Use of GIS and remotely sensed data to enhance digitized soil maps
Date
Authors
Major Professor
Advisor
Committee Member
Journal Title
Journal ISSN
Volume Title
Publisher
Altmetrics
Authors
Research Projects
Organizational Units
The Department of Agronomy seeks to teach the study of the farm-field, its crops, and its science and management. It originally consisted of three sub-departments to do this: Soils, Farm-Crops, and Agricultural Engineering (which became its own department in 1907). Today, the department teaches crop sciences and breeding, soil sciences, meteorology, agroecology, and biotechnology.
History
The Department of Agronomy was formed in 1902. From 1917 to 1935 it was known as the Department of Farm Crops and Soils.
Dates of Existence
1902–present
Historical Names
- Department of Farm Crops and Soils (1917–1935)
Related Units
- College of Agriculture and Life Sciences (parent college)
Journal Issue
Is Version Of
Versions
Series
Department
Abstract
Soil surveys provide information about soil properties and climate of a region. Recent soil survey maps are digitalized on digital orthophoto quadrangle (DOQ) base, mostly at a scale of 1:12000 (5.28 inches=1 mile). Current soil maps were not developed for precision farming and site-specific management. The accuracy of the soil maps for site-specific management use is of concern. Data collected from corn and soybean fields in Boone, Hardin, and Story Counties in Iowa were used in this study. This study identified areas that have differences with respect to photo pattern on remotely sensed imagery and relief within soil delineation of a geographic information system (GIS). Electrical conductivity (EM) and yield data were analyzed to determine their correlation with soils in the delineations. Soils that have the same map unit generally share EM values of similar range. Map units on refined soil delineations were compared with the EM readings and yield data. Results indicated that there is a better correlation between soils in the refined delineations and the EM data. This technique serves to enhance the accuracy of digitized soil maps.