DIGITAL SOIL MAPPING APPROACH BASED ON FUZZY LOGIC AND FIELD EXPERT KNOWLEDGE

被引:25
作者
de Menezes, Michele Duarte [1 ]
Godinho Silva, Sergio Henrique [2 ]
Owens, Phillip Ray [3 ]
Curi, Nilton [2 ]
机构
[1] Univ Fed Rural Rio de Janeiro, Dept Solos, BR-23890000 Seropedica, RJ, Brazil
[2] Univ Fed Lavras UFLA, Dept Ciencia Solo, Lavras, MG, Brazil
[3] Purdue Univ, Dept Agron, W Lafayette, IN 47907 USA
来源
CIENCIA E AGROTECNOLOGIA | 2013年 / 37卷 / 04期
关键词
Digital soil mapping; soil prediction; conditioned Latin hypercube sampling; knowledge miner; INFORMATION; MODEL; INFERENCE; SYSTEM;
D O I
10.1590/S1413-70542013000400001
中图分类号
S [农业科学];
学科分类号
09 ;
摘要
In Brazil, soil surveys in more detailed scale are still scarce and necessary to more adequately support the decision makers for planning soil and environment activities in small areas. Hence, this review addresses some digital soil mapping techniques that enable faster production of soil surveys, beyond fitting continuous spatial distribution of soil properties into discrete soil categories, in accordance with the inherent complexity of soil variation, increasing the accuracy of spatial information. The technique focused here is knowledge-based in expert systems, under fuzzy logic and vector of similarity. For that, a contextualization of each tool in the soil types and properties prediction is provided, as well as some options of knowledge extraction techniques. Such tools have reduced the inconsistency and costs associated with the traditional manual processes, relying on a relatively low density of soil samples. On the other hand, knowledge-based technique is not automatic, and just as the traditional soil survey, the knowledge of soil-landscape relationships is irreplaceable.
引用
收藏
页码:287 / 298
页数:12
相关论文
共 45 条
  • [1] [Anonymous], 2006, MAPPING OF THE SOIL
  • [2] [Anonymous], R LANG ENV STAT COMP
  • [3] BRUNGARD C.W., 2010, PROGR SOIL SCI, V2, P67
  • [4] Soil survey as a knowledge system
    Bui, EN
    [J]. GEODERMA, 2004, 120 (1-2) : 17 - 26
  • [5] ON THE ROLE OF EXPERT SYSTEMS AND NUMERICAL TAXONOMY IN SOIL CLASSIFICATION
    DALE, MB
    MCBRATNEY, AB
    RUSSELL, JS
    [J]. JOURNAL OF SOIL SCIENCE, 1989, 40 (02): : 223 - 234
  • [6] INTEGRATING CASE-BASED AND RULE-BASED REASONING
    DUTTA, S
    BONISSONE, PP
    [J]. INTERNATIONAL JOURNAL OF APPROXIMATE REASONING, 1993, 8 (03) : 163 - 203
  • [7] About regression-kriging: From equations to case studies
    Hengl, Tomislav
    Heuvelink, Gerard B. M.
    Rossiter, David G.
    [J]. COMPUTERS & GEOSCIENCES, 2007, 33 (10) : 1301 - 1315
  • [8] THE SOIL SURVEY AS PARADIGM-BASED SCIENCE
    HUDSON, BD
    [J]. SOIL SCIENCE SOCIETY OF AMERICA JOURNAL, 1992, 56 (03) : 836 - 841
  • [9] Jenny H., 1941, Agronomy Journal, V33, P857
  • [10] Mapping of reference area representativity using a mathematical soilscape distance
    Lagacherie, P
    Robbez-Masson, JM
    Nguyen-The, N
    Barthès, JP
    [J]. GEODERMA, 2001, 101 (3-4) : 105 - 118