Edge enhancement of potential field data using the logistic function and the total horizontal gradient

  • Luan Thanh PhamEmail author
  • Erdinc Oksum
  • Thanh Duc Do
Original Study


Locating the edges of anomalous bodies provides a fundamental tool in the geologic interpretation of potential field data. This paper compares the effectiveness of the commonly used edge detection methods such as the total horizontal gradient, analytic signal, tilt angle, theta map and their modified versions in terms of their accuracy on the determination of edges of source bodies. This paper also introduces an edge detector method for the enhancement of potential field anomalies, which is based on the logistic function of the total horizontal gradient. The new method is tested on synthetic data calculated using 3 models, and also on real magnetic and gravity data from Vietnam. The effectiveness of the method is evaluated by comparing the results with those of other popular methods. These results demonstrate that the method is a useful tool for the qualitative interpretation of potential field data.


Logistic function Total horizontal gradient Potential field data Edge detection 


  1. Arısoy MO, Dikmen U (2015) Edge enhancement of magnetic data using fractional-order-derivative filters. Geophysics 80(1):J7–J17CrossRefGoogle Scholar
  2. Chen AG, Zhou TF, Liu DJ, Zhang S (2017) Application of an enhanced theta-based filter for potential field edge detection: a case study of the luzong ore district. Chin J Geophys 60(2):203–218CrossRefGoogle Scholar
  3. Cooper GRJ (2009) Balancing images of potential-field data. Geophysics 74:L17–L20CrossRefGoogle Scholar
  4. Cooper GRJ (2014) Reducing the dependence of the analytic signal amplitude of aeromagnetic data on the source vector direction. Geophysics 79:J55–J60CrossRefGoogle Scholar
  5. Cooper GRJ, Cowan DR (2006) Enhancing potential field data using filters based on the local phase. Comput Geosci 32:1585–1591CrossRefGoogle Scholar
  6. Cooper GRJ, Cowan DR (2008) Edge enhancement of potential-field data using normalized statistics. Geophysics 73(3):H1–H4CrossRefGoogle Scholar
  7. Cordell L, Grauch VJS (1985) Mapping basement magnetization zones from aeromagnetic data in the San Juan basin, New Mexico. In: Hinze WJ (ed) The utility of regional gravity and magnetic anomaly maps. Society of Exploration Geophysics, Tulsa, pp 181–197CrossRefGoogle Scholar
  8. Ferreira FJF, Souza J, Bongiolo ABS, Castro LG (2013) Enhancement of the total horizontal gradient of magnetic anomalies using the tilt angle. Geophysics 78(3):J33–J41CrossRefGoogle Scholar
  9. Hang NTT, Thanh DD, Minh LH (2017) Application of directional derivative method to determine boundary of magnetic sources by total magnetic anomalies. Vietnam J Earth Sci 39(4):360–375Google Scholar
  10. Hidalgo-Gato MC, Barbosa VC (2017) The monogenic signal of potential-field data: a Python implementation. Geophysics 82(3):F9–F14CrossRefGoogle Scholar
  11. Liu J, Tran MD, Tang Y, Nguyen QL, Tran TH, Wu W, Chen J, Zhang Z, Zhao Z (2012) Permo-Triassic granitoids in the northern part of the Truong Son belt, NW Vietnam: geochronology, geochemistry and tectonic implications. Gondwana Res 22(2):628–644CrossRefGoogle Scholar
  12. Ma G, Li L (2012) Edge detection in potential fields with the normalized total horizontal derivative. Comput Geosci 41:83–87CrossRefGoogle Scholar
  13. Miller HG, Singh V (1994) Potential field tilt a new concept for location of potential field sources. J Appl Geophys 32:213–217CrossRefGoogle Scholar
  14. Minh LH, Hung LV, Trieu CD (2001) Some modern methods of the interpretation aeromagnetic data applied for Tuan Giao region. Vietnam J Earth Sci 22(3):207–216Google Scholar
  15. Pilkington M, Tschirhart V (2017) Practical considerations in the use of edge detectors for geologic mapping using magnetic data. Geophysics 82(3):1–8CrossRefGoogle Scholar
  16. Rao DB, Prakash MJ, Ramesh Babu N (1990) 3-D and 2 1/2-D modeling of gravity anomalies with variable density contrast. Geophys Prospect 38:411–422CrossRefGoogle Scholar
  17. Roest WRJ, Verhoef J, Pilkington M (1992) Magnetic interpretation using the 3-D analytic signal. Geophysics 57(1):116–125CrossRefGoogle Scholar
  18. Sandwell D, Garcia E, Soofi K, Wessel P, Chandler M, Smith WHF (2013) Toward 1-mGal accuracy in global marine gravity from CryoSat-2, Envisat, and Jason-1. Lead Edge 32(8):892–899CrossRefGoogle Scholar
  19. Tuyen NH, Phach PV, Shakirov RB, Trong CD, Hung PN, Anh LD (2018) Geoblocks recognition and delineation of the earthquake prone areas in the Tuan Giao area (Northwest Vietnam). Geotectonics 52(3):359–381CrossRefGoogle Scholar
  20. Verduzco B, Fairhead JD, Green CM, MacKenzie C (2004) New insights into magnetic derivatives for structural mapping. Lead Edge 23(2):116–119CrossRefGoogle Scholar
  21. Wijns C, Perez C, Kowalczyk P (2005) Theta map: edge detection in magnetic data. Geophysics 70:39–43CrossRefGoogle Scholar
  22. Yao Y, Huang D, Yu X, Chai B (2015) Edge interpretation of potential field data with the normalized enhanced analytic signal. Acta Geod Geophys 51(1):125–136CrossRefGoogle Scholar
  23. Zhang X, Yu P, Tang R, Xiang Y, Zhao CJ (2015) Edge enhancement of potential field data using an enhanced tilt angle. Explor Geophys 46(3):276–283CrossRefGoogle Scholar
  24. Zhou MF, Chen WT, Wang CY, Prevec SA, Liu PP, Howarth GH (2013) Two stages of immiscible liquid separation in the formation of Panzhihua-type Fe–Ti–V oxide deposits, SW China. Geosci Front 4(5):481–502CrossRefGoogle Scholar
  25. Zhou S, Huang D, Jiao J (2016) Total horizontal derivatives of potential field three-dimensional structure tensor and their application to detect source edges. Acta Geod Geophys 52(3):317–329CrossRefGoogle Scholar

Copyright information

© Akadémiai Kiadó 2019

Authors and Affiliations

  1. 1.Faculty of PhysicsVNU University of ScienceHa NoiVietnam
  2. 2.Department of Geophyisical Engineering, Engineering FacultySüleyman Demirel UniversityIspartaTurkey

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