基于计算机图形学的土壤质地自动分类系统
收稿日期: 2006-02-01
修回日期: 2006-05-01
网络出版日期: 2006-05-25
基金资助
国家自然科学基金(40471009, 90202012)、国家重点基础研究发展计划(2005CB422006)、中国科学 院知识创新工程(KZCX3- SW- 339).
Automatic Soil Textur e Classification System Based on Computer Gr aphics
Received date: 2006-02-01
Revised date: 2006-05-01
Online published: 2006-05-25
国内外通行的国际制、美国农部制等土壤质地分类制， 均采用传统的人工查找平面正三角 坐标图方法获取质地名称， 这对大批量土样费时费力、精度难以控制。结合国外土壤质地计算机 分类方法研究的状况， 本文基于计算机图形学技术， 利用Visual Basic 平台， 设计并完成了更具实 用性、更便于国内使用的土壤质地自动分类系统( STAC) 。STAC 系统的特点是简单、方便、快速、 直观， 具有单个或批量土壤质地的自动分类、图形显示、统计、分析以及支持用户自定义分类制等 多种功能。文中着重阐述了其中的计算机图形学实现原理和关键技术。
张丽萍,张镱锂,王英安 . 基于计算机图形学的土壤质地自动分类系统[J]. 地理科学进展, 2006 , 25(3) : 86 -95 . DOI: 10.11820/dlkxjz.2006.03.011
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.
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