The effects of DEM resolution and neighborhood size on digital soil survey

Smith, Michael P.; Zhu, A‐Xing; Burt, Janis M.; Stiles, Cynthia A.

doi:10.1016/j.geoderma.2006.07.002

Cited by 135 publications

(86 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The adjustment of a DEM to a scale enables the development of future studies of, for example, digital mapping of properties with higher quality and reliability of the resulting information. This is according to McBratney et al (2003) and Smith et al (2006), who reported a direct relationship between the accuracy of DSM studies with landscape features, and analyzed whether these are represented correctly by the DEMs.…”

Section: Resultsmentioning

confidence: 99%

“…The prediction performance of classes and soil properties can be influenced by the terrain features, the scale at which pedogenic processes occur in the landscape and whether the DEMs can represent the features in the terrain (McBratney et al, 2003;Smith et al, 2006). Moreover, the error magnitude in the DEM is not always known by users; when this information is available, it is region-specific.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Assessment of Digital Elevation Model for Digital Soil Mapping in a Watershed with Gently Undulating Topography

Moura-Bueno

Dalmolin

Caten

et al. 2016

Rev. Bras. Ciênc. Solo

View full text Add to dashboard Cite

ABSTRACT:Terrain attributes (TAs) derived from digital elevation models (DEMs) are frequently used in digital soil mapping (DSM) as auxiliary covariates in the construction of prediction models. The DEMs and information extracted from it may be limited with regard to the spatial resolution and error magnitude, and can differ in the behavior of terrain features. The objective of this study was to evaluate the quality and limitations of free DEM data and to evaluate a topographic survey (TS) underlying the choice of a more appropriate model, for use in DSMs at a scale of 1:10,000. The study was conducted in an area of 937 ha in the watershed of Lajeado Giruá, in southern Brazil. The DEMs: DEM-TS, DEM-Topographic Map (TM), DEM-ASTER, DEM-SRTM, and DEM-TOPODATA were evaluated with regard to the precision elevation by statistical tests based on field reference points, the root mean square error (RMSE), identification of the number and size of spurious depressions, and the application of the Brazilian Cartographic Accuracy Standards Law (BCASL) to define the scale of each DEM. In addition, the TA derived from each DEM was compared with the TA from DEM-TS, considered to be terrain reality. The results showed that the elevation data of DEM-TS had the best quality (RMSE = 1.93 m), followed by DEM-SRTM (RMSE = 5.95 m), DEM-Topographic Map (RMSE = 8.28 m), DEM-TOPODATA (RMSE = 9.78 m) and DEM-ASTER (RMSE = 15.57 m). The DEM-TS was well-represented at a 1:10,000 scale, while the DEM-Topographic Map and DEM-SRTM fitted 1:50,000, the DEM-TOPODATA 1:50,000 and the DEM-ASTER a 1:100,000 scale. The results of DEM-SRTM and DEM-TOPODATA were closest to terrain reality (DEM-TS) and had the lowest number of spurious depressions and RMSE values for each evaluated attribute, but were inadequate for not fitting detailed scales compatible with small areas. The techniques for the acquisition of elevation data of each DEM and mainly the flat to gently undulating topography were factors that influenced the results. For a DSM at a scale of 1:10,000 in similar areas, the most appropriate model is DEM-TS.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Assessment of Digital Elevation Model for Digital Soil Mapping in a Watershed with Gently Undulating Topography

Moura-Bueno

Dalmolin

Caten

et al. 2016

Rev. Bras. Ciênc. Solo

View full text Add to dashboard Cite

show abstract

“…The digital elevation model (DEM) was extracted from the download system of the Continuo de Elevaciones Mexicano (INEGI, 2007) and resized to each study area. The pixel size was 28.5 x 28.5 m to enhance precision for automated cartography of local soil maps using the nearest neighbor technique (Smith et al, 2006). From the DEM were used to extract slope, aspect, profile curvature, flow, analytical hillshading, convergence index, wetness index and catchment area were generated using IDRISI® and SAGA System (Cimmery, 2007).…”

Section: Maps Of Local Soil Classes and Topographic Propertiesmentioning

confidence: 99%

“…The precision of the generated maps ranges from 50 to 88 % (Lagacherie & Holmes, 1997;Dobos et al, 2001;Moran & Bui, 2002;Hengl & Rossiter, 2003;Peng et al, 2003;Qi & Zhu, 2003;Schmidt & Hewitt, 2004;Scull et al, 2005;Giasson et al, 2006;Smith et al, 2006;Qi et al, 2006;Ziadat, 2007;Figueiredo et al, 2008;Schmidt et al, 2008;Hansen et al, 2009;Ballabio, 2010;Behrens et al, 2010). These maps produced by DSM are based on scientific data by the extrapolation of soil properties, but do not take local soil knowledge into consideration.…”

Section: Introductionmentioning

confidence: 99%

Computer-assisted cartography using topographic properties: precision and accuracy of local soil maps in central Mexico

Cruz-Cárdenas

Solorio

Trejo

et al. 2011

Rev. Bras. Ciênc. Solo

View full text Add to dashboard Cite

SUMMARYMap units directly related to properties of soil-landscape are generated by local soil classes. Therefore to take into consideration the knowledge of farmers is essential to automate the procedure. The aim of this study was to map local soil classes by computer-assisted cartography (CAC), using several combinations of topographic properties produced by GIS (digital elevation model, aspect, slope, and profile curvature). A decision tree was used to find the number of topographic properties required for digital cartography of the local soil classes. The maps produced were evaluated based on the attributes of map quality defined as precision and accuracy of the CAC-based maps. The evaluation was carried out in Central Mexico using three maps of local soil classes with contrasting landscape and climatic conditions (desert, temperate, and tropical). In the three areas the precision (56 %) of the CAC maps based on elevation as topographical feature was higher than when based on slope, aspect and profile curvature. The accuracy of the maps (boundary locations) was however low (33 %), in other words, further research is required to improve this indicator.Index terms: decision tree, digital elevation model, map quality.(1) Received for publication in March 2010 and approved in January 2011.

show abstract

“…The software tools for DSM can be divided into three types: (a) general-purpose geostatistics tools such as Gstat (Pebesma, 2004), ArcGIS Geostatistical Analyst (ESRI, 2014) and GS plus (Gamma Design Software, 2007); (b) statistical packages such as R and Matlab; and (c) special soil mapping tools such as FuzME (Minasny and McBratney, 2002), SoLIM Solutions (Zhu et al, 1997;Smith et al, 2006;Zhu, 2006) and TAL (Teh, 2002;Sung, 2014). Emergent demands and trends in the DSM field pose new challenges for these software tools.…”

Section: Introductionmentioning

confidence: 99%

CyberSoLIM: A cyber platform for digital soil mapping

et al. 2016

Self Cite

View full text Add to dashboard Cite

In recent years, new demands and trends have emerged in the digital soil mapping (DSM) field: the range of applications as well as the range of users has become much diverse. Users of DSM include not only experts in soil science community but also those from relevant domains (e.g., hydrology, ecology). In addition, the rapid expansion of areas for DSM and the ever increasing spatial resolution of covariates call for an accelerated level of computation. These new trends have raised the bar for DSM software platforms. This paper presents CyberSoLIM, a prototype system to illustrate an idea of easy-of-use and high performance enabled cyber environment for DSM. CyberSoLIM is implemented to have five main features: (1) heuristic modeling, which allows digital soil mappers to construct DSM workflow easily; (2) visualized modeling with which the conceptual workflow of DSM is expressed by graphic icons; (3) workflow reuse, which increases the efficiency of DSM deployment; (4) online execution and high-performance computing, which can use the advantage of cyber infrastructure and high-performance computing; and (5) web service enabled, which provides effective and easy means to share and integrate models and algorithms. As an illustration of such environment, CyberSoLIM was used to infer the silt content in topsoil (0-20 cm) in China's Anhui Province. The case study confirms that software platform as illustrated by CyberSoLIM is easy to use and efficient in terms of mapping productivity.

show abstract

The effects of DEM resolution and neighborhood size on digital soil survey

Cited by 135 publications

References 24 publications

Assessment of Digital Elevation Model for Digital Soil Mapping in a Watershed with Gently Undulating Topography

Assessment of Digital Elevation Model for Digital Soil Mapping in a Watershed with Gently Undulating Topography

Computer-assisted cartography using topographic properties: precision and accuracy of local soil maps in central Mexico

CyberSoLIM: A cyber platform for digital soil mapping

Contact Info

Product

Resources

About