Soil Information System Research Articles

Information soil database of Republic of Khakassia

Relevance. Currently, a number of soil information systems of various levels and directions have been created, the studies on the creation and application of soil databases are represented insufficiently in the Republic of Khakassia today.Methods. Were carried out by common methods: at-ground soil and geobotanical studies, cartographic method, physical and agrophysical, agrochemical methods of soil researches. For the database creation the Microsoft Access software package was used, which systematized and unified a large amount of experimental data.Results. Based on the long-term soil research, the database “Agricultural Soils of the foothills of the Western Sayan of Khakassia” with a wide range of soil characteristics for various purposes and uses was formed and registered. The database contains attribute information about the current state of arable and postagrogenic soils in the foothills of the Western Sayan of the Republic of Khakassia. The set of independent materials is presented in the form of tables, queries, forms, reports and catalogues of text files (.docx), photos (.jpeg), which contain information about soil forming factors, soil classification and distribution by natural and climatic zones on the research territory. Currently, the database includes a description of 17 representative soil profiles with an optimal set of indicators, a detailed description of each pedologic horizon, an accurate geographical reference and a digital photography of each reference soil profile. It contains the taxonomic attribute of the dominant and codominant soils in various classification systems (SC RF; WRB, 2006; FAO, 1988). The main information object is the type (subtype) of soil, which includes systematized factors of soil criteria (a list of 18 sets): morphological description of the soil profile, indicators of pedological property, chemical, physico-chemical, agrophysical, hydrophysical and other indicators. The contemporary database with a variety of pedologic properties will serve as a basis for the rational use and protection of soils. Geographical coordinates of soil profiles in the database will allow to display them on the maps of Russia and to put them in the Unified state register of soil resources of Russia.

Soil mapping and priorities in Denmark

• Denmark benefits from a strong soil survey history and the availability of soil data at a national scale. • DSM and DSA products contribute to enriching the Danish soil database and establishing a national digital soil information system. • Lack of awareness of soils in Danish society can be linked to a gap in education. • Soil sealing, soil organic matter decline, compaction and erosion are the major soil threats in Denmark.

Connecting Students’ Interests to a Learning Context: The Case of Ecosystem Services in STEM Education

Interest in a subject matter is a powerful motivation in education. Prior knowledge of students’ interests can be helpful in teaching the concept of ecosystem services (ES) and disservices (ED), which is increasingly being used in science, technology, engineering, and mathematics (STEM) education, including soil science. Study objectives were to evaluate prior students’ soil science-related interests and use them to expand the learning context of a laboratory exercise on soil reaction (pH) with ES/ED in an online introductory soil science course (FNR 2040: Soil Information Systems) taught at Clemson University. Students from multiple fields of study (environmental and natural resources, forestry, and wildlife biology) completed the laboratory exercise in Fall 2021. This exercise on soil regulating and provisioning ES/ED included a sequence of reusable learning objects (RLOs), which are self-contained online modules frequently used for e-learning. Laboratory activities included calculating the liming replacement cost of soil inorganic carbon (SIC) and avoided social cost of carbon (SC-CO2) from soil inorganic carbon (SIC) stocks in the assigned soil. The laboratory exercise was effective in increasing the familiarity with the concept of ES/ED (+39.4 increase in “extremely familiar” category) and the concept of SIC (+44.7 increase in “moderately familiar” category). The graded online quiz consisted of 9 questions and was taken by 55 students with an average score of 7.0 (out of 9). A post-assessment survey found that the laboratory was an effective way to learn about soil pH, SIC, and their ES/ED. Detailed student comments showed learning enjoyment (e.g., calculations, good experience), the value of multimedia (e.g., video, PowerPoint), the learning flexibility (e.g., separate parts), content applicability (e.g., economic values of services), and constructive criticism (e.g., clearer instructions, lots of information). A word cloud based on comments by the students about their soil ES laboratory exercise experience indicated the most common words submitted by students to describe their experience, such as “soil”, “calculations”, “enjoyed”, “learning”, and “values”, among others. Applied recommendations are proposed to develop future exercises based on the alignment of students’ interests, STEM subject matter, and ES/ED applications.

Digital soil assessment in support of a soil information system for monitoring salinization and sodification in agricultural areas

AbstractSalinization and sodification are types of degradation associated with the accumulation of salts and alkaline materials in the soil. They gradually advance unnoticed till severe degradation appears if not properly controlled. Relevant soil information is not routinely kept by many countries thus contributing to their advancement particularly in agricultural areas where their impacts have huge consequences on food security. We developed a 3‐step protocol to detect salinization and sodification advancement at different spatial scales and support soil information system development. The first step establishes an indicator database focusing on measured soil Electrical Conductivity (EC), pH, Exchangeable Sodium Percent (ESP), and a suit of environmental covariates. The second step outlines data harmonization strategies and classification of salinization and sodification problems. It also incorporates digital soil mapping for spatial information on salinization or sodification. The third step has time‐series modelling of salinization and sodification using mixed‐effects approach to improve hotspot detection in agricultural areas. The protocol was tested in Afghanistan, Sudan, and Lesotho using time‐series data between 2001 and 2018. It successfully identified salt and soda accumulation at different soil depths with more than 80% accuracy on holdout samples. In Sudan and Afghanistan, it identified topsoils as more prone to salinization than the subsoils and consequently depicted more salt accumulation in topsoils than subsoils in agricultural areas. In Lesotho, it identified emerging subsoil sodification. The protocol has potential for supporting the development of soil information on salinization and sodification which is currently lacking at many national and regional levels.

Teaching Field Data Crowdsourcing Using a GPS-Enabled Cellphone Application: Soil Erosion by Water as a Case Study

Crowdsourcing is an important tool for collecting spatio-temporal data, which has various applications in education. The objectives of this study were to develop and test a laboratory exercise on soil erosion by water and field data crowdsourcing in an online introductory soil science course (FNR 2040: Soil Information Systems) at Clemson University. Students from different STEM disciplines (wildlife biology, forestry, and environmental and natural resources) participated in the study in the fall of 2021. They completed a sequence of self-contained digital teaching modules or reusable learning objects (RLOs), which are often used in online learning. The exercise included a field exercise and learning module to teach students about different types of water-based soil erosion as well as field data collection and crowdsourcing tools. As a result of this exercise, student familiarity with crowdsourcing was effectively increased, as shown by the post-assessment survey with a +31.2% increase in the “moderately familiar” category and a +28.3% increase in the “extremely familiar” category. The online quiz contained ten questions and was taken by 56 students with an average score of 9.5 (out of 10). A post-assessment survey found that most of the students indicated that the laboratory was an effective learning experience about field data crowdsourcing using a GPS-enabled cellphone application. Detailed students’ comments indicated enjoyment of learning (e.g., data collection, learning about different technologies), the value of multimedia (e.g., ArcGIS Survey123, cellphone), the flexibility of learning (e.g., field work), the content applicability (e.g., actual field examples of erosion by water), and criticism (e.g., technical issues). A word cloud derived from students’ comments about their laboratory exercise experience indicated the most frequent words used by students, such as “erosion”, “enjoyed”, and “different”, among others. Incorporating a learning module and field exercise using modern data collection technology into an undergraduate soil science education course enabled students to understand the value and methods for leveraging cellphone-based field collection methods to crowdsource data for environmental assessment. Practical recommendations for planning and executing future crowdsourcing exercises were developed using the current study as an example.

Soil and Climate Geographic Information System Data-Derived Risk Mapping for Grape Phylloxera in Washington State.

Grape phylloxera (Daktulosphaira vitifoliae, syn. Viteus vitifoliae), a destructive root and foliar pest of grapevines, occurs in almost all viticulture regions worldwide. However, certain regions have remained “phylloxera free.” Until recently, this included Washington state (United States), where this insect is regulated as a quarantine pest by Washington State Department of Agriculture. In 2019, established phylloxera populations were discovered in Washington. Phylloxera is typically managed by using resistant or tolerant rootstocks. In Washington, most wine grapes are grown on their own roots of the susceptible species Vitis vinifera instead of grafted rootstock, and thus, are at high risk of vine death should they become infested with phylloxera. This article reports development of a phylloxera risk map for Washington state using geographical soil texture (sand content) and soil temperature data. Weighted averages of soil texture data (mapping year: 2016, depth: 0–100 cm) were obtained from United States Department of Agriculture-Natural Resource Conservation Service (USDA-NRCS) and soilgrids. Soil temperature data were obtained from over 200 weather stations of Washington State University’s AgWeatherNet network. Threshold-based classifications were performed in Quantum GIS software on the rasterized soil sand content and temperature independently to derive low, moderate, and high-risk areas, with risk defined as site suitability for optimal phylloxera development. The validation identified 22 out of 23 confirmed phylloxera-positive sites as “high risk,” and one site as “moderate risk” when considering soil sand content alone. Soil temperature data alone classified 10 sites as “high risk” and 13 sites as “low risk.” When soil sand content was combined with soil temperature (as a risk modifier), 10 sites were classified as “high risk,” 12 sites as “high-moderate risk” and one site as “moderate-low” risk. Ground-truth comparisons of confirmed positive sites for phylloxera agreed with past research suggesting that soil sand content is the dominant factor influencing phylloxera infestation. Pertinent risk assessment can be an important component for vineyard decision-making, including whether to use rootstocks in vineyard development or replant scenarios. It may also help to focus the initial scouting and identification efforts to sites and may be helpful when tracking and developing solutions for quarantine pests, such as phylloxera.

Provincial-scale digital soil mapping using a random forest approach for British Columbia

Although British Columbia (BC), Canada, has a rich history of producing conventional soil maps (CSMs) between 1925 and 2000, the province still lacks a detailed soil map with a comprehensive coverage due to the cost and time required to develop such a product. This study builds on previous digital soil mapping (DSM) research in BC and develops provincial-scale maps. Soil taxonomic classes (e.g., great groups and order) and parent material classes were mapped at a 100 m spatial resolution for BC (944 735 km2). Training points were generated from detailed and semi-detailed soil survey maps. The training points were intersected with 26 topographic indices for mapping parent materials with an additional 9 climatic and vegetation indices for mapping soil classes. The soil–environmental relationships were inferred using the random forest (RF) classifier. The fitted models were used to predict 23 soil great groups, 9 soil orders, and 10 parent material classes. Accuracy assessments were performed using n = 14 570 validation points for parent material classes and n = 14 316 validation points for soil classes, acquired from the BC Soil Information System. The accuracy rates for soil great groups, orders, and parent material classes were 55%, 62%, and 69%, respectively, and kappa coefficients were 0.37, 0.41, and 0.59, respectively. This study demonstrated that when RF was trained using CSMs, the accuracy for the resulting DSM was higher than the original CSM. To assess prediction uncertainties, ignorance uncertainty maps were developed using class-probability layers generated by the RF models.

S-map parameters for APSIM

Agroecosystem models have become an important tool for impact assessment studies, and their results are often used for management and policy decisions. Soil information is a key input for these models, yet site-specific soil property data are often not available, and soil databases are increasingly being used to provide input parameters. For New Zealand, the digital spatial soil information system S-map provides geospatial data on a range of soil characteristics, including estimates of soil water properties. We describe a protocol for how properties from S-map can be used as input parameters for the APSIM (Agricultural Production Systems sIMulator) framework. Finally, we investigate how changes in the physical description of soil layers, and soil organic matter pools, affect the various outputs of APSIM.•This paper presents a description of how information from S-map, a digital soil map of New Zealand, can be used for building a soil description for APSIM.•A sensitivity analysis shows the effect of soil layering and the set-up setup, size, and distribution of SOM pools on model outputs, including plant growth and N leaching

A flexible selection tool for the inclusion of soil biology methods in the assessment of soil multifunctionality

Soil biota contribute to the delivery of multiple soil functions. However, soil biological methods are highly underrepresented in the assessment of soil functionality in agricultural production systems. Here we present a flexible tool to support decision-making during the selection process of soil biological methods for monitoring soil functions. This tool is based on a structured and conceptual framework that connects soil biota to soil functions through their contribution to different soil processes. The methods assessed by the tool were selected as a result of a thorough literature review. Soil biology experts supported the development of the tool (i) by providing feedback on the reviewed methods through a survey and (ii) by determining the relevance of different soil biota to the soil processes related to soil multifunctionality during a workshop. The tool is freely accessible online at the Biological Soil Information System (BIOSIS) platform, where researchers or users with an understanding of research practices can interact with the tool to define the context of their assessment and preferences for technical criteria of the methods. By incorporating user input, this flexible tool can help inform a wide variety of research and assessment programs interested in applying soil biological methods to monitor soil multifunctionality at different scales.

Spatial and temporal dynamics of soil organic carbon stock and carbon sequestration affected by major land-use conversions in Northwestern highlands of Ethiopia

Soil organic carbon (SOC) is the major component of the terrestrial carbon (C) budget, a key indicator of environmental sustainability. So, estimating SOC stock and soil carbon (C) sequestration dynamics is important for evidence-based and carbon-conscious decisions. Quantification of SOC stock and soil C sequestration affected by land-use changes (LUCs) have received much attention in addressing food and climate security. This study aims to estimate the dynamics of SOC stock, soil C sequestration and associated soil parameters affected by major LUCs from 2012 to 2021 in Awi highlands of Amhara Regional State of Ethiopia. The study area has experienced dramatic LUC, particularly plantation and growing of Acacia decurrens (J.C. Wendl.) tree followed by recurrent deforestation and then cropping and back to the plantation. The study quantified spatial and temporal dynamics of SOC stock, soil C sequestration and associated changes affected by the LUCs. A total of 22 topsoil (0–20 cm) legacy data was obtained from the Ethiopian Soil Information System (EthiSIS) database of 2012. The same number of samples were collected at the same locations in 2021 by using the same sampling procedure as that of 2012. In addition, the same number of core samples were collected in 2021 for bulk density analysis. To estimate the unmeasured bulk density of legacy data, we applied a pedotransfer function. We used empirical equations and basic statistics to assess changes in SOC stock and C sequestration rate between the two periods. Statistically significant variation (P < 0.01) in SOC stock and C sequestration was observed between the two periods. LUC from acacia plantation to croplands caused a decline of SOC stock by −30.16%, and it also caused the decline of total nitrogen stock, available phosphorus, cation exchange capacity (CEC). However, the reverse LUC caused an increase in SOC by 27.74% and the abovementioned soil parameters. LUC from plantation forest to cropland caused emission of 8.3 tons of CO2 year−1. Generally, overall LUCs caused the net negative change in SOC stock by (−2.42 %) and associated soil parameters in the last ten years. Our study provides evidence that overall LUCs in the current study site caused a decline in SOC stock, along with associated soil parameters with carbon emitted to the atmosphere. Hence, sustainable land-use management options which can offset losses in SOC stock should be implemented soon.

Spatial and Temporal Changes of Groundwater Storage in the Quaternary Aquifer, UAE

To study the temporal and spatial variations of the groundwater quantity and quality in response to intensive groundwater exploitation from the Quaternary aquifer in UAE, a water budget model with a cell size of one km2 was developed. The available historical records of groundwater levels and salinity have been used to develop the water table and salinity maps of UAE for the years 1969, 2005, 2010, and 2015. The available water resources and soil information system was used to facilitate validity, cogency, and consistency of the groundwater analysis. The spatial analysis module of GIS was used to define the aquifer setting, saturated thickness, aquifer base elevation, effective porosity, and groundwater salinity at each grid cell. The obtained results indicated that the volume of fresh groundwater resources in the Quaternary aquifer in UAE has decreased from 238 km3 in 1969 to around 10 km3 in 2015. A major part of these depleted fresh groundwater resources was replaced by brackish water, and, therefore, the total groundwater storage in this aquifer has only decreased from 977 in 1969 to 922 km3 in 2015, respectively. If the same groundwater exploitation continues, the freshwater storage in the surficial aquifer might be totally depleted in agricultural areas. Most probably, the brackish groundwater resources will be exploited. In such areas, more attention should be devoted to the management of brackish water resources to avoid the exacerbation of the saltwater intrusion problem. Despite the fact that the obtained results indicate the negative impacts of the improper water resources management in a small part of the arid area, the learned lessons are valid for other arid countries, in particular, using the proper steady state boundary conditions for the initial conditions in modeling the available future management alternatives.

Incorporating Ecosystem Services into STEM Education

The framework of ecosystem services (ES) and disservices (ED) has increasingly been used in various science, technology, engineering, and mathematics (STEM) disciplines, including soil science. The objectives of this study were to use ES/ED concepts to extend and test an existing lecture and laboratory exercise on soil organic carbon (SOC) in an online introductory soil science course (FNR 2040: Soil Information Systems) taught to Clemson University students from various STEM disciplines (forestry, wildlife biology, and environmental and natural resources) in Fall 2020. The laboratory exercise was extended with a series of reusable learning objects (RLOs), which are self-contained digital modules commonly utilized in e-learning. The laboratory exercise consisted of identifying ES and calculating the avoided social cost of carbon (SC-CO2) from soil organic carbon stocks in the assigned soil’s topsoil horizon. The laboratory exercise effectively increased student familiarity with ES/ED as indicated by the post-assessment survey with a +24.4% increase in the moderately familiar category and a +36.1% increase in the extremely familiar category. The graded online quiz consisted of ten questions and was taken by 51 students with an average score of 8.7 (out of 10). A post-assessment survey indicated that most of the students found that the laboratory was an effective way to learn about ES/ED with examples from soil science. Detailed students’ comments indicated enjoyment of learning (e.g., calculations, applying new knowledge), the value of multimedia (e.g., PowerPoint, video), the flexibility of learning (e.g., different parts in the laboratory), the applicability of content (e.g., real-world examples), and criticism (e.g., tedious calculations). A word cloud based on students’ comments about their experience with the laboratory exercise on soil ES indicated the most common words used by students to describe their experience, such as “soil services”, “learning”, “enjoyed”, and “ecosystems”, among others. Incorporating ES/ED into an undergraduate STEM course enabled students to connect ES/ED provided by soil with the societal systems reliant on the soil resources.

Fe-Mn concentrations in upland loess soils in mid-continental north America: A step towards dynamic soil survey

Iron-manganese (Fe-Mn) concentrations are common morphological indicators of soil oxidation-reduction reactions and are widely used to infer soil hydrology. The factors determining occurrence and distribution of Fe-Mn concentrations at the continental scale have been rarely studied. The objective of this study was to explore the distribution of Fe-Mn concentrations in upland loess soils and identify their favorable environment conditions in the mid-continental North America. A total of 3966 soil profiles were collected from the National Soil Information System database (NASIS). A decision tree (DT) model was used to analyze the spatial relationships between Fe-Mn concentration formation and its relevant environmental factors (climate, soil properties, and land use/land cover), and to identify key factors of Fe-Mn concentrations distribution and occurrence in upland loess soils. The DT model was evaluated with 25% validation dataset with an accuracy of 79%. Results showed that Fe-Mn concentrations were more likely to occur in mesic areas with large precipitation and low internal soil drainage rates, compared to frigid and thermic areas with low precipitation and large internal soil drainage rates. Annual precipitation and temperature were identified as the most important climatic factors influencing the occurrence of Fe-Mn concentrations and showed a complex interaction with soil properties at multiple scales. Soil properties related to potential wet to saturated soil conditions were also important for the occurrence of Fe-Mn concentrations. Results demonstrated the importance of using knowledge of pedogenesis in the selection of environmental covariates and the interpretation of DT model results. Understanding where Fe-Mn concentrations tend to form in the landscape will contribute to improving decisions about proper use of soil that may be limited by wetness and possible inferences about climate influences.

African soil properties and nutrients mapped at 30\xa0m spatial resolution using two-scale ensemble machine learning

Soil property and class maps for the continent of Africa were so far only available at very generalised scales, with many countries not mapped at all. Thanks to an increasing quantity and availability of soil samples collected at field point locations by various government and/or NGO funded projects, it is now possible to produce detailed pan-African maps of soil nutrients, including micro-nutrients at fine spatial resolutions. In this paper we describe production of a 30 m resolution Soil Information System of the African continent using, to date, the most comprehensive compilation of soil samples (N approx 150,000) and Earth Observation data. We produced predictions for soil pH, organic carbon (C) and total nitrogen (N), total carbon, effective Cation Exchange Capacity (eCEC), extractable—phosphorus (P), potassium (K), calcium (Ca), magnesium (Mg), sulfur (S), sodium (Na), iron (Fe), zinc (Zn)—silt, clay and sand, stone content, bulk density and depth to bedrock, at three depths (0, 20 and 50 cm) and using 2-scale 3D Ensemble Machine Learning framework implemented in the mlr (Machine Learning in R) package. As covariate layers we used 250 m resolution (MODIS, PROBA-V and SM2RAIN products), and 30 m resolution (Sentinel-2, Landsat and DTM derivatives) images. Our fivefold spatial Cross-Validation results showed varying accuracy levels ranging from the best performing soil pH (CCC = 0.900) to more poorly predictable extractable phosphorus (CCC = 0.654) and sulphur (CCC = 0.708) and depth to bedrock. Sentinel-2 bands SWIR (B11, B12), NIR (B09, B8A), Landsat SWIR bands, and vertical depth derived from 30 m resolution DTM, were the overall most important 30 m resolution covariates. Climatic data images—SM2RAIN, bioclimatic variables and MODIS Land Surface Temperature—however, remained as the overall most important variables for predicting soil chemical variables at continental scale. This publicly available 30-m Soil Information System of Africa aims at supporting numerous applications, including soil and fertilizer policies and investments, agronomic advice to close yield gaps, environmental programs, or targeting of nutrition interventions.

THEORETICAL BASICS OF THE SCIENTIFIC TREND OF INFORMATIONAL SOIL SCIENCE

The definition of informational soil science as a new trend of soil science is proposed, and includes a system of ordering, collecting, storing and analyzing of the soil data at different hierarchical levels, obtaining continuous in space and time information on soil conditions for modeling and balanced use, reproduction and management of soils, resources based on environmental, social, environmental, economic and legal requirements. The subject of informational soil science is all aspects of the functioning of information, namely: (1) the processes of origin, transmission, storage, processing, dissemination of information about the soil, its properties and soil processes; (2) ways to manage information processes; (3) general patterns of influence of information processes on the nature of applied communications in soil science. Traditional and modern methods of analysis of soil information, which form the modern methodological apparatus of informational soil science, are also considered. Peculiarities of formation of thematic databases of soil formation factors, in particular determining geomorphological factor, and use of spatial analytical functions of soil information systems in modeling of influence of a relief on development of erosion processes of a certain territory are considered. Since informational soil science, as an applied trend of soil science, is considered an integrated scientific subject, it also uses the methods and achievements of many applied and humanitarian sciences. It can be argued that in connection with the development of a new direction of organization and analysis of soil data based on automated information systems, new terminology borrowed from computer science, computer theory and programming is widely used in soil science, the vocabulary of concepts in mathematics is significantly expanded. This is an inevitable and necessary for our science process that helps to increase its efficiency in connection with the use of modern achievements of these relatively new disciplines. Keywords: soil information; informatiology; data base; informational soil science.

Mapping a hydrophysical soil property through a comparative analysis of local and global scale approximations

Current available soil information allows building baselines to improve research, such as sustainable resource management; however, its use requires analysis of accuracy and precision that describes specific variables on local and global scales. Therefore, this study evaluated differences in the spatial distribution of water retention capacity (WRC) of the soil at a depth of 0.3 m, calculated from local general soil surveys and the global gridded soil information system (SoilGrids), using detailed or semi-detailed soil surveys as a reference, in two regions of Colombia (A and B). The qualitative and statistical analyses evaluated differences in WRC surfaces generated by the information sources. Neither information sources described WRC accurately, achieving correlations between −0.15 and 0.49 and average absolute errors between 9.65 and 19.52 mm for zones A and B, respectively. However, studies on the local scale remain within the ranges observed in the most detailed local studies. The use of products on the global scale is subject to regional analyses; nevertheless, they can be included as a covariate in digital soil mapping studies on more detailed scales.

ANALYSIS OF THE WORLDWIDE MODERN SOIL INFORMATION SYSTEMS AND SOIL DATABASES

Problem Statement and Purpose. Since the end of the ХХ century, a number of soil information systems and information databases have been developed and implement­ed. As of today, there are more than two dozen large soil information systems of various scales, which we have analyzed in order to determine the parameters and necessary resources for the development of our own soil information system. The purpose of the study was to conduct an extended analysis of the most important soil information systems. Approbation and testing of these information systems were also performed.Data &amp; Methods. In order to study the soil information systems, which cover individ­ual countries, regions or are global, a detailed analysis of (1) literature sources, mostly foreign authors, which describes the information systems, their advantages and dis­advantages, describes the structure of the database, etc; (2) available online official resources, which contain a detailed description of soil information systems, features of their creation and use, databases, as well as applied aspects; (3) downloaded and in­stalled software applications, which are separate software products of soil information systems, and allows to use and study them autonomously using PC.Results.The most well-known soil information systems SOTER, LUCAS, ESDB, NASIS, CanSIS are analyzed, the main objectives of which are to provide informa­tion on soil and landscape resources at different scales to model the potential of agri­cultural production, climate change, landscape restoration and land management, in education purposes, as well as to ensure harmonized norms and rules of soil cartog­raphy, classification, interpretation of information about soil resources. Summing up the analysis of various soil databases and information systems, it should be noted that despite the achievements, most soil information systems do not yet provide complete information for forecasting global soil changes. Methods of studying soil properties are not standardized, which complicates the harmonization of data for use within a single database. There is a need to continue work on the formalization of soil informa­tion, using the rich experience gained by soil scientists throughout human history. In this regard, it is necessary to strengthen developments in this area, which will increase the contribution of the Ukrainian school of soil science in the formalization of soil research at the global level.

IRAKA: The first Colombian soil information system with digital soil mapping products

Advances in science and technology combined with the need to handle and manage natural resources have resulted in a gradual increase in soil data availability. This has allowed characterizing, describing, or proposing projects to address issues such as soil degradation, agricultural productivity, threats, and ecosystem services. Despite the availability of soil data, users are increasingly looking for additional, timely, and reliable information in order to respond to current and future situations, such as food security and climate change. IRAKA is a soil information system for the Colombian Cundiboyacense high plateau and the first to provide additional information from available official sources. It has a modular design based on the organization of a soil database whose structure incorporated 299 profiles, 1432 samples, and 55 properties and the integration, harmonization, and standardization of 8 soil surveys conducted in the area. The structured information enabled modeling and validating physical and chemical properties through digital soil mapping and comparing different machine learning techniques, including random forest, ranger, support vector machine, and ensemble models of these techniques. The interpolations of 11 quantitative properties and 1 qualitative property resulted in acceptable coefficients of goodness of fit due to different factors: property variability, representativeness, distribution in the study area, and property description based on environmental covariates. All the information generated has been made available for widespread use across different geographic web services. Thus IRAKA contributes to the management of information and knowledge through techniques and tools that allow users to visualize new information, use the information, and draw attention to new studies and improve databases in which the confidence level is insufficient and does not allow decision making.

Classification and geovisualization process of soil data using a web-based spatial information system

Abstract Because of the increased demand for information, the scientific community have published their results on the Internet over the last 20 years, adapting to society requirements. Due to the development of web-based spatial information soil systems, access to data on various themes and of varying quality has become substantially easier. The focus of our paper is to demonstrate a freely accessible and usable web-based soil database and soil information system (Soil Information and Soil Classifier System), which is suitable for geovisualization uploaded soil data and for determining reference soil groups (RSGs) in accordance with the World Reference Base of Soil Resources (WRB; RSG). In order to achieve this, we algorithmized the diagnostic soil classification process of the WRB, then we created decision trees to correspond input soil data to the WRB system. In order to facilitate geovisualization of the spatial data, the Keyhole Markup Language file format supported by Google API was applied.

Developing pedotransfer functions to harmonize extractable soil phosphorus content measured with different methods: A case study across the mainland of France

Phosphorus (P) is a nutrient essential to living organisms and ecosystems. Accurate information regarding extractable soil P is necessary for agricultural management and environmental quality. Direct measurements of extractable soil P at large scales are usually impeded by considerable time, labour, and economic resources required for implementation. To meet agronomic and environmental monitoring needs, multiple extraction methods have been developed worldwide to estimate the different components of soil P. In France, three extraction methods are used, namely the Dyer method for acidic soils, Joret-Hébert for calcareous soils, and Olsen for all soils. Therefore, it is difficult to compare data obtained nationwide for monitoring purposes. Consequently, it is of significant importance to develop pedotransfer functions (PTFs) to harmonise extractable soil P data obtained from different extraction methods with the assistance of other easily available predictors from soil information systems. In this study, we used an extensive dataset from the French soil-monitoring programme for the calibration and evaluation of PTFs. We implemented the partial least squares regression to relate extractable P measured by the Dyer or Joret-Hébert method to extractable P determined by the Olsen method considering 14 soil properties (total P2O5, pH, cation exchange capacity (CEC), CaCO3, soil texture (clay, silt and sand contents), total organic carbon, and exchangeable Fe, Al, CaO, Mn, MgO, and K2O). We constructed patrimonial models by selecting the most important predictors. According to the results of 10 iterations cross-validation, the average R2, root mean-square error (RMSE), and mean error (ME) of the PTF of calcareous soils were 0.66, 25.81, and −0.11 mg kg−1, whereas those of acidic soils were 0.70, 24.02, and −0.87 mg kg1, respectively. The Joret-Hébert P2O5, silt, pH, total P2O5, CEC, and K were the most important predictors for estimating Olsen P2O5 in calcareous soils, whereas Dyer P2O5, exchangeable Al, K, and pH were the most important predictors for estimating Olsen P2O5 in acidic soils. We observed that the explanatory power of the soil properties was more important in calcareous than in acidic soils. As expected, the proxies of Olsen P2O5, namely, Dyer P2O5 and Joret-Hébert P2O5, were the most important variables in modelling Olsen P2O5 variations. In addition, the relationship between Olsen P2O5 and Dyer P2O5 was much stronger than that between Olsen P2O5 and Joret-Hébert P2O5. The results confirmed the feasibility of estimating extractable P in soil by PTFs that were constructed using statistical methods, such as partial least squares regression. The addition of more predictors that are related to agricultural practices and topography attributes may improve the prediction accuracy.