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.
Similar content being viewed by others
References
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)
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)
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)
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
Boylan N et al (2008) Peat slope failure in Ireland. Q J Eng Geol Hydrogeol 41:93–108
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
Campbell J (1996) Introduction to remote sensing, 2nd edn. Taylor and Francis, London
Canters F (1997) Evaluating the uncertainty of area estimates derived from fuzzy land-cover classification. Photogramm Eng Remote Sens 63:403–414
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
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)
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
Dykes A et al (2008) Peat slope failures and other mass movements in western Ireland. Q J Eng Geol Hydrogeol 44:5–16
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
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
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)
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
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
Han Y, Shi X, Che G (2012) Experimental study on the frost heaving characteristics of turfy Soil Foundation. Inform Bus Intell 267(599-605)
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
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)
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
Huang Z, Chau K (2007) A new image thresholding method based on Gaussian mixture model. Appl Math Comput 205(2):899–907
Işık Y et al (2015) Rock mass parameters based doline susceptibility mapping in gypsum terrain. Q J Eng Geol Hydrogeol 48:124–134
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)
Kalra G, Singh S (2016) Efficient digital image denoising for gray scale images. Multimed Tools Appl 75(8):4467–4484
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
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)
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
Lei N, Su Z (2015) Study on mineral distribution of peat soil in Northeast of China. Asian J Chem 25(18):10150–10152
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
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)
Liu T, Miao Q, Xu P (2016) Color topographical map segmentation Algorithm based on linear element features. Multimed Tools Appl 75(10):5417–5438
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)
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)
Meyer W, Turner B II (eds) (1994) Changes in land use and land cover: a global perspective. Cambridge University Press, Cambridge, pp 437–471
Michael L, Boylan N (2013) Predictions of settlement in peat soils. Q J Eng Geol Hydrogeol 46(3):303–322
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
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
Pont D, Kimberley MO, Brownlie RK (2015) Calibrated tree counting on remotely sensed images of planted forests. Int J Remote Sensing 36 (15)
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
Saha S, Basu S, Nasipuri M (2015) iLPR: an Indian license plate recognition system. Multimed Tools Appl 74(23):10621–10656
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
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
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)
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
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
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)
Xu Z et al (2015) Semantic based representing and organizing surveillance big data using video structural description technology. J Syst Software 102:217–225
Xu Z et al (2016) Semantic enhanced cloud environment for surveillance data management using video structural description. Computing 98(1-2):35–54
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
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)
Zhang T, Jiang L, Zhao T (2014) Soil temperature independent algorithm for estimating bare surface soil moisture. J Appl Remote Sens 8(1):083558
Zhu A, Qi F, Moore A (2010) Prediction of soil properties using fuzzy membership values. Geoderma 158(3-4):199–206
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
Corresponding author
Rights and permissions
About this article
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
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11042-016-3842-z