All of them are gratefully acknowledged.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Lei Nie.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Nie, L., Huang, Y. & Xu, Y. Distribution and evolutionary of turfy soil identified by remote-sensing images based on fuzzy evaluation. Multimed Tools Appl 76, 14635–14651 (2017). https://doi.org/10.1007/s11042-016-3842-z

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-016-3842-z

Keywords

Navigation