Quality Assurance of Soil-Landscape Information Modeling (SoLIM) to verify results and accuracy of inference information

GLNF CESU Project #: UWM-NRCS-03
TA# 68-3A75-2-89-9
Partners:
University of Wisconsin, Madison and USDA-Natural Resources Conservation Service
Project Contact: A-Xing Zhu & James E. Burt
Agency Contact: Jonathan Hempel (Jon.Hempel@wv.usda.gov)
Project Funding: $28,657
Project Dates:

09/28/2005 - 09/30/2008

 

Project Abstract:

SoLIM (Soil Landscape Inference Model) is a new technology for soil mapping based on recent developments ion geographic information science (GISc), artificial intelligence (AI), and information representation theory. SoLIM was designed to overcome the limitations of existing soil survey methods and to improve the efficiency and accuracy of the soil survey. The objective of this project is to develop a process to verify accuracy of the existing data from the Dane County, WI SoLIM project. Data produced by SoLIM process is 100 X the detail of the traditional soil survey. Ensuring the quality of this soil survey information will enable others to become confident in this new and emerging approach to develop highly detailed soil survey information.

Project Products: