A strategy to fill gaps in soil survey over large spatial extents: an example from the Murray-Darling basin of Australia

We re-mapped the soils of the Murray-Darling Basin (MDB) in 1995-1998 with a minimum of new fieldwork, making the most out of existing data. We collated existing digital soil maps and used inductive spatial modelling to predict soil types from those maps combined with environmental predictor variables. Lithology, Landsat Multi Spectral Scanner (Landsat MSS), the 9-s digital elevation model (DEM) of Australia and derived terrain attributes, all gridded to 250-m pixels, were the predictor variables. Because the basin-wide datasets were very large data mining software was used for modelling. Rule induction by data mining was also used to define the spatial domain of extrapolation for the extension of soil-landscape models from existing soil maps. Procedures to estimate the uncertainty associated with the predictions and quality of information for the new soil-landforms map of the MDB are described. (C) 2002 Elsevier Science B.V. All rights reserved.

Soil Survey of Black Hawk County, Iowa, 2005

The general soil map, which is a color map, shows the survey area divided into groups of associated soils called general soil map units. This map is useful in planning the use and management of large areas. To find information about your area of interest, locate that area on the map, identify the name of the map unit in the area on the color-coded map legend, then refer to the section General Soil Map Units for a general description of the soils in your area.

Soil Survey of Clay County, Iowa, 2005

The general soil map, which is a color map, shows the survey area divided into groups of associated soils called general soil map units. This map is useful in planning the use and management of large areas. To find information about your area of interest, locate that area on the map, identify the name of the map unit in the area on the color-coded map legend, then refer to the section General Soil Map Units for a general description of the soils in your area.

Geostatistical prediction of clay percentage based on soil survey data

Selostus: Viljelymaiden savespitoisuuden alueellistaminen geostatistiikan ja pistemäisen tiedon avulla

Soil Survey of Iowa. Report no. 34, Boone County soils, 1924

This report contains a general colored soil map of Boone County and information on the county's soil physiology, drainage and fertility. It also includes information on field experiments, rotation of crops, prevention of erosion, soil types and other vital soil information in Boone County.

Bibliography of organic and forest soils, 1926 to 1934; selected from the literature by the Organic and forest soils committee of the American soil survey association;

Mimeographed.

Soil survey, Graham County, North Carolina /

"Issued August 1953" -- p. 1.

Soil survey Sarasota County, Florida /

"Issued November 1959".

Soil survey of Mellette County, South Dakota

"In cooperation with South Dakota Agricultural Experiment Station."

Soil survey of Ward County, Texas /

Prepared in cooperation with Texas Agricultural Experiment Station.

Soil survey, Cottle County, Texas

Cover title.

Soil survey of Clay County, Alabama

"In cooperation with Alabama Department of Agriculture and Industries and Alabama Agricultural Experiment Station."

Soil survey of Salt Lake area, Utah

"In cooperation with Utah Agricultural Experiment Station."

Soil survey ... Coleman County, Texas /

Includes indexes.

Soil survey of Moore county, Texas / [by Luther C. Geiger].

Prepared in cooperation with Texas Agricultural Experiment Station.