From 4f82bf76c1b3643c6bc34cdbbccd681c8b38b922 Mon Sep 17 00:00:00 2001 From: thengl Date: Wed, 13 Mar 2019 16:50:10 +0100 Subject: [PATCH] Amanda's ref --- 07-Soil_organic_carbon.Rmd | 2 +- refs.bib | 18 ++++-------------- 2 files changed, 5 insertions(+), 15 deletions(-) diff --git a/07-Soil_organic_carbon.Rmd b/07-Soil_organic_carbon.Rmd index 5586287..ca944d5 100755 --- a/07-Soil_organic_carbon.Rmd +++ b/07-Soil_organic_carbon.Rmd @@ -208,7 +208,7 @@ knitr::include_graphics("figures/Fig_standard_soil_profiles_SOC_calc.png") ## Estimation of Bulk Density using a globally-calibrated PTF -Where values for bulk density are missing, and no local PTF exists, WoSIS points (global compilation of soil profiles) can be used to fit a PTF that can fill-in gaps in bulk density measurements globally. A regression matrix extracted on 15th of May 2017 (and which contains harmonized values for BD, organic carbon content, pH, sand and clay content, depth of horizon and USDA soil type at some 20,000 soil profiles world-wide), can be fitted using a random forest model (see also @ramcharan2017soil): +Where values for bulk density are missing, and no local PTF exists, WoSIS points (global compilation of soil profiles) can be used to fit a PTF that can fill-in gaps in bulk density measurements globally. A regression matrix extracted on 15th of May 2017 (and which contains harmonized values for BD, organic carbon content, pH, sand and clay content, depth of horizon and USDA soil type at some 20,000 soil profiles world-wide), can be fitted using a random forest model (see also @Ramcharan2017): ```{r} dfs_tbl = readRDS("extdata/wosis_tbl.rds") diff --git a/refs.bib b/refs.bib index 9dab462..3b58a23 100755 --- a/refs.bib +++ b/refs.bib @@ -5510,24 +5510,13 @@ @Article{doi:10.1093/bioinformatics/btw765 } @Article{Ramcharan2017, - Title = {A Soil Bulk Density Pedotransfer Function Based on Machine Learning: A Case Study with the NCSS Soil Characterization Database}, + Title = {{A Soil Bulk Density Pedotransfer Function Based on Machine Learning: A Case Study with the NCSS Soil Characterization Database}}, Author = {Ramcharan, Amanda and Hengl, Tomislav and Beaudette, Dylan and Wills, Skye}, Journal = {Soil Science Society of America Journal}, Year = {2017}, Number = {6}, Pages = {1279--1287}, - Volume = {81}, - Publisher = {The Soil Science Society of America, Inc.} -} - -@Article{ramcharan2017soil, - Title = {Soil Property and Class Maps of the Conterminous US at 100 meter Spatial Resolution based on a Compilation of National Soil Point Observations and Machine Learning}, - Author = {Ramcharan, Amanda and Hengl, Tomislav and Nauman, Travis and Brungard, Colby and Waltman, Sharon and Wills, Skye and Thompson, James}, - Journal = {Soil Science Society of America Journal}, - Year = {2018}, - Pages = {186-201}, - Volume = {82}, - Doi = {10.2136/sssaj2017.04.0122} + Volume = {81} } @Article{ramcharan2018soil, @@ -5537,7 +5526,8 @@ @Article{ramcharan2018soil Year = {2018}, Pages = {186-201}, Volume = {82}, - Publisher = {The Soil Science Society of America, Inc.} + Publisher = {The Soil Science Society of America, Inc.}, + Doi = {10.2136/sssaj2017.04.0122} } @Article{raup2007glims,