Mapping stocks of soil total nitrogen using remote sensing data: A comparison of random forest models with different predictors

Y Zhang, B Sui, H Shen, L Ouyang - Computers and Electronics in …, 2019 - Elsevier
Estimation of soil total nitrogen (STN) is important for quantifying the spatial distribution of
soil N (Nitrogen) stocks, determining the amount absorbed by crops and avoiding yield …

Mapping stocks of soil total nitrogen using remote sensing data: A comparison of random forest models with different predictors

Y Zhang, B Sui, H Shen… - … and Electronics in …, 2019 - ui.adsabs.harvard.edu
Estimation of soil total nitrogen (STN) is important for quantifying the spatial distribution of
soil N (Nitrogen) stocks, determining the amount absorbed by crops and avoiding yield …

Mapping stocks of soil total nitrogen using remote sensing data:: A comparison of random forest models with different predictors

Y Zhang, B Sui, H Shen, L Ouyang - 2019 - dl.acm.org
Estimation of soil total nitrogen (STN) is important for quantifying the spatial distribution of
soil N (Nitrogen) stocks, determining the amount absorbed by crops and avoiding yield …

Mapping stocks of soil total nitrogen using remote sensing data: a comparison of random forest models with different predictors.

ZY Zhang Yue, SB Sui Biao, SHO Shen HaiOu… - 2019 - cabidigitallibrary.org
Estimation of soil total nitrogen (STN) is important for quantifying the spatial distribution of
soil N (Nitrogen) stocks, determining the amount absorbed by crops and avoiding yield …

[引用][C] Mapping stocks of soil total nitrogen using remote sensing data: A comparison of random forest models with different predictors

Y Zhang, B Sui, H Shen, L Ouyang - Computers and Electronics in …, 2019 - cir.nii.ac.jp
Mapping stocks of soil total nitrogen using remote sensing data: A comparison of random forest
models with different predictors | CiNii Research CiNii 国立情報学研究所 学術情報ナビゲータ …

[引用][C] Mapping stocks of soil total nitrogen using remote sensing data: A comparison of random forest models with different predictors

Y Zhang, B Sui, H Shen, L Ouyang - 2019