Open legacy soil survey data in Brazil: geospatial data quality and how to improve it

Abstract

Spatial soil data applications require sound geospatial data including coordinates and a coordinate reference system. However, when it comes to legacy soil data we frequently find them to be missing or incorrect. This paper assesses the quality of the geospatial data of legacy soil observations in Brazil, and evaluates geospatial data sources (survey reports, maps, spatial data infrastructures, web mapping services) and expert knowledge as a means to fix inconsistencies. The analyses included several consistency checks performed on 6,195 observations from the Brazilian Soil Information System. The positional accuracy of geospatial data sources was estimated so as to obtain an indication of the quality for fixing inconsistencies. The coordinates of 20 soil observations, estimated using the web mapping service, were validated with the true coordinates measured in the field. Overall, inconsistencies of different types and magnitudes were found in half of the observations, causing mild to severe misplacements. The involuntary substitution of symbols and numeric characters with similar appearance when recording geospatial data was the most common typing mistake. Among the geospatial data sources, the web mapping service was the most useful, due to operational advantages and lower positional error (~6 m). However, the quality of the description of the observation location controls the accuracy of estimated coordinates. Thus, the error of coordinates estimated using the web mapping service ranged between 30 and 1000 m. This is equivalent to coordinates measured from arc-seconds to arc-minutes, respectively. Under this scenario, the feedback from soil survey experts is crucial to improving the quality of geospatial data.

Mapping at 30 m Resolution of Soil Attributes at Multiple Depths in Midwest Brazil

“…Natural vegetation and pasturelands are still under-represented. Indeed, there are many soil observations still unavailable in the region that could become open access and be used to increase spatial coverage and improve predictions [29]. Considering our large study area, we performed relatively low-cost mapping because of the use of legacy soil observations and comparatively fewer new soil observations, free RS-based covariates and the open-source R software and Google Earth Engine cloud-based platform, for data processing and visualization.…”

Soil Color and Mineralogy Mapping Using Proximal and Remote Sensing in Midwest Brazil

“…In this study, the uncertainty was not examined as maps because this technique was not implemented at the current development stage of GEE [64]. Therefore, to verify the correspondence of the spatial patterns of our predictions, we performed Pearson's correlation between our maps (at the three depth intervals) with legacy soil observations acquired from a national dataset [33], and also with weathering degree and hue, both inferred according to the World Reference Base for Soil Resources -WRB [14] from a 1:1,000,000-scale legacy soil class map that covered the study area [45]. The flow diagram of the proposed method is shown in Figure 2.…”

“…Nevertheless, the spatial patterns of soil color and mineralogy under current conditions remains not mapped for most Brazilian soils, both qualitatively and quantitatively. The main reason for that might be that in Brazilian repositories [33] there is a lack of mineralogical data, possibly due to the fact that traditional methods, such as X-ray diffraction (XRD) are time consuming and resource intensive [29]. Besides that, XRD measurements are qualitative and not conducive to quantitative analyses [34].…”

“…Besides that, XRD measurements are qualitative and not conducive to quantitative analyses [34]. Soil color in national datasets [33] also lacks or does not contain spatial referencing or was visually approximated, which has been proven to be less consistent than modern colorimeter measurements [19].…”

How is the learning process of digital soil mapping in a diverse group of land use planners?

“…Data from the semi-detailed survey of soils of the municipality of Londrina are available at the Free Brazilian Repository for Open Soil Data (www.ufsm.br/febr) under the identification code ctb0022. The Free Brazilian Repository for Open Soil Data is a repository that stores accessible soil data for various applications (Samuel-Rosa et al, 2020).…”