Digital soil mapping of the Itaqueri-SP creek basin using cluster analysis and geographic information systems

• Grant number: 11/19328-0
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Effective date (Start): January 01, 2012
• Effective date (End): December 31, 2012
• Field of knowledge: Physical Sciences and Mathematics - Geosciences - Physical Geography
• Principal Investigator: Archimedes Perez Filho
• Grantee: Juliana Kumori
• Host Institution: Instituto de Geociências (IG). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil

Abstract

Traditionally, the soil resources survey in the country has shown limitations regarding the accuracy, cost, and efficiency, due to large demands on skilled human resources and vast territorial dimensions. However, the demand for soil maps for land use planning and environmental analysis is strong, thus making the issue a hurdle to be overcome. In this way, the Digital Soil Mapping procedures (DSM) along with the development of the Geographic Information System have gained highlight as a precise, effective, and less costly procedure. Pedometric techniques as well as ancillary cartographic materials have enabled the soil classes mapping at various scales. Thus, this study aims to produce a soil map at 1:50.000 scale by digital mapping techniques of the Itaqueri creek basin, located in the Itirapina/SP county. It will be created a geodatabase by digitizing cartographic data, formulating the digital elevation model, and will be derived geomorphometric parameters (slope and curvature of slope) and lithology. The cluster analysis approach will be used for the determination of soil mapping units. The error matrix and Kappa index will be employed to analyze the results. However, we emphasize that due to the recent development of DSM, the choice of geomorphometric variables and classification method is a preliminary and experimental approach. In case of insufficiently accurate or precise results, further different methodological approaches and other variables can be included in the model.(AU)