A China dataset of soil properties for land surface modelling (version 2, CSDLv2) DOI Creative Commons
Gaosong Shi,

Wenye Sun,

Wei Shangguan

et al.

Earth system science data, Journal Year: 2025, Volume and Issue: 17(2), P. 517 - 543

Published: Feb. 7, 2025

Abstract. Accurate and high-resolution spatial soil information is crucial for efficient sustainable land use, management, conservation. Since the establishment of digital mapping (DSM) GlobalSoilMap working group, significant advances have been made in terms availability quality globally. However, accurately predicting variation over large complex areas with limited samples remains a challenge, especially China, which has diverse landscapes. To address this we utilised 11 209 representative multi-source legacy profiles (including Second National Soil Survey World Information Service, First regional databases) soil-forming environment characterisation. Using advanced ensemble machine learning high-performance parallel-computing strategy, developed comprehensive maps 23 physical chemical properties at six standard depth layers from 0 to 2 m China 90 resolution (China dataset surface modelling version 2, CSDLv2). Data-splitting independent-sample validation strategies were employed evaluate accuracy predicted maps' quality. The results showed that significantly more accurate detailed compared traditional type linkage methods (i.e. CSDLv1, first dataset), SoilGrids 2.0, HWSD 2.0 products, effectively representing across China. prediction all intervals ranged good moderate, median model efficiency coefficients most ranging 0.29 0.70 during data-splitting 0.25 0.84 validation. wide range between 5 % lower 95 upper limits may indicate substantial room improvement current predictions. relative importance environmental covariates predictions varied property depth, indicating complexity interactions among multiple factors formation processes. As used study mainly originate conducted 1970s 1980s, they could provide new perspectives on changes, together existing based 2010s. findings make important contributions project can also be Earth system better represent role hydrological biogeochemical cycles This freely available https://www.scidb.cn/s/ZZJzAz (last access: 17 November 2024​​​​​​​) or https://doi.org/10.11888/Terre.tpdc.301235 (Shi Shangguan, 2024).

Language: Английский

A China dataset of soil properties for land surface modelling (version 2, CSDLv2) DOI Creative Commons
Gaosong Shi,

Wenye Sun,

Wei Shangguan

et al.

Earth system science data, Journal Year: 2025, Volume and Issue: 17(2), P. 517 - 543

Published: Feb. 7, 2025

Abstract. Accurate and high-resolution spatial soil information is crucial for efficient sustainable land use, management, conservation. Since the establishment of digital mapping (DSM) GlobalSoilMap working group, significant advances have been made in terms availability quality globally. However, accurately predicting variation over large complex areas with limited samples remains a challenge, especially China, which has diverse landscapes. To address this we utilised 11 209 representative multi-source legacy profiles (including Second National Soil Survey World Information Service, First regional databases) soil-forming environment characterisation. Using advanced ensemble machine learning high-performance parallel-computing strategy, developed comprehensive maps 23 physical chemical properties at six standard depth layers from 0 to 2 m China 90 resolution (China dataset surface modelling version 2, CSDLv2). Data-splitting independent-sample validation strategies were employed evaluate accuracy predicted maps' quality. The results showed that significantly more accurate detailed compared traditional type linkage methods (i.e. CSDLv1, first dataset), SoilGrids 2.0, HWSD 2.0 products, effectively representing across China. prediction all intervals ranged good moderate, median model efficiency coefficients most ranging 0.29 0.70 during data-splitting 0.25 0.84 validation. wide range between 5 % lower 95 upper limits may indicate substantial room improvement current predictions. relative importance environmental covariates predictions varied property depth, indicating complexity interactions among multiple factors formation processes. As used study mainly originate conducted 1970s 1980s, they could provide new perspectives on changes, together existing based 2010s. findings make important contributions project can also be Earth system better represent role hydrological biogeochemical cycles This freely available https://www.scidb.cn/s/ZZJzAz (last access: 17 November 2024​​​​​​​) or https://doi.org/10.11888/Terre.tpdc.301235 (Shi Shangguan, 2024).

Language: Английский

Citations

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