Methodologies for Global Soil Mapping

2010 ◽  
pp. 429-436 ◽  
Author(s):  
B. Minasny ◽  
A.B. McBratney
Keyword(s):  
Soil Mapping ◽  
Global Soil

scholarly journals Standardised soil profile data to support global mapping and modelling (WoSIS snapshot 2019)

2019 ◽  
Author(s):  
Niels H. Batjes ◽  
Eloi Ribeiro ◽  
Ad van Oostrum
Keyword(s):  
Soil Profile ◽  
Soil Property ◽  
Soil Mapping ◽  
Digital Soil Mapping ◽  
Total Carbon ◽  
System Modelling ◽  
Profile Data ◽  
Wide Range ◽  
Global Soil ◽  
Soil Information

Abstract. The World Soil Information Service (WoSIS) provides quality-assessed and standardised soil profile data to support digital soil mapping and environmental applications at broad scale levels. Since the release of the first WoSIS snapshot, in July 2016, many new soil data were shared with us, registered in the ISRIC data repository, and subsequently standardised in accordance with the licences specified by the data providers. Soil profile data managed in WoSIS were contributed by a wide range of data providers, therefore special attention was paid to measures for soil data quality and the standardisation of soil property definitions, soil property values (and units of measurement), and soil analytical method descriptions. We presently consider the following soil chemical properties (organic carbon, total carbon, total carbonate equivalent, total Nitrogen, Phosphorus (extractable-P, total-P, and P-retention), soil pH, cation exchange capacity, and electrical conductivity) and physical properties (soil texture (sand, silt, and clay), bulk density, coarse fragments, and water retention), grouped according to analytical procedures (aggregates) that are operationally comparable. Further, for each profile, we provide the original soil classification (FAO, WRB, USDA, and version) and horizon designations insofar as these have been specified in the source databases. Measures for geographical accuracy (i.e. location) of the point data as well as a first approximation for the uncertainty associated with the operationally defined analytical methods are presented, for possible consideration in digital soil mapping and subsequent earth system modelling. The latest (dynamic) set of quality-assessed and standardised data, called wosis_latest, is freely accessible via an OGC-compliant WFS (web feature service). For consistent referencing, we also provide time-specific static snapshots. The present snapshot (September 2019) comprises 196,498 geo-referenced profiles originating from 173 countries. They represent over 832 thousand soil layers (or horizons), and over 5.8 million records. The actual number of observations for each property varies (greatly) between profiles and with depth, this generally depending on the objectives of the initial soil sampling programmes. In the coming years, we aim to fill gradually gaps in the geographic and feature space, this subject to the sharing of a wider selection of soil profile data for so far under-represented areas and properties by our existing and prospective partners. Part of this work is foreseen in conjunction within the Global Soil Information System (GloSIS) being developed by the Global Soil Partnership (GSP). The WoSIS snapshot – September 2019 is archived and freely accessible at https://doi.org/10.17027/isric-wdcsoils.20190901 (Batjes et al., 2019).

Digital soil mapping: the challenge to obtain the best soil dataset and create a precise environmental model to support land use management at a national level (Ecuador).

2020 ◽  
Author(s):  
Daphne Armas ◽  
Mário Guevara ◽  
Fernando Bezares ◽  
Rodrigo Vargas ◽  
Pilar Durante ◽  
...  
Keyword(s):  
Land Use ◽  
Information System ◽  
Soil Properties ◽  
Soil Profile ◽  
Soil Mapping ◽  
Digital Soil Mapping ◽  
Land Use Management ◽  
National Scale ◽  
Global Soil ◽  
Soil Information

<p>One of the biggest challenges for digital soil mapping is the limited of field soil information (e.g., soil profile descriptions, soil sample analysis) for representing soil variability across scales. Global initiatives such as the Global Soil Partnership (GSP) and the development of a <strong>Global Soil Information System</strong> (GloSIS), World Soil Information Service (WoSis) or SoilGrids250m for global pedometric mapping highlight new opportunities but the crescent need of new and better soil datasets across the world. Soil datasets are increasingly required for the development of soil monitoring baselines, soil protection and sustainable land use strategies, and to better understand the response of soils to global environmental change.  However, soil surveys are a very challenging task due to their high acquisition costs such data and operational complexity. The use of legacy soil data can reduce these sampling efforts.</p><p>The main objective of this research was the rescue, synthesis and harmonization of legacy soil profile information collected between 2009 and 2015 for different purposes (e.g., soil or natural resources inventory) across Ecuador. This project will support the creation of a soil information system at the national scale following international standards for archiving and sharing soil information (e.g., GPS or the GlobalSoilMap.net project). This new information could be useful to increase the accuracy of current digital soil information across the country and the future development of digital soil properties maps.</p><p>We provided an integrated framework combining multiple data analytic tools (e.g., python libraries, pandas, openpyxl or pdftools) for the automatic conversion of text in paper format (e.g., pdf, jpg) legacy soil information, as much the qualitative soil description as analytical data,  to usable digital soil mapping inputs (e.g., spatial datasets) across Ecuador. For the conversion, we used text data mining techniques to automatically extract the information. We based on regular expressions using consecutive sequences algorithms of common patterns not only to search for terms, but also relationships between terms. Following this approach, we rescued information of 13.696 profiles in .pdf, .jpg format and compiled a database consisting of 10 soil-related variables.</p><p>The new database includes historical soil information that automatically converted a generic tabular database form (e.g., .csv) information.</p><p>As a result, we substantially improved the representation of soil information in Ecuador that can be used to support current soil information initiatives such as the WoSis, Batjes et al. 2019, with only 94 pedons available for Ecuador, the Latin American Soil Information System (SISLAC, http://54.229.242.119/sislac/es),  and the United Nations goals  towards increasing soil carbon sequestration areas or decreasing land desertification trends.  In our database there are almost 13.696 soil profiles at the national scale, with soil-related (e.g., depth, organic carbon, salinity, texture) with positive implications for digital soil properties mapping. </p><p>With this work we increased opportunities for digital soil mapping across Ecuador. This contribution could be used to generate spatial indicators of land degradation at a national scale (e.g., salinity, erosion).</p><p>This dataset could support new knowledge for more accurate environmental modelling and to support land use management decisions at the national scale.</p><p> </p>

scholarly journals Standardised soil profile data to support global mapping and modelling (WoSIS snapshot 2019)

2020 ◽  
Vol 12 (1) ◽  
pp. 299-320 ◽  
Author(s):  
Niels H. Batjes ◽  
Eloi Ribeiro ◽  
Ad van Oostrum
Keyword(s):  
Soil Profile ◽  
Soil Property ◽  
Soil Mapping ◽  
Digital Soil Mapping ◽  
Total Carbon ◽  
System Modelling ◽  
Profile Data ◽  
Wide Range ◽  
Global Soil ◽  
Soil Information

Abstract. The World Soil Information Service (WoSIS) provides quality-assessed and standardised soil profile data to support digital soil mapping and environmental applications at broadscale levels. Since the release of the first “WoSIS snapshot”, in July 2016, many new soil data were shared with us, registered in the ISRIC data repository and subsequently standardised in accordance with the licences specified by the data providers. Soil profile data managed in WoSIS were contributed by a wide range of data providers; therefore, special attention was paid to measures for soil data quality and the standardisation of soil property definitions, soil property values (and units of measurement) and soil analytical method descriptions. We presently consider the following soil chemical properties: organic carbon, total carbon, total carbonate equivalent, total nitrogen, phosphorus (extractable P, total P and P retention), soil pH, cation exchange capacity and electrical conductivity. We also consider the following physical properties: soil texture (sand, silt, and clay), bulk density, coarse fragments and water retention. Both of these sets of properties are grouped according to analytical procedures that are operationally comparable. Further, for each profile we provide the original soil classification (FAO, WRB, USDA), version and horizon designations, insofar as these have been specified in the source databases. Measures for geographical accuracy (i.e. location) of the point data, as well as a first approximation for the uncertainty associated with the operationally defined analytical methods, are presented for possible consideration in digital soil mapping and subsequent earth system modelling. The latest (dynamic) set of quality-assessed and standardised data, called “wosis_latest”, is freely accessible via an OGC-compliant WFS (web feature service). For consistent referencing, we also provide time-specific static “snapshots”. The present snapshot (September 2019) is comprised of 196 498 geo-referenced profiles originating from 173 countries. They represent over 832 000 soil layers (or horizons) and over 5.8 million records. The actual number of observations for each property varies (greatly) between profiles and with depth, generally depending on the objectives of the initial soil sampling programmes. In the coming years, we aim to fill gradually gaps in the geographic distribution and soil property data themselves, this subject to the sharing of a wider selection of soil profile data for so far under-represented areas and properties by our existing and prospective partners. Part of this work is foreseen in conjunction within the Global Soil Information System (GloSIS) being developed by the Global Soil Partnership (GSP). The “WoSIS snapshot – September 2019” is archived and freely accessible at https://doi.org/10.17027/isric-wdcsoils.20190901 (Batjes et al., 2019).

Global soil mapping with Neural Networks 

2021 ◽  
Author(s):  
Giulio Genova ◽  
Luis de Sousa ◽  
Tanja Mimmo ◽  
Luigi Borruso ◽  
Laura Poggio
Keyword(s):  
Neural Networks ◽  
Prediction Models ◽  
Traditional Approach ◽  
Contextual Information ◽  
Water Security ◽  
Soil Mapping ◽  
Digital Soil Mapping ◽  
Environmental Covariates ◽  
Complex Architectures ◽  
Global Soil

<p>High quality global soil maps are crucial to face several challenges such as reducing soil erosion, climate change adaptation and mitigation, ensuring food and water security, and biodiversity conservation planning. To obtain accurate and robust soil properties maps, research and development are necessary to identify the most appropriate prediction models and to develop efficient and robust workflows. A few recent studies used Artificial Neural Networks (ANN) in Digital Soil Mapping, in some cases improving the accuracy of the predicted maps compared to other methods like Random Forest (RF). In this study we tested different ANN architectures on a global top-soil dataset of ca. 110 000 samples, comparing the results for the different architectures with the more traditional approach of RF. The target variables considered are pH, Soil Organic Carbon, Sand, Silt, and Clay. We selected 40 environmental covariates from a pool of over 400 to represent the most important soil forming factors. We tried simpler architectures (single input – single target) using point observations for one target variable with corresponding raster cell values for spatially explicit environmental covariates. We also used more complex architectures (multi input - multi target) incorporating contextual information surrounding an observation (convolutional) and with multiple target variables. Preliminary results show that increasing the number of hidden layers in the neural network does not significantly influence the results, while changing the type of architecture can play a bigger role in the overall accuracy of the model. The overall prediction accuracy of the ANN was comparable with the RF model. We conclude that ANN are a promising, relatively new, approach for Global Digital Soil Mapping and that further research is needed to improve performance.</p>

Towards methodologies for global soil mapping

GlobalSoilMap ◽  
2014 ◽  
pp. 291-294 ◽  
Author(s):  
A Nikiforova ◽  
M Fleis ◽  
M Borisov
Keyword(s):  
Soil Mapping ◽  
Global Soil

The evolving methodology for global soil mapping

GlobalSoilMap ◽  
2014 ◽  
pp. 215-220 ◽  
Author(s):  
J Padarian ◽  
B Minasny ◽  
A McBratney
Keyword(s):  
Soil Mapping ◽  
Global Soil

Humus state of chernozem at different ways of tillage in the agrosystems of the left-bank forest steppe of Ukraine

2015 ◽  
Vol 2 (3) ◽  
pp. 61-77
Author(s):  
O. Demydenko ◽  
V. Velychko
Keyword(s):  
Soil Cover ◽  
Forest Steppe ◽  
Left Bank ◽  
Energy Reserves ◽  
Soil Resources ◽  
Global Soil ◽  
Humus Accumulation ◽  
By Products ◽  
The Way

The contemporary condition of soil cover in Ukraine is characterized. The attention is focused onto widespread degradation processes in soils. The causes that determine the development of these negative processes are considered. The contemporary informational support for the condition of soil cover in Ukraine is estimated. In general, the current available information is of narrow-departmental nature, obtained by different methods and non-correlated monitoring programs. As a rule, it is stored in under-structured databases, incompatible with other information systems; mainly recorded on paper media unusable with modern technologies, whereby such information resources are diffi cult to be compiled together. These disadvantages are strong constraints against consistent usage of materials for evaluation, forecast and management of changes in the soil cover. The Soil Observation program should thereby be combined with Agrochemical Passportization and ecology-ameliora- tive monitoring; in other words, the application of innovative soil-agrochemical methodology is considered. Each individual type of surveys shall complement the others, and taken altogether, they shall constitute a con- sistent Information System, capable of solving the problems of assessing the condition, forecasting, manage- ment, usage and protection of soil resources. The monitoring procedures should be conducted on the basis of a new soil concept in line with unifi ed programs and methods, so as to meet European approaches to the maxi- mum extent. Such a technical composition enables getting information on present-day processes in soils, and is the only combination that actually helps us to “ecologize” our knowledge of soils, which is the leading trend in the scope of global soil-science. Thus obtained results will serve as a State-owned tool which would subse- quently facilitate the use and protection of soil resources all over the country, to be involved in a united global soil-information scope. The attention is focused onto social signifi cance of the information on soils and their fertility in terms of land resources optimization, as well as the formation of sustainable land use in Ukraine. Aim. To demonstrate the long-term effect of different ways of tillage of typical low-humus chernozem on the change in humus content and composition and the direction of transformation processes of organic fertili- zers. To study the changes in the structure of energy reserves in group and fractional composition of humus in typical low-humus light-loamy chernozem of the Forest-Steppe of Ukraine. Methods. Field, laboratory, microbiological, computational, mathematical and statistical. Results. It was determined that in conditions of long-term subsurface tillage the most effi cient humus accumulation occurs in the 0–20 cm layer of chernozem with simultaneous increase in its content in the lower part of the processed layer without any accumulation differentiation. Surface tillage leads to expressed differentiation in humus accumulation in the 0–20 cm layer of soil (0.005 % per year). When 6 t/ha of humus are replaced by 7 t/ha of by-products the intensity of humus accumulation is decreasing regardless of the way of tillage, but humus accumulation was found to be the most effi cient for subsurface tillage. The application of subsurface tillage leads to the increase in the ratio of C HA : C FA , which is conditioned by the increase in the humifi cation of plant remains of by-products in the 0−20 cm layer of soil by 110–112 % – for subsurface tillage, and by 105 % – for surface tillage. Conclusions. It was established that systematic subsurface tillage of typical chernozem of the Left-Bank Forest-Steppe of Ukraine leads to the structuring both of the total reserves of energy С org , and its quality content, aimed at the increase in the intensity of the processes of humifi cation and accumulation of organic carbon, and the decrease in miner- alization. The ratio of energy reserves С org of humic acids to fulvic acids in the 0−30 cm layer of chernozem is 1.85−1.87 regardless of the way of tillage, which testifi es to the repeatability of humus accumulation, but the total reserves of energy С org was higher for subsurface tillage (+ 31 Teracalorie/ha) compared to deep plough- ing. As for the surface tillage, the energy enrichment was at the level of deep ploughing.

Analysis of Information Support for the Condition of Soil Resources in Ukraine

2015 ◽  
Vol 2 (2) ◽  
pp. 77-84 ◽  
Author(s):  
S. Baliuk ◽  
V. Solovey ◽  
M. Zakharova ◽  
A. Kucher ◽  
S. Truskavetskyi
Keyword(s):  
Soil Cover ◽  
Sustainable Land Use ◽  
Information Support ◽  
Land Resources ◽  
Soil Resources ◽  
Diffi Cult ◽  
Other Information ◽  
Global Soil ◽  
Individual Type ◽  
Available Information

The contemporary condition of soil cover in Ukraine is characterized. The attention is focused onto widespread degradation processes in soils. The causes that determine the development of these negative processes are considered. The contemporary informational support for the condition of soil cover in Ukraine is estimated. In general, the current available information is of narrow-departmental nature, obtained by different methods and non-correlated monitoring programs. As a rule, it is stored in under-structured databases, incompatible with other information systems; mainly recorded on paper media unusable with modern technologies, whereby such information resources are diffi cult to be compiled together. These disadvantages are strong constraints against consistent usage of materials for evaluation, forecast and management of changes in the soil cover. The Soil Observation program should thereby be combined with Agrochemical Passportization and ecology-ameliora- tive monitoring; in other words, the application of innovative soil-agrochemical methodology is considered. Each individual type of surveys shall complement the others, and taken altogether, they shall constitute a con- sistent Information System, capable of solving the problems of assessing the condition, forecasting, manage- ment, usage and protection of soil resources. The monitoring procedures should be conducted on the basis of a new soil concept in line with unifi ed programs and methods, so as to meet European approaches to the maxi- mum extent. Such a technical composition enables getting information on present-day processes in soils, and is the only combination that actually helps us to “ecologize” our knowledge of soils, which is the leading trend in the scope of global soil-science. Thus obtained results will serve as a State-owned tool which would subse- quently facilitate the use and protection of soil resources all over the country, to be involved in a united global soil-information scope. The attention is focused onto social signifi cance of the information on soils and their fertility in terms of land resources optimization, as well as the formation of sustainable land use in Ukraine.

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