A Comparison, Validation, and Evaluation of the S-world Global Soil Property Database
- Independent datasets with a proper global coverage are absent.
- The support of the global soil property maps (available at different resolutions like 30 arc-seconds or 0.5 degree) differs from the point observations in the soil profile databases.
- Single quality measures like the root mean square difference (RMSD) are insufficient as it is likely that the quality of the maps differs geographically due to the natural inherent variation in soil properties, the scale of underlying soil maps, and sampling intensity.
2. Materials and Methods
2.1. S-World and Its Use in the Global Land Outlook
2.2. A Comparative Analysis
2.2.1. Global Soil Databases
- GSDE: Global Soil Dataset for use in Earth System Models . The GSDE provides a range of soil property maps at a resolution of 30 arc-second for eight layers up to a depth of 2.3 m (i.e., 0–4.5, 4.5–9.1, 9.1–16.6, 16.6–28.9, 28.9–49.3, 49.3–82.9, 82.9–138.3 and 138.3–229.6 cm). The GSDE is based on the DSMW and various regional and national soil databases. The GSDE first harmonized the databases and subsequently linked the results to the map units of the DSMW.
- HWSD: Harmonized World Soil Database . The HWSD is principally a soil map with soil types at a 30 arc-seconds resolution. The 16,022 different soil map units combine data from the DSMW with regional and national updates of soil information worldwide. The majority of the soil map units are described by multiple, so-called, soil components. In addition, soil property data are provided for the topsoil (0–30 cm) and the subsoil (30–100 cm) for each of the soil components in the map units.
- IGBP-DIS: Global Gridded Surfaces of Selected Soil Characteristics . The data includes 7 soil properties at a resolution of 5 arc-minutes. The data were developed by the Global Soil Data Task Group of the International Geosphere-Biosphere Programme (IGBP) Data and Information System (DIS). The, so-called, Soil Data System uses a statistical bootstrapping approach to link the pedon records in the Global Pedon Database  to the DSMW.
- WISE30sec: Harmonized soil property values for broad-scale modelling . The dataset considers 20 soil properties. These estimates are presented for fixed depth intervals of 20 cm up to a depth of 100 cm, and intervals of 50 cm between 100 cm to 200 cm (or less when appropriate). A harmonized dataset of derived soil properties for the world that is comprised of a soil geographical and a soil attribute component. The dataset was created using the HWSD, overlaid by a climate zones map (Köppen-Geiger) as co-variate, and soil property estimates derived from analyses of the ISRIC-WISE soil profile database for the respective mapped ‘soil/climate’ combinations.
2.2.2. Data Preprocessing
- Data acquisition: GSDE data on sand, clay and SOC content were downloaded from the Land-Atmoshere Interaction Research Group at Sun Yat-sen University at 30 arc-seconds. The vertical variation in soil properties was captured by eight layers of differing depths. HWSD data were downloaded from IIASA at 30 arc-seconds resolution. The map units of the HWSD are described by 1–10 different soil types. The relative importance of the soil types and the SOC contents (for the topsoil (0–30 cm) and subsoil (30–100 cm)) and clay contents were included in the database. IGBP-DIS data were downloaded from the Distributed Active Archive Centre for Biochemical Dynamics and included soil-carbon density and bulk density data at 5 arc-minutes resolution. Data from SoilGrids were directly obtained from the developer at ISRIC and included grids of clay and SOC contents at 250 m resolution at seven different depth intervals. WISE30sec data were downloaded from the ISRIC website, including estimates of sand, silt and SOC content for fixed depth intervals of 20 cm up to a depth of 100 cm. Data were obtained in October 2017 except for the GSDE database that was downloaded on 8 January 2018.
- Conversion: All the obtained datasets had to be converted into the proper matching variables (i.e., depth interval and measurement units). The GSDE and SoilGrids included complete data at various depth intervals. Weighted averages were calculated for the 0–30 cm topsoil and 30–100 cm subsoil for SOC, and over the 0–100 cm profile for the clay content. The HWSD already provided SOC contents for topsoil and subsoil. For the clay content a weighted average was calculated over the soil profile. If, due to a limited soil depth, no data were provided for the subsoil, clay contents of the topsoil were used. Typically, two methods are used to deal with the complex map units containing soil associations (84% of all map units): either the dominant soil type is used (which on average covers 65% of the map unit) (HWSDd) or the area weighted average of the soil properties is calculated based on the share of each soil type (HWSDw). Both methods were used to derive the required grids of soil properties. The IGBP-DIS database included soil carbon density and bulk density but lacked data on soil texture. We derived data on SOC contents for topsoil and subsoil from the soil carbon density and bulk density. The derivation required two main assumptions: (i) differences in soil depth are not considered and (ii) carbon stocks in the 0–30 cm topsoil roughly equal the carbon stocks in the 30–100 cm subsoil (following Hiederer and Köchy ). Similar to the HWSD, the WISE30 database included information for the topsoil and subsoil of the different soil components. The WISE30 was used in a similar way as the HWSD: soil properties of the dominant soil component (WISE30d) and the weighted average (WISE30w) were derived.
- Aggregation/resampling: Finally, maps at 5 arc-minutes resolution were resampled to additionally obtain maps at 30 arc-seconds resolution. Maps at 30 arc-seconds resolution or more detailed were aggregated to a 5 arc-minutes resolution. During aggregation, the mean of all grid cells was calculated while ignoring possible cells with no data values.
2.2.3. Consistency Analysis
- The spatially aggregated mean of the ensemble mean (μEμ): average soil property within an ecoregion.
- The spatially aggregated standard deviation of the ensemble mean (σEμ): the spatial variation of a soil property within an ecoregion.
- The spatially aggregated mean of the ensemble standard deviation (μEσ): the average consistency of the estimates of a soil property within an ecoregion.
- The spatially aggregated standard deviation of the ensemble standard deviation (σEσ): The variation in the consistency of the estimates within an ecoregion.
- Soil profiles had to be independent from the S-World calculations. Therefore, all soil profiles that were also included in the WISE3.1 database were removed from the database.
- Only soil profiles that were georeferenced with a 30 arc-seconds accuracy (or higher) were included in the validation.
- Only soil profiles that included either or both SOC and soil texture data were useful.
2.4. Methodological Evaluation of S-World
3. Results and Discussion
3.1. Comparative Analysis
3.2. Validation Results
3.3. Methodology Evaluation
3.4. General Discussion
Data Availability Statement
Conflicts of Interest
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|Topsoil SOC%||Subsoil SOC%||Clay%|
|(Sub)tropical moist broadleaf forests||2.2||2.6||1.2||1.7||1.1||2.3||0.6||1.5||35.8||8.2||7.4||3.2|
|(Sub)tropical dry broadleaf forests||1.5||1.0||0.7||1.0||0.5||0.3||0.2||0.4||35.5||9.5||6.9||2.7|
|(Sub)tropical coniferous forests||2.2||1.2||1.3||1.2||0.8||0.4||0.4||0.4||27.3||7.2||7.5||2.2|
|Temperate broadleaf/mixed forests||3.0||3.8||1.8||2.6||1.5||3.1||1.1||2.2||23.4||6.9||4.8||2.4|
|Temperate coniferous forests||3.2||3.3||2.1||2.5||1.4||2.8||1.1||2.2||20.2||6.5||4.7||2.3|
|Deserts and Xeric shrublands||0.7||0.4||0.4||0.6||0.3||0.2||0.1||0.3||20.5||7.2||5.8||2.4|
|Topsoil SOC%||Subsoil SOC%||Clay%|
|(Sub)tropical moist broadleaf forests||1.2||55.3||0.6||94.6||7.4||76.1|
|(Sub)tropical dry broadleaf forests||0.7||81.8||0.2||99.2||6.9||88.8|
|(Sub)tropical coniferous forests||1.3||66.7||0.4||98.9||7.5||96.2|
|Temperate broadleaf/mixed forests||1.8||70.5||1.1||89.3||4.8||94.1|
|Temperate coniferous forests||2.1||65.4||1.1||89.7||4.7||95.0|
|Deserts and Xeric shrublands||0.4||91.9||0.1||99.9||5.8||95.6|
|5 Arc Minutes||30 Arc-Seconds|
|(Sub)tropical moist broadleaf forests (n = 7824)||0.8||−0.1||7.1||0.7||−0.2||7.6|
|(Sub)tropical dry broadleaf forests (n = 3097)||1.3||0.0||7.9||1.2||0.0||8.0|
|(Sub)tropical coniferous forests (n = 2486)||1.5||0.2||−2.1||1.5||0.2||−2.4|
|Temperate broadleaf/mixed forests (n = 20074)||1.7||0.0||7.7||1.6||0.0||7.8|
|Temperate coniferous forests (n = 8478)||4.0||0.2||11.4||3.9||0.1||11.6|
|Boreal forests/taiga (n = 200)||0.8||0.6||17.5||1.0||0.5||16.7|
|(Sub)tropical grasslands/savannas/shrublands (n = 10141)||1.0||0.0||9.2||0.9||0.0||9.6|
|Temperate grasslands/savannas/shrublands (n = 17205)||0.6||0.0||9.3||0.6||0.0||10.1|
|Flooded grasslands/savannas (n = 545)||2.9||0.4||18.6||2.8||0.3||19.6|
|Montane grasslands/shrublands (n = 2023)||0.7||−0.2||0.0||0.7||−0.2||1.0|
|Tundra (n = 193)||−12.4||−7.6||13.0||−11.7||−7.2||14.7|
|Mediterranean forests/woodlands/scrub (n = 935)||0.3||−0.1||3.6||0.3||−0.2||3.5|
|Deserts and Xeric shrublands (n = 9808)||0.3||−0.1||4.7||0.3||−0.1||5.1|
|Mangroves (n = 184)||1.9||0.3||15.7||1.9||0.3||15.3|
|(Sub)tropical moist broadleaf forests||2520||Temperate grasslands/savannas/shrublands||583|
|(Sub)tropical dry broadleaf forests||969||Flooded grasslands/savannas||1929|
|(Sub)tropical coniferous forests||282||Montane grasslands/shrublands||2416|
|Temperate broadleaf/mixed forests||635||Tundra||40,103|
|Temperate coniferous forests||476||Mediterranean forests/woodlands/scrub||3435|
|Boreal forests/taiga||75,325||Deserts and Xeric shrublands||2402|
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Stoorvogel, J.J.; Mulder, V.L. A Comparison, Validation, and Evaluation of the S-world Global Soil Property Database. Land 2021, 10, 544. https://doi.org/10.3390/land10050544
Stoorvogel JJ, Mulder VL. A Comparison, Validation, and Evaluation of the S-world Global Soil Property Database. Land. 2021; 10(5):544. https://doi.org/10.3390/land10050544Chicago/Turabian Style
Stoorvogel, Jetse J., and Vera L. Mulder. 2021. "A Comparison, Validation, and Evaluation of the S-world Global Soil Property Database" Land 10, no. 5: 544. https://doi.org/10.3390/land10050544