Keywords:
- soil analysis
- artificial intelligence
- field soil analysis
- calibration
- Platt Scaling
- Isotonic Regression
Abstract
This article discusses the comparison and calibration of field and artificial intelligence analysis of soil nutrients. The results revealed some inconsistencies between the two methods, indicating the need to calibrate the AI model. Calibration was performed using two widely used calibration algorithms: Platt Scaling and Isotonic Regression, and their performance was assessed. The results showed the importance of comparing and calibrating field and artificial intelligence results for reliable soil analysis.
References
McBratney, A.B., Santos, M.M., Minasny, B., 2003. On digital soil mapping. – Geoderma – 117, 3, 52
Minasny, B., McBratney, A.B., Malone, B.P., Wheeler, I., 2013. Chapter one - digital mapping of soil carbon. In: Sparks, D.L. (Ed.), Advances in Agronomy. Academic Press, – pp. 1, 47
Hengl, T., Heuvelink, G.B., Kempen, B., Leenaars, J.G., Walsh, M.G., Shepherd, K.D., Sila, A., MacMillan, R.A., de Jesus, J.M., Tamene, L., 2015. Mapping soil properties of Africa at 250 m resolution: random forests significantly improve current predictions. PLoS One 10, e0125814.
Malone, B.P., McBratney, A., Minasny, B., Laslett, G., 2009. Mapping continuous depth functions of soil carbon storage and available water capacity. – Geoderma 154 (1–2), –138, 152.
Lacoste, M., Minasny, B., McBratney, A., Michot, D., Viaud, V., Walter, C., 2014. High resolution 3D mapping of soil organic carbon in a heterogeneous agricultural landscape. – Geoderma – 213, 296, 311.
Wälder, K., Wälder, O., Rinklebe, J., Menz, J., 2008. Estimation of soil properties with geostatiscal methods in floodplains. Arch. Agron. Soil Sci. 54 (3), – 275, 295.
Karunaratne, S., Bishop, T., Baldock, J., Odeh, I., 2014. Catchment scale mapping of measureable soil organic carbon fractions. – Geoderma – 219, 14, 23.
Taghizadeh-Mehrjardi, R., Minasny, B., Sarmadian, F., Malone, B., 2014. Digital mapping of soil salinity in Ardakan region, central Iran. – Geoderma – 213, 15, 28.
Pahlavan-Rad, M.R., Akbarimoghaddam, A., 2018. Spatial variability of soil texture fractions and pH in a flood plain (case study from eastern Iran). – Catena – 160, 275, 281.
Taghizadeh-Mehrjardi, R., Nabiollahi, K., Kerry, R., 2016. Digital mapping of soil organic carbon at multiple depths using different data mining techniques in Baneh region, Iran. – Geoderma – 266, 98, 110.
Forkuor, G., Hounkpatin, O.K., Welp, G., Thiel, M., 2017. High resolution mapping of soil properties using remote sensing variables in South-Western Burkina Faso: a comparison of machine learning and multiple linear regression models. PLoS One 12, e 0170478.
