PROGRESS IN GEOGRAPHY ›› 2006, Vol. 25 ›› Issue (3): 86-95.doi: 10.11820/dlkxjz.2006.03.011

• Original Articles • Previous Articles     Next Articles

Automatic Soil Textur e Classification System Based on Computer Gr aphics

ZHANG Liping1,2, ZHANG Yili1, WANG Yingan1,2   

  1. 1. Institute of Geographical Sciences and Natural Resources Research, CAS, Beijing 100101, China|
    2. Graduate School of the Chinese Academy Sciences, Beijing 100039, China
  • Received:2006-02-01 Revised:2006-05-01 Online:2006-05-25 Published:2006-05-25


International and USDA's soil texture classification systems are prevalent in the world, which adopt additional manual inquiring of triangle coordinate diagram to realize the naming of soil texture. This takes a lot of time and energy and lacks precision control. To apply computer program can perform the same task easily, conveniently and fast. According to the oversea research status quo in soil texture automatic classification based on computer graphics, using Visual Basic (VB) a as platform, soil texture automatic classification system (STAC) is built the better practicability in China. The theories of STAC are mainly based on the fact that each point in the textural triangle represents a unique combination of clay, sand and silt content. For a given textural class, all combinations of clay, sand and silt content are bound by a polygon. Therefore, finding the textural class is equivalent to finding the polygon where the particular combination of clay, sand and silt content is located. The algorithm of the program is point - in - polygon algorithm, which can determine whether a point of known coordinates (clay percentage and sand percentage) lies inside a polygon in the textural triangle. STAC is simple, convenient, fast and explicit. STAC can be used in a Windows 95 console program and above without requiring installation. It realizes texture automatic naming of single as well as batch soil data and provides graphical display, statistics and analysis function, and user - defined classification, and can classify several thousands of soil samples in about a second.

CLC Number: 

  • S159.9