Digital Soil Information Research Articles

Farmers’ Perception and Practice of Soil Fertility Management and Conservation in the Era of Digital Soil Information Systems in Southwest Nigeria

This study assessed the perception and use of digital applications for soil fertility management and conservation strategies among small-scale crop farmers in southwest Nigeria. A total of 376 farmers were randomly selected across the six southwest states. The data collected were analyzed using descriptive statistics. The majority of the farmers relied on perception and other non-scientific approaches such as the appearance of weeds and performance of crops in the previous season to assess soil fertility. Only 1.1% and 0.3% of the farmers assessed soil fertility through soil tests and digital applications, respectively. Most farmers adopted bush fallowing and the use of inorganic fertilizers to improve soil fertility. Although 4.8% of the farmers indicated that they had digital applications on their mobile phones, only 2.9% claimed to have used these. More than half (56.4%) of the farmers stated that a lack of awareness of the existence of digital applications and internet-enabled telephones were the reasons they have not been able to use digital applications. The majority of the farmers (97.3%) indicated their willingness to embrace the use of new farm decision digital applications which could provide more information, especially on soil fertility, if introduced. More extensive services focusing on older, less literate farmers and farmers who hitherto did not belong to any farmers’ association are advocated for in order to encourage the use of digital applications and soil fertility management and conservation practices.

The Role of Digital Soil Information in Assisting Precision Soil Management

Soil information is the basis for the site-specific management of soils. The study aimed to digitize soil information and classify it into soil mapping units (SMUs) using geostatistics. The study area was grouped into 12 SMUs, or management zones. The pH of the soils ranged from 7.3 in SMU2 to 8.6 in SMU5. Most SMUs exhibited low total nitrogen (TN) that could be attributed to very low soil organic carbon (SOC) in the soils. Available phosphorus (AvP) was very low in all the mapping units. The exchangeable K varied between 0.12 cmol(+) kg−1 (SMU7) and 0.95 cmol(+) kg−1 (SMU10). SMU12 was identified as marginally sodic and at a high risk of developing severe alkalinity unless possible management measures are implemented. Our findings show that a lack of soil information causes an imbalance between soil requirements and external nutrient inputs, negatively affecting crop production. Therefore, high-resolution digital soil information can assist the site-specific application of soil nutrients and amendments based on spatial variability in line with soil requirements.

Can soil fertility properties in rice fields in sub-Saharan Africa be predicted by digital soil information? A case study of AfSoilGrids250m

Soil information is essential for sustainable agricultural intensification in sub-Saharan Africa (SSA). This is the case for rice production, for which soil fertility is one of the main constraints. Through the Africa Soil Information Service (AfSIS), digital soil information at 250 m resolution (AfSoilGrids250m) is available for SSA. However, it was not validated in a wide range of rice-growing conditions. The objective of this study was to assess the accuracy of AfSoilGrids250m by comparing predicted soil fertility properties including pH H2O, clay and silt contents, total nitrogen (TN) and organic carbon (OC) with wet chemistry (WC) analysis and diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) methods. Soil samples were collected from 1002 rice fields in three production systems (irrigated lowland, rainfed lowland, and rainfed upland) in 32 sites and over five agro-ecological zones (AEZ). The coefficient of determination (R2), index of Nash-Sutcliffe efficiency (NSE), root mean square error (RMSE), and percent bias (PBias) were used to assess the predictive performance of AfSoilGrids250m. In comparison with WC and DRIFTS methods, AfSoilGrids250m underestimated the studied soil fertility properties. At the field scale, the prediction accuracy of AfSoilGrids250m for pH H2O, clay and silt contents, total nitrogen (TN), and organic carbon (OC) were poor (R2 < 0.50). The best predictive performances were obtained when data were aggregated by site-production system combination (site x PS) (n = 40). With this aggregation, AfSoilGrids250m achieved satisfactory to good prediction accuracy for TN and OC. The classification of AfSoilGrids250m had a fair to moderate agreement with both WC and DRIFTS classifications for clay content, TN, and OC. We conclude that current digital soil information (AfSoilGrids250m) is useful for assessing and classifying soil fertility properties of rice fields in different production systems at the site scale in SSA, but not as much for predicting them at the farmers' field scale.

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.

Ten challenges for the future of pedometrics

Pedometrics, the application of mathematical and statistical methods to the study of the distribution and genesis of soils, has broadened its scope over the past two decades. The primary focus of pedometricians has traditionally been on spatial and spatio-temporal soil inventories with numerical soil classification, geostatistical modelling of spatial variation and mapping. The rapid development of remote and proximal soil sensing as well as data-driven statistical modelling techniques have had a major impact on pedometrics over the past decades. During this time, a general demand for quantitative digital soil information for environmental modelling and management has compelled pedometricians to address other soil-related questions from a quantitative point of view: soil genesis and utility and quality of soil. While scientific progress is largely an autonomous process that is difficult to steer, research efforts could benefit from an agenda with pressing pedometric research topics. This paper defines and discusses ten recent or longstanding pedometrics challenges, with the attempt to identify knowledge gaps and suggest new concepts and methods to overcome them. The ten challenges were selected through a collaborative effort and may serve as a guidance for future pedometrics research and to foster collaboration among soil scientists. The challenges discussed in this paper are also indicators of the current understanding and state of knowledge from which progress can be measured in the future.

Validating digital soil maps using soil taxonomic distance: A case study of Ireland

Recently, there has been a marked increase across the world in the demand for digital soil information, in which digital soil mapping research plays a key role. Methods to validate these digital soil maps are needed. Soil maps, and in particular soil taxonomic maps contain embedded information that represents an understanding of the functioning of the soil within its landscape and the contributing soil forming factors. These cannot be easily validated by a straight point-to-polygon comparison. Furthermore, the uncertainty associated with a misclassification is not binary, but rather a more complex measure that accounts for the degree of divergence between the point observation and map unit that takes into account these underlying relationships between soils, landscape and function. Here we present a map validation approach based on the soil taxonomic divergence and compare this to the outcome from validation based on a straight binary presence/absence evaluation of the map units. We do so for the newly generated soils map of Ireland at a scale of 1:250,000. We find that the overall accuracy calculated through the presence absence method was 69% accurate, whereas the minimum taxonomic distance concept, has an overall accuracy of 90.1%. In particular, soil map units with large spatial coverage tended to be assessed as being very uncertain using the presence/absence method, the confidence around these map units was significantly improved using the minimum taxonomic distance approach. Where large differences were observed between field observations and mapped soil units, we found the taxonomic distance measure a more informative diagnostic as why these differences were observed.

Development of wide-area digital soil information and its application(JSSPN Progress Awards)

Development of wide-area digital soil information and its application(JSSPN Progress Awards)

Spatial Scaling for Digital Soil Mapping

We describe in this paper, a broad overview of spatial scale concepts and scaling procedures that are specifically relevant for digital soil mapping (DSM). Despite the recent growth and operational status of DSM, one existing and foreseeably growing issue for users of digital soil information is the inequality of spatial scales between what is required and what is actually available to adequately address soil‐related questions posed from within and from outside the soil science community. In the absence of conducting new soil survey or not being able to acquire the original legacy soil information (soil point data) as a means of creating user‐specified soil information products, spatial scaling provides a useful solution. Spatial scaling for DSM involves changes in map extent, grid‐cell resolution, and prediction support. We review in this paper the different forms of spatial scaling, which are described in terms of changes to grid spacing and prediction support. Fine‐gridding and coarse‐gridding are operations where the grid spacing changes but support remains unchanged. Deconvolution and convolution are operations where the support always changes which may or may not involve changing the grid spacing. While disseveration and conflation operations occur when the support and grid size are equal and both are then changed equally and simultaneously. Some possible and existing pedometric methods are described for implementation of each scaling process, as is an extended example for performing convolution where the support changes yet the resolution remains the same.

Soil maps of The Netherlands

The Netherlands has a long history of soil research. Over the past 150years, seven national soil maps have been produced at scales ranging from 1:50,000 to 1:1,000,000. The maps were based on different conceptual models which reflected advances in soil science as well as societal demands. There are four phases in the development of soil mapping in The Netherlands. The first three are: (i) the geological phase (1837–1937), (ii) the physiographic phase (1937–1962) and (iii) the morphometric phase (1962–1995). The earliest soil maps, made in the mid-1800s, were largely based on surface geology. In 1950 the first national soil map was published based on physiographic soil mapping. From the 1960s onwards, mapping followed a pedogenetic–morphometric approach and these maps have been widely used in land use planning, hydrologic studies, re-allotments, and agricultural land evaluations. An increase in environmental awareness with the need to assess environmental impacts and developments in information technology induced the digital soil information phase (1995–present). New technologies have improved the collection, storage, analysis and presentation of soil geographic information. It is concluded that initial soil mapping in The Netherlands had a strong agricultural focus but that the current maps are used in a wide range of applications.

European digital archive on soil maps (EuDASM): preserving important soil data for public free access

Historical soil survey paper maps are valuable resources that underpin strategies to support soil protection and promote sustainable land use practices, especially in developing countries where digital soil information is often missing. However, many of the soil maps, in particular those for developing countries, are held in traditional archives that are not easily accessible to potential users. Additionally, many of these documents are over 50 years old and are beginning to deteriorate. Realising the need to conserve this information, the Joint Research Centre (JRC) and the ISRIC-World Soil Information foundation have created the European Digital Archive of Soil Maps (EuDASM), through which all archived paper maps of ISRIC has been made accessible to the public through the Internet. The immediate objective is to transfer paper-based soil maps into a digital format with the maximum possible resolution and to ensure their preservation and easy disclosure. More than 6,000 maps from 135 countries have been captured and are freely available to users through a user-friendly web-based interface. Initial feedback has been very positive, especially from users in Africa, South America and Asia to whom archived soil maps were made available to local users, often for the first time. Link: http://eusoils.jrc.ec.europa.eu/library/maps/country_maps/list_countries.cfm

Taxonomic distance measurements applied for soil correlation

The development of the recent European and global initiatives resulted in an increasing demand for harmonized digital soil information. One of the major limitations of harmonization is the great variation of field and analytical methods and classification systems. Since 1998, the World Reference Base for Soil Resources (WRB) is the global correlation scheme for soil classification and international communication. The one to one correlation of units, however, is difficult, if not impossible. Another problem is that the correct correlation of national units to WRB units might have spatial consequences. If the original map units need to be maintained, it is important to express the extent to which certain national units match with the WRB units. Taxonomic distance measurements were applied successfully to express numerically the correlation between the brown forest soil types (BFS) of the Hungarian Soil Classification System (HSCS) and WRB Reference Soil Groups (RSGs).