Sources

Alot of research for this project was performed, mostly on the optical properties of Soil. This paper is written in Dutch an and will be translated in English for the wiki on a later time. The following sources were used in this project:

• Alvarez Grima, M. (2014, July 16). Orientatie interview MTI.
• Ambrogi, F., Lama, N., Boracchi, P., & Biganzoli, E. (2007). Selection of artificial neural network models for survival analysis with Genetic Algorithms. Computational Statistics & Data Analysis, 52(1), 30–42. doi:10.1016/j.csda.2007.05.001
• Andy Ward, Ph.D. (2012, October 25). The Importance of Particle Size Distributions to The Characterization of Soils.
• Blott, S. J., & Pye, K. (2001). GRADISTAT: a grain size distribution and statistics package for the analysis of unconsolidated sediments. Earth Surface Processes and Landforms, 26(11), 1237–1248.
• Chesworth, W. (Ed.). (2008). Encyclopedia of Soil Science. Dordrecht: Springer Netherlands.
• Cox, M. R., & Budhu, M. (2008). A practical approach to grain shape quantification. Engineering Geology, 96(1–2), 1–16. doi:10.1016/j.enggeo.2007.05.005
• Gómez-Robledo, L., López-Ruiz, N., Melgosa, M., Palma, A. J., Capitán-Vallvey, L. F., & Sánchez-Marañón, M. (2013). Using the mobile phone as Munsell soil-colour sensor: An experiment under controlled illumination conditions. Computers and Electronics in Agriculture, 99, 200–208. doi:10.1016/j.compag.2013.10.002
• Hartemink, A. E., & Minasny, B. (2014). Towards digital soil morphometrics. Geoderma, 230–231, 305–317. doi:10.1016/j.geoderma.2014.03.008
• Igathinathane, C., Pordesimo, L. O., Columbus, E. P., Batchelor, W. D., & Sokhansanj, S. (2009). Sieveless particle size distribution analysis of particulate materials through computer vision. Computers and Electronics in Agriculture, 66(2), 147–158. doi:10.1016/j.compag.2009.01.005
• Igathinathane, C., Ulusoy, U., & Pordesimo, L. O. (2012). Comparison of particle size distribution of celestite mineral by machine vision ΣVolume approach and mechanical sieving. Powder Technology, 215–216, 137–146. doi:10.1016/j.powtec.2011.09.037
• Kröner, S., & Doménech Carbó, M. T. (2013). Determination of minimum pixel resolution for shape analysis: Proposal of a new data validation method for computerized images. Powder Technology, 245, 297–313. doi:10.1016/j.powtec.2013.04.048
• Melville, M. D., & Atkinson, G. (1985). Soil colour: its measurement and its designation in models of uniform kleurmodel. Journal of Soil Science, 36(4), 495–512. doi:10.1111/j.1365-2389.1985.tb00353.x
• Miller, N. A., & Henderson, J. J. (2010). Quantifying Sand Particle Shape Complexity using a Dynamic, Digital Imaging Technique. Agronomy Journal, 102(5), 1407. doi:10.2134/agronj2010.0097
• Phokharatkul, P., & Kimpan, C. (2002). Handwritten Thai Character Recognition Using Fourier Descriptors and Genetic Neural Networks. Computational Intelligence, 18(3), 270–293.
• Raj, P. M., & Cannon, W. R. (1999). 2-D particle shape averaging and comparison using Fourier descriptors. Powder Technology, 104(2), 180–189. doi:10.1016/S0032-5910(99)00046-7
• Soil. (2014, September 3). In Wikipedia, the free encyclopedia. Retrieved from https://en.wikipedia.org/w/index.php?title=Soil&oldid=624015984
• Training Institute for dredging. (2008). Ingewijde Training. Kinderdijk: MTI.
• Van Elburg, J. (2014, September 23). Hoe omgaan met PSD en het bepalen van een minimale sample groote.
• Viscarra Rossel, R. A., Fouad, Y., & Walter, C. (2008). Using a digital camera to measure soil organic carbon and iron contents. Biosystems Engineering, 100(2), 149–159. doi:10.1016/j.biosystemseng.2008.02.007
• Viscarra Rossel, R. A., Minasny, B., Roudier, P., & McBratney, A. B. (2006). Kleurmodel models for soil science. Geoderma, 133(3–4), 320–337. doi:10.1016/j.geoderma.2005.07.017
• Xu, K., Luxmoore, A. R., Jones, L. M., & Deravi, F. (1998). Integration of neural networks and expert systems for microscopic wear particle analysis. Knowledge-Based Systems, 11(3–4), 213–227. doi:10.1016/S0950-7051(98)00052-5