Showing papers on "Digital soil mapping published in 1972"

Computer-based soil mapping of small areas from sample data I Multivariate classification and ordination

Abstract: A 1400 M X 600 M RECTANGULAR AREA OF NORTH BERKSHIRE HAD BEEN SAMPLED AT THE INTERSECTIONS OF A 100 M SQUARE GRID, AND SEVENTEEN PROPERTIES OF THE SOIL PROFILE MEASURED. THE EIGHTY-FOUR SAMPLING SITES WERE CLASSIFIED NUMERICALLY TO PRODUCE A HIERARCHY, AND THE CLASSES OF THE UPPER PART OF THE HIERARCHY MAPPED. THE MAPPED CLASSES BECAME INCREASINGLY FRAGMENTED AS THE NUMBER OF CLASSES INCREASED. AT THE 3-CLASS LEVEL, THE CLASSES CORRESPONDED TO CHARACTER SPACE CLUSTERS AND CLASS FRAGMENTATION WAS NOT SERIOUS. PRINCIPAL-COMPONENT ANALYSIS OF THE SAMPLE DATA YIELDED A FIRST COMPONENT THAT ACCOUNTED FOR 40 PERCENT OF THE TOTAL VARIANCE AND WELL REPRESENTED THE FIELD CHARACTERS USED FOR SOIL CLASSIFICATION. AN ISARITHM MAP OF THE FIRST COMPONENT SHOWS HOW THE SOIL CHANGES GRADUALLY OVER THE LANDSCAPE IN GOOD AGREEMENT WITH A SOIL-SERIES MAP MADE BY FREE SURVEY. /AUTHOR/

Computer-based soil mapping of small areas from sample data II Classification smoothing

Abstract: TWO RECTANGULAR AREAS 1400 M X 600 M IN SOUTH CENTRAL ENGLAND HAD BEEN SAMPLED AT THE INTERSECTIONS OF 100 M SQUARE GRIDS, AND SOME 20 SOIL PROPERTIES MEASURED. HIERARCHICAL NUMERICAL CLASSIFICATIONS GAVE CLASSES WHICH, WHEN MAPPED, WERE VERY FRAGMENTED. FRAGMENTATION WAS LESS WHEN THE GEOGRAPHIC LOCATIONS OF THE SAMPLING SITES WERE INCLUDED IN THE CLASSIFICATION. LINEAR FUNCTIONS OF LOCATION AND CONTIGUITY CONSTRAINTS PRODUCE MAPS THAT ARE SMOOTHER, I.E. LESS FRAGMENTED, BUT ARE UNSATISFACTORY IN OTHER ASPECTS. INVERSE SQUARE AND EXPONENTIAL FUNCTIONS OF LOCATION PRODUCE SMOOTHER MAPS THAT ARE QUITE AS GOOD AS THOSE PRODUCED WITHOUT TAKING LOCATION INTO ACCOUNT, IN THAT THE SOIL IS NO MORE VARIABLE WITHIN THE CLASSES MAPPED. /AUTHOR/

Automatic retrieval and analysis of soil characterization data

Abstract: Soil site, environmental, morphological and laboratory characterization data for 186 Montana soils (pedons) were encoded using the "Proposed Coding System for the Pedon Data Record for the National Cooperative Soil Survey" and have been stored on magnetic tape at Montana State University. Data for 1466 horizons were stored in the Pedon Data (PD) Record and included observations from the following soil orders; Mollisols, Aridisols, Alfisols, Entisols, and Inceptisols. Mollisols and Aridisols were the dominant orders in the sample. Encoding soil data on specially prepared mark sense forms required 40 percent less time and was more economical than recording the codes on 80-column data forms and key punching. Cost and preparation of mark sense forms were about the same as the cost of key punching the data with student help, Total required time for processing an 8-horizon pedon with average amounts of characterization data was about three hours. Computer written pedon descriptions and laboratory tables were produced from encoded data in the PD record for about $0.25 and $0.30, respectively. Multiple copies of the descriptions and tables were copied from labeled files for less than $0.10 each. Developing new and smaller working files from the Pedon Data (PD) Record with fixed formats and selected characteristics were more economical for statistical analysis than direct retrieval from the lengthy PD record. The standard deviations of the means calculated from Laboratory data for percent sand, silt, clay, 1/3 bar water retention and 15 bar water retention were higher than expected for some of the field named textural classes. The mean percent sand, silt, and clay for nearly all the field named textural classes fit within the correct partition of the textural triangle. A majority of the samples were from medium and fine textural classes. An inventory of available data and correlations between morphological data (includes site and environmental factors) and laboratory characteristics were used as criteria to select variables for statistical analysis. Percent clay (determined in the laboratory) and organic carbon were the best of 58 parameters tested to predict percent soil water at 15 bar tension. The following model was developed using 930 samples: [Percent 15 bar water = 2.1 + 0.29 (percent clay) + O.58 (organic matter)]. Percent water held at 15 bar tension can be predicted using percent clay and moist color value. The following model was developed using 874 samples: [Percent 15 bar water = 7.1 + 0.28 (percent clay) 0.95 (moist color value)]. The parameters in six models were evaluated and summarized for incorporation into three proposed forms for calculating estimated soil water available to plants. AUTOMATIC RETRIEVAL AND ANALYSIS OF SOIL CHARACTERIZATION DATA by GORDON LEE DECKER a thesis submitted to the'Graduate Faculty in partial fulfillment of the.requirements for the degree of DOCTOR OF PHILOSOPHY in Crop and Soil Science.

Grid sampling and air photography in upland soil mapping

Abstract: A DESCRIPTION OF SOIL PROFILES AT POINTS ON A REGULAR GRID (83 POINTS AT C. 300 M SPACING IN C. 17 KM SQUARE), COMBINED WITH AIR PHOTOGRAPH INTERPRETATION, HAS BEEN TESTED AS A SOIL SURVEY TECHNIQUE AT THE 1:10000 SCALE IN THE RHINOG MOUNTAINS OF NORTH WALES. VERY FEW BOUNDARIES FOR DEFINABLE SOIL UNITS COULD BE CONFIDENTLY DRAWN FROM THESE DATA. THE GRID METHOD, IN SPITE OF MANY APPARENT ADVANTAGES, DID NOT GIVE RESULTS WHICH COULD PRODUCE A SOIL MAP OR BE EXTRAPOLATED TO WIDER AREAS OF SIMILAR GEOLOGY AND PHYSIOGRAPHY. SUBSEQUENTLY, A FREE SURVEY WAS NECESSARY TO ENABLE PRODUCTION OF A SOIL MAP. DISCUSSION, RESULTS AND ILLUSTRATIONS OF THE GRID AND FREE SURVEY METHODS REFER TO A SAMPLE AREA CONTAINING 36 GRID POINTS. ASSESSMENT OF SIGNIFICANT SOILS OBTAINED BY THE TWO METHODS ARE COMPARED. /AUTHOR/

Remote sensing of soils, land forms, and land use in the northern great plains in preparation for ERTS applications

Abstract: Research to determine the optimum time or season for obtaining imagery to identify and map soil limitations was conducted in the proposed Oahe irrigation project area in South Dakota. The optimum time for securing photographs or imagery is when the soil surface patterns are most apparent. For cultivated areas similar to the study area, May is the optimum time. The fields are cultivated or the planted crop has not yet masked soil surface features. Soil limitations in 59 percent of the field of the flight line could be mapped using the above criteria. The remaining fields cannot be mapped because the vegetation or growing crops do not express features related to soil differences. This suggests that imagery from more than one year is necessary to map completely the soil limitations of Oahe area by remote sensing techniques. Imagery from the other times studied is not suitable for identifying and mapping soil limitations of Oahe area by remote sensing techniques. Imagery from the other times studied is not suitable for identifying and mapping soil limitations because the vegetative cover masked the soil surface and does not reflect soil differences.