Machine-Learning Variables at Different Scales vs. Knowledge-based Variables for Mapping Multiple Soil Properties-Reference-Cited by-同舟云学术

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Machine-Learning Variables at Different Scales vs. Knowledge-based Variables for Mapping Multiple Soil Properties

Published:2018-04-26 Issue:3 Volume:82 Page:645-656
ISSN:0361-5995
Container-title:Soil Science Society of America Journal
language:en
Short-container-title:Soil Science Society of America Journal

Author:

Shi Jingjing¹²,Yang Lin¹²,Zhu A-Xing¹²,Qin Chengzhi¹²,Liang Peng¹²,Zeng Canying³,Pei Tao¹²

Affiliation:

1. State Key Lab. of Resour. & Environ. Inf. Sys.; Inst. of Geogr. Sci. & Nat. Resour. Res. Chinese Acad. of Sci.; Beijing 100101 China

2. Univ. of Chinese Acad. of Sci.; Beijing 100049 China

3. School of Geography Nanjing Normal Univ.; Nanjing 210023 China

Funder

National Natural Science Foundation of China

Natural Science Research Program of Jiangsu

Publisher

Wiley

Subject

Soil Science

Link

http://onlinelibrary.wiley.com/wol1/doi/10.2136/sssaj2017.11.0392/fullpdf

Reference83 articles.

1. Digital soil mapping across the globe;Arrouays;Geoderma Regional,2017

2. Arun , K. Langmead , C.J. 2005 Structure based chemical shift prediction using random forests non-linear regression Proceedings of the 4th Asia-Pacific Bioinformatics Conference, Taipei, Taiwan. 13-16 Feb. 2006 https://doi.org/10.1142/9781860947292_0035

3. Predictive Soil Maps Based on Geomorphic Mapping, Remote Sensing, and Soil Databases in the Desert Southwest

4. Hyper-scale digital soil mapping and soil formation analysis;Behrens;Geoderma,2014

5. Multi-scale digital terrain analysis and feature selection for digital soil mapping;Behrens;Geoderma,2010

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