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World Soil Information Service (WoSIS) - Towards the standardization and harmonization of world soil data : Procedures Manual 2018
Carvalho Ribeiro, E.D. ; Batjes, N.H. ; Oostrum, A.J.M. van - 2018
ISRIC - World Soil Information (ISRIC Report 2018/01) - 166 p.
Spatial data infrastructures for handling soil data
Mendes de Jesus, J.S. ; Carvalho Ribeiro, E.D. ; Batjes, N.H. ; Kempen, B. - 2017
In: Abstract Book Pedometrics 2017. - Wageningen : - p. 154 - 154.
Standardization of world soil profile data to support global mapping and modelling
Batjes, Niels ; Carvalho Ribeiro, Eloi ; Leenaars, Johan ; Oostrum, Ad van - 2017
In: Abstract Book Pedometrics 2017. - - p. 29 - 29.
Procedures for collecting, compiling, standardizing/harmonizing and subsequently providing quality-assessed world soil profile data to the international community, as developed in the framework of WoSIS (World Soil Information Service), are described. Harmonization, as defined by the Global Soil Partnership (GSP), involves “providing mechanisms for the collation, analysis and exchange of consistent and comparable global soil data and information”. Areas of harmonization include those related to: a) soil description, classification and mapping, b) soil analyses, c) exchange of soil data, and d) interpretations. Seen the breadth and magnitude of the task, so far we have focused on developing and applying procedures for handling and standardizing legacy soil profile data, with special attention for the selection of soil properties considered in the Global-SoilMap specifications: organic carbon, pH, texture (sand, silt, and clay), coarse fragments (> 2 mm), cation exchange capacity, electrical conductivity, bulk density, and water retention. These properties are commonly considered in digital soil mapping and can be used to address a wide range of global issues, such as food security, combatting land degradation, and adaptation and mitigation to climate change. The standardized data are served to the international community using two formats. Static snapshots in TXT format, with a time stamp and identifier (doi), are provided to allow for consistent citation purposes. For example, the ‘July 2016’ snapshot includes standardized data for some 94,000 profiles. Newly standardized data are gradually added to a dynamic version of the dataset that can be accessed ‘24/7’ using WFS connection in GIS applications (some 109,000 profiles as of March 2017); the number of measured data for each property varies between profiles and with depth. Both the static and dynamic versions are freely available at: Future releases of WoSIS will consider a wider range of soil properties (e.g. content of nitrogen, phosphorus and other (micro) nutrients), including data derived from soil spectrometry. Instrumental to enhanced usability and accessibility of data managed in WoSIS will be the continued harmonization of soil property values and further standardization of soil analytical method descriptions. Development and testing of such procedures, in partnership with data providers, will allow for the fulfilment of (future) demands for global soil information, and enable further collation of standardized soil data shared by partners and third parties.
Fire and plant diversity at the global scale
Pausas, Juli G. ; Carvalho Ribeiro, Eloi - 2017
Global Ecology and Biogeography 26 (2017)8. - ISSN 1466-822X - p. 889 - 897.
diversity - fire regime - plant richness - productivity - pyrogeography

Aim: Understanding the drivers of global diversity has challenged ecologists for decades. Drivers related to the environment, productivity and heterogeneity are considered primary factors, whereas disturbance has received less attention. Given that fire is a global factor that has been affecting many regions around the world over geological time scales, we hypothesize that the fire regime should explain a significant proportion of global coarse-scale plant diversity. Location: All terrestrial ecosystems, excluding Antarctica. Time period: Data collected throughout the late 20th and early 21st century. Taxa: Seed plants (= spermatophytes = phanerogamae). Methods: We used available global plant diversity information at the ecoregion scale and compiled productivity, heterogeneity and fire information for each ecoregion using 15 years of remotely sensed data. We regressed plant diversity against environmental variables; thereafter, we tested whether fire activity still explained a significant proportion of the variance. Results: Ecoregional plant diversity was positively related to both productivity (R2 =.30) and fire activity (R2 =.38). Once productivity and other environmental variables were in the model (R2 =.50), fire regime still explained a significant proportion of the variability in plant diversity (overall model, R2 =.71). The results suggest that fire drives temporal and spatial variability in many ecosystems, providing opportunities for a diversity of plants. Main conclusions: Fire regime is a primary factor explaining plant diversity around the globe, even after accounting for productivity. Fires delay competitive exclusion, increase landscape heterogeneity and generate new niches; thus, they provide opportunities for a large variety of species. Consequently, fire regime should be considered in order to understand global ecosystem distribution and diversity.

Standardised soil profile data for the world (WoSIS, July 2016 snapshot)
Batjes, N.H. ; Carvalho Ribeiro, E.D. ; Oostrum, A.J.M. van; Leenaars, J.G.B. ; Mendes de Jesus, J.S. - 2017
Soil is an important provider of ecosystem services. Yet, this natural resource is being threatened. Professionals, scientists and decision makers require quality-assessed soil data to address issues such as food security, land degradation, and climate change. Procedures for safeguarding, standardising and subsequently serving of consistent soil data from WoSIS (World Soil Information Service) to underpin broad scale mapping and modelling are described in the above mentioned ESSD paper.
WoSIS: providing standardised soil profile data for the world
Batjes, N.H. ; Carvalho Ribeiro, E.D. ; Oostrum, A.J.M. van; Leenaars, J.G.B. ; Hengl, T. ; Mendes de Jesus, J.S. - 2017
Earth System Science Data 9 (2017)1. - ISSN 1866-3508 - p. 1 - 14.
The aim of the World Soil Information Service (WoSIS) is to serve quality-assessed, georeferenced soil data (point, polygon, and grid) to the international community upon their standardisation and harmonisation. So far, the focus has been on developing procedures for legacy point data with special attention to the selection of soil analytical and physical properties considered in the GlobalSoilMap specifications (e.g. organic carbon, soil pH, soil texture (sand, silt, and clay), coarse fragments ( <  2 mm), cation exchange capacity, electrical conductivity, bulk density, and water holding capacity). Profile data managed in WoSIS were contributed by a wide range of soil data providers; the data have been described, sampled, and analysed according to methods and standards in use in the originating countries. Hence, special attention was paid to measures for soil data quality and the standardisation of soil property definitions, soil property values, and soil analytical method descriptions. At the time of writing, the full WoSIS database contained some 118 400 unique “shared” soil profiles, of which some 96 000 are georeferenced within defined limits. In total, this corresponds with over 31 million soil records, of which some 20 % have so far been quality-assessed and standardised using the sequential procedure discussed in this paper. The number of measured data for each property varies between profiles and with depth, generally depending on the purpose of the initial studies. Overall, the data lineage strongly determined which data could be standardised with acceptable confidence in accord with WoSIS procedures, corresponding to over 4 million records for 94 441 profiles. The publicly available data – WoSIS snapshot of July 2016 – are persistently accessible from ISRIC WDC-Soils through doi:10.17027/isric-wdcsoils.20160003.
SoilGrids250m: Global gridded soil information based on machine learning
Hengl, T. ; Mendes de Jesus, J.S. ; Heuvelink, G.B.M. ; Ruiperez Gonzalez, M. ; Kilibarda, Milan ; Blagotic, Aleksandar ; Wei, Shangguan ; Wright, Marvin N. ; Geng, Xiaoyuan ; Bauer-Marschallinger, Bernhard ; Guevara, Mario Antonio ; Vargas, Rodrigo ; MacMillan, Robert A. ; Batjes, N.H. ; Leenaars, J.G.B. ; Carvalho Ribeiro, E.D. ; Wheeler, Ichsani ; Mantel, S. ; Kempen, B. - 2017
PLoS ONE 12 (2017)2. - ISSN 1932-6203 - 40 p.
This paper describes the technical development and accuracy assessment of the most recent and improved version of the SoilGrids system at 250m resolution (June 2016 update). SoilGrids provides global predictions for standard numeric soil properties (organic carbon, bulk density, Cation Exchange Capacity (CEC), pH, soil texture fractions and coarse fragments) at seven standard depths (0, 5, 15, 30, 60, 100 and 200 cm), in addition to predictions of depth to bedrock and distribution of soil classes based on the World Reference Base (WRB) and USDA classification systems (ca. 280 raster layers in total).
Soil legacy data rescue via GlobalSoilMap and other international and national initiatives
Arrouays, Dominique ; Leenaars, Johan G.B. ; Richer de Forges, Anne C. ; Adhikari, Kabindra ; Ballabio, Cristiano ; Greve, Mogens H. ; Grundy, Mike ; Guerrero, Eliseo ; Hempel, Jon ; Hengl, Tom ; Heuvelink, Gerard ; Batjes, Niels ; Carvalho Ribeiro, Eloi ; Hartemink, Alfred ; Okx, J.P. - 2017
GeoResJ 14 (2017). - ISSN 2214-2428 - p. 1 - 19.
GlobalSoilMap - Legacy data - Soil data rescue

Legacy soil data have been produced over 70 years in nearly all countries of the world. Unfortunately, data, information and knowledge are still currently fragmented and at risk of getting lost if they remain in a paper format. To process this legacy data into consistent, spatially explicit and continuous global soil information, data are being rescued and compiled into databases. Thousands of soil survey reports and maps have been scanned and made available online. The soil profile data reported by these data sources have been captured and compiled into databases. The total number of soil profiles rescued in the selected countries is about 800,000. Currently, data for 117, 000 profiles are compiled and harmonized according to GlobalSoilMap specifications in a world level database (WoSIS). The results presented at the country level are likely to be an underestimate. The majority of soil data is still not rescued and this effort should be pursued. The data have been used to produce soil property maps. We discuss the pro and cons of top-down and bottom-up approaches to produce such maps and we stress their complementarity. We give examples of success stories. The first global soil property maps using rescued data were produced by a top-down approach and were released at a limited resolution of 1 km in 2014, followed by an update at a resolution of 250 m in 2017. By the end of 2020, we aim to deliver the first worldwide product that fully meets the GlobalSoilMap specifications.

WoSIS – World Soil Information Service
Batjes, N.H. ; Carvalho Ribeiro, E.D. ; Oostrum, A.J.M. van; Mendes de Jesus, J.S. - 2016
data collection
ISRIC - World Soil Information (WDC-Soils) has a mission to serve the international community as custodian of global soil data and information, and to increase awareness and understanding of soils in major global issues. With partners we have implemented a server database based on PostgreSQL, known as WoSIS (World Soil Information Service). The aims are to safeguard and subsequently share soil data upon their standardization and harmonization. The data come from disparate sources; conditions for use are stored in WoSIS together with the full data lineage to ensure that data providers are duly acknowledged. In accord with these conditions (licenses), the submitted data is gradually standardized and harmonized, ultimately to make them “comparable as if assessed by a single given (reference) method.” So far, we have focused on point (profile) data, limiting ourselves to the selection of soil analytical and physical properties listed in the GlobalSoilMap (2013) specifications. A wider range of quality-assessed soil data (point, polygon, and grid) will be considered in the future. The present complement of standardized soil profile data is freely accessible at:
A spatial data infrastructure for storing and exchanging global soil data
Kempen, B. ; Mendes de Jesus, J.S. ; Batjes, N.H. ; Carvalho Ribeiro, E.D. ; Leenaars, J.G.B. ; Hengl, T. - 2016
In: Eurosoil Istanbul 2016, abstract book. - ECSSS - p. 104 - 104.
The demand for soil data for agro-ecological and other environmental applications at national, regional and global level is growing; establishing a spatial data infrastructure (SDI) for global soil data is key for connecting soil data holders and serving the user community effectively. Organizations investing in a flexible soil SDI can efficiently contribute to and benefit from international collaborative initiatives while consolidating their role as mandated soil data holder. ISRIC–World Soil Information has been investing in the development of new geo-information technologies with the objective to improve and increase global soil data exchange and use. Here we describe main components of ISRIC’s evolving global soil SDI.
Towards the standardization and harmonization of world soil data : Procedures Manual ISRIC World Soil Information Service (WoSIS version 2.0)
Carvalho Ribeiro, E.D. ; Batjes, N.H. ; Leenaars, J.G.B. ; Oostrum, A.J.M. van; Mendes de Jesus, J.S. - 2015
Wageningen : ISRIC - World Soil Information (ISRIC Report 2015/03) - 110 p.
New gridded data sets for global sustainability studies — WISE30SEC and SOILGRIDS
Batjes, N.H. ; Mendes de Jesus, J.S. ; Heuvelink, G.B.M. ; Carvalho Ribeiro, E.D. ; Kempen, B. ; Leenaars, J.G.B. ; Hengl, T. ; Ruiperez Gonzalez, M. ; Oostrum, A.J.M. van; Bosch, H. van den - 2015
In: Book of Abstracts, Wageningen Soil Conference 2015 / Keestra, S., Mol, A., Zaal, A., Wallinga, J., Jansen, B., Wageningen UR - ISBN 9789461731685 - p. 158 - 158.
SoilGrids1km : a system for automated global soil mapping, Version: 5th of April 2014
Hengl, T. ; Mendes de Jesus, J.S. ; Carvalho Ribeiro, E.D. ; Batjes, N.H. ; Heuvelink, G.B.M. ; Kempen, B. ; Ruiperez Gonzalez, M. ; Leenaars, J.G.B. ; Caspari, T.M. ; Samuel Rosa, A. ; Reuter, H.I. ; Macmillan, R.A. - 2014
geographical information systems - soil science
SoilGrids1km is a collection of updatable soil property and class maps of the world at a relatively coarse resolution of 1 km produced using state-of-the-art model-based statistical methods: 3D regression with splines for continuous soil properties and multinomial logistic regression for soil classes.
Towards improved soil information for studies of global sustainability
Batjes, N.H. ; Hengl, T. ; Mendes de Jesus, J.S. ; Heuvelink, G.B.M. ; Carvalho Ribeiro, E.D. ; Kempen, B. ; Leenaars, J.G.B. ; Ruiperez Gonzalez, M. - 2014
SoilGrids1km— global soil information based on automated mapping
Hengl, T. ; Mendes de Jesus, J.S. ; Macmillan, R.A. ; Batjes, N.H. ; Heuvelink, G.B.M. ; Carvalho Ribeiro, E.D. ; Samuel Rosa, A. ; Kempen, B. ; Leenaars, J.G.B. ; Walsh, M.G. ; Ruiperez Gonzalez, M. - 2014
PLoS ONE 9 (2014)8. - ISSN 1932-6203
global land areas - organic-carbon - resolution - climate - world - maps - interpolation - database - models
Background Soils are widely recognized as a non-renewable natural resource and as biophysical carbon sinks. As such, there is a growing requirement for global soil information. Although several global soil information systems already exist, these tend to suffer from inconsistencies and limited spatial detail. Methodology/Principal Findings We present SoilGrids1km — a global 3D soil information system at 1 km resolution — containing spatial predictions for a selection of soil properties (at six standard depths): soil organic carbon (g kg-1), soil pH, sand, silt and clay fractions (%), bulk density (kg m-3), cation-exchange capacity (cmol+/kg), coarse fragments (%), soil organic carbon stock (t ha-1), depth to bedrock (cm), World Reference Base soil groups, and USDA Soil Taxonomy suborders. Our predictions are based on global spatial prediction models which we fitted, per soil variable, using a compilation of major international soil profile databases (ca. 110,000 soil profiles), and a selection of ca. 75 global environmental covariates representing soil forming factors. Results of regression modeling indicate that the most useful covariates for modeling soils at the global scale are climatic and biomass indices (based on MODIS images), lithology, and taxonomic mapping units derived from conventional soil survey (Harmonized World Soil Database). Prediction accuracies assessed using 5–fold cross-validation were between 23–51%. Conclusions/Significance SoilGrids1km provide an initial set of examples of soil spatial data for input into global models at a resolution and consistency not previously available. Some of the main limitations of the current version of SoilGrids1km are: (1) weak relationships between soil properties/classes and explanatory variables due to scale mismatches, (2) difficulty to obtain covariates that capture soil forming factors, (3) low sampling density and spatial clustering of soil profile locations. However, as the SoilGrids system is highly automated and flexible, increasingly accurate predictions can be generated as new input data become available. SoilGrids1km are available for download via under a Creative Commons Non Commercial license.
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