Predicting soil depth in a large and complex area using machine learning and environmental correlations-Reference-Cited by-同舟云学术

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Predicting soil depth in a large and complex area using machine learning and environmental correlations

Published:2022-08 Issue:8 Volume:21 Page:2422-2434
ISSN:2095-3119
Container-title:Journal of Integrative Agriculture
language:en
Short-container-title:Journal of Integrative Agriculture

Author:

LIU Feng,YANG Fei,ZHAO Yu-guo,ZHANG Gan-lin,LI De-cheng

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Plant Science,Agronomy and Crop Science,Animal Science and Zoology,Food Animals,Ecology,Biochemistry,Food Science

Reference61 articles.

1. Soil Physics;Baver,1956

2. Chapter 8: Land-surface parameters specific to topo-climatology;Böhner;Developments in Soil Science,2009

3. A mechanistic model to predict soil thickness in a valley area of Rio Grande do Sul, Brazil;Bonfatti;Geoderma,2018

4. Geostatistical approach for identifying scale-specific correlations between soil thickness and topographic attributes;Bourennane;Geomorphology,2014

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1. Mapping high poplar growth areas for bioenergy cultivation: A swarm-optimized approach;Renewable and Sustainable Energy Reviews;2023-11

2. Analysis of Prediction Accuracy and Model Optimization in Soil Geochemical Mapping of Arsenic Using Geostatistics and Machine Learning Methods;2023

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