Harmonising legacy soil data for digital soil mapping in Indonesia

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 80 0,0 0 0. Currently, data for 117, 0 0 0 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 topdown 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.

Environmental Modelling & Software, 2002

The multilingual soil profile database (named SDBm Plus) is user-friendly software designed to store and retrieve in an efficient and systematic way the large amounts of geo-referenced soil attribute data collected in soil surveys and laboratories. The database has the following main characteristics: (i) running on Windows platforms; (ii) 'assist menus' facilitating data entry; (iii) automatic translation from English to Spanish, French and German; (iv) metadata facility to describe the methods used in laboratory analysis;

Agrokémia és Talajtan, 2010

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Spatial soil databases can help model complex phenomena in which soils are decisive, for example, evaluating agricultural potential or estimating carbon storage capacity. The Soil Information System for Latin America and the Caribbean, SISLAC, is a regional initiative promoted by the FAO's South American Soil Partnership to contribute to the sustainable management of soil. SISLAC includes data coming from 49,084 soil profiles distributed unevenly across the continent, making it the region's largest soil database. However, some problems hinder its usages, such as the quality of the data and its high dimensionality. The objective of this research is twofold. First, to evaluate the quality of SISLAC and its data values and generate a new, improved version that meets the minimum quality requirements to be used by different interests or practical applications. Second, to demonstrate the potential of improved soil profile databases to generate more accurate information on soil properties, by conducting a case study to estimate the spatial variability of the percentage of soil organic carbon using 192 profiles in a 1473 km 2 region located in the department of Valle del Cauca, Colombia. The findings show that 15 percent of the existing soil profiles had an inaccurate description of the diagnostic horizons. Further correction of an 4.5 additional percent of existing inconsistencies improved overall data quality. The improved database consists of 41,691 profiles and is available for public use at (Díaz-Guadarrama, S. & Guevara, M., 2022). The updated profiles were segmented using algorithms for quantitative pedology to estimate the spatial variability. We generated segments one centimeter thick along with each soil profile data, then the values of these segments were adjusted using a spline-type function to enhance vertical continuity and reliability. Vertical variability was estimated up to 150 cm in-depth, while ordinary kriging predicts horizontal variability at three depth intervals, 0 to 5, 5 to 15, and 15 to 30 cm, at 250 m-spatial resolution, following the standards of the GlobalSoilMap project. Finally, the leave-one-out crossvalidation provides information for evaluating the kriging model performance, obtaining values for the RMSE index between 1.77% and 1.79% and the R 2 index greater than 0.5. The results show the usability of SISLAC database to generate spatial information on soil properties and suggest further efforts to collect a more significant amount of data to guide sustainable soil management. Table 1, Initial profiles and their layers by country. The countries are ordered by number of profiles, those with less than 100 profiles were grouped together. NA: Not Applicable Country Profiles

Journal of environment and earth science, 2015

The extraction of information from surveyed and classified soil maps by desired end-users has increased in recent times due to the high cost involved in the classification and mapping out of such soils by the individual users, and is also a time consuming process. In some instances, the end users do not even understand the methods that were used in producing the maps, the errors associated with it and the potential limitations of usage. Knowledge over the years has shown that estimates contained in some soil maps are not perfect because they are typically based on limited data and limited information. To acknowledge that soil maps are not free of errors, the uncertainty in the estimates may be represented with error bounds that characterize the accuracy of the map. In recent times more advanced methods have been introduced with high precision of accuracy, including the use of artificial neural networks, remote sensing and photogrammetric procedures, combined with geographic informa...

Digital Soil Mapping, 2010

It is still classical soil mapping for routine soil survey and classification activities in the Philippines. Nevertheless, the Bureau of Soils and Water Management (BSWM) has the necessary equipment for Geographic Information System (GIS) and Remote Sensing (RS) as well trained manpower complement to conduct digital soil mapping presently done at research and project level basis. Our current digital soil mapping research is focused on the mapping of land attributes of the watersheds of Cabulig, Misamis Oriental and of Inabanga, Bohol through a research grant from the Australian Centre for International Agricultural Research (ACIAR). With three months of field soil survey work to commence this February 2012, the research will develop methods of rapid soil measurement that allow quick and inexpensive (though less precise) measurements/ estimates of important soil attributes. This recognizes that, in the face of soil variability, the appropriate strategy is to make lots of inexpensive measurements rather than a few, precise and more expensive ones. Rapid soil measurement methods include the use of proximal sensors, such as visible/near infra-red and/or mid infra-red spectrometers, and pedotransfer functions to estimate soil attributes. These methods still require the use of conventional laboratory and field measurements on a proportion of sample locations, to provide local calibration. We also have FAO-funded land degradation assessment to harmonize our digital data holdings with global land degradation data. Furthermore, we are in the process of acquiring satellite imageries to cover the whole country and once processed, re-issue all our maps based on orthoimages. While digital soil mapping may still be a long way to go for BSWM, nevertheless, this seems the only way to go as we are faced with hiring moratorium which when once lifted, we are faced only with computer literates but classical soil survey illiterates in the job market. We thank the organizers of this East Asia Node Conference for enabling us to participate in the partnership.