Improving model parsimony and accuracy by modified greedy feature selection in digital soil mapping

Author:

Zhang XianglinORCID,Chen SongchaoORCID,Xue Jie,Wang Nan,Xiao Yi,Chen QianqianORCID,Hong Yongsheng,Zhou Yin,Teng Hongfen,Hu Bifeng,Zhuo Zhiqing,Ji Wenjun,Huang Yuanfang,Gou Yuxuan,Richer-de-Forges Anne C.ORCID,Arrouays DominiqueORCID,Shi ZhouORCID

Publisher

Elsevier BV

Subject

Soil Science

Reference107 articles.

1. Abbas, A., Khan, S., 2007. Using Remote Sensing Techniques for Appraisal of Irrigated Soil Salinity. Modsim 2007: International Congress on Modelling and Simulation (January), 2632-2638.

2. Linking soils to ecosystem services—A global review;Adhikari;Geoderma,2016

3. Assessment of the importance of gully erosion effective factors using Boruta algorithm and its spatial modeling and mapping using three machine learning algorithms;Amiri;Geoderma,2019

4. Andy, J., Isaak, R.H., Andrew, N., Edward, G., 2008. Hole-filled SRTM for the globe Version 4, available from the CGIAR-CSI SRTM 90m Database: https://srtm.csi.cgiar.org.

5. Arrouays, D., Grundy, M.G., Hartemink, A.E., Hempel, J.W., Heuvelink, G.B., Hong, S.Y., Lagacherie, P., Lelyk, G., McBratney, A.B., McKenzie, N.J., Mendonça-Santos, M.d.L., 2014. GlobalSoilMap: Toward a fine-resolution global grid of soil properties. Advances in Agronomy, 125, 93-134.

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