An SRTM-based Procedure to Delineate SOTER Terrain Units on 1:1 and 1:5 Million Scales


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The users and developers of the SOTER database have accumulated many suggestions for improvement of the Soil and TERrain (SOTER) Procedure Manual since the last Manual was published in 1995. Meanwhile, new technology and data sources have become available for database development. Digital soil mapping technology advances very fast and provides many new quantitative approaches for surveyors of natural resources.

The work presented here has taken advantage from the emerging digital soil mapping technology and the 90 m resolution Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM) for the development of a quantitative procedure for SOTER Terrain Unit delineation. The target scales were 1:1 and 1:5 million. The procedure is based on the SOTER Manual specifications and is meant to be compatible with the datasets formally developed using the traditional way. Meanwhile, suggested changes regarding the Terrain Units delineation have already been implemented.

The results are published in this booklet in three major sections. The first part describes the procedure in a step-by-step manner, giving all the technical details needed to run the procedure. ArcInfo® geographical information system software (GIS) was used to execute the procedure. The commands have been recorded and are given for each section. The second part gives additional details on the Potential Drainage Density Index (PDD), its use, meaning and the procedure to derive it from the SRTM data. PDD was developed and used in this context to quantify terrain dissection, which is one of the four terrain variables used for SOTER Terrain Unit characterization. The last part is a complete list of command, an ”ArcInfo® monitor file”, which can be used to replicate the entire procedure.

The main reason for developing this procedure was to provide a tested methodology and to suggest it to be a potential standard for SOTER database development. Standard, quantitative methodology is strongly needed to avoid inconsistency among the input national datasets.

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