The Study of Soil Fertility Spatial Variation Feature Based on GIS and Data Mining

Abstract : Studying on the spatial distribution and variation characteristics of soil fertility by Application of geographical information systems (GIS) and data mining(DM), with the quantitative analysis of spatial variability of soil fertility in complexity, and provide the effective way for simulations which can be closer to the farmland soil fertility variability. At the same time, interpolation method based on the spatial variability of soil can provide different accuracy data for soil database, researching of space fuzzy clustering based on precise fertilization regional fertility space can provide a decision-making basis for spatial variability of soil fertility evaluation, a precise prediction and evaluation of precision agriculture are the indispensable basic information and theoretical basis of the development and implementation of precision agriculture.In this paper, the authors take the national 863 project which in the Yushu City of Jilin province as the survey region. And then get the best prediction method and discuss the different effect of the soil nutrient under spatial interpolation prediction model on the analysis of the soil nutrient space mutation characteristics of the foundation by the GIS technology and the geography statistical method. Finally, we analysis the soil fertility status by using the weighted space fuzzy clustering as well as the soil nutrient of space mutation distribution, so as to provide basis for the study on area space mutation characteristics of cultivated land soil fertility which has an important theoretical and practical effect on the precise fertilization of crop and soil fertility evaluation.
Type de document :
Communication dans un congrès
Daoliang Li; Yingyi Chen. 6th Computer and Computing Technologies in Agriculture (CCTA), Oct 2012, Zhangjiajie, China. Springer, IFIP Advances in Information and Communication Technology, AICT-393 (Part II), pp.211-220, 2013, Computer and Computing Technologies in Agriculture VI. 〈10.1007/978-3-642-36137-1_26〉
Liste complète des métadonnées

Littérature citée [6 références]  Voir  Masquer  Télécharger

https://hal.inria.fr/hal-01348234
Contributeur : Hal Ifip <>
Soumis le : vendredi 22 juillet 2016 - 15:52:15
Dernière modification le : vendredi 22 juillet 2016 - 16:04:40
Document(s) archivé(s) le : dimanche 23 octobre 2016 - 13:10:16

Fichier

978-3-642-36137-1_26_Chapter.p...
Fichiers produits par l'(les) auteur(s)

Licence


Distributed under a Creative Commons Paternité 4.0 International License

Identifiants

Citation

Chunan Li, Guifen Chen, Guangwei Zeng, Jiao Ye. The Study of Soil Fertility Spatial Variation Feature Based on GIS and Data Mining. Daoliang Li; Yingyi Chen. 6th Computer and Computing Technologies in Agriculture (CCTA), Oct 2012, Zhangjiajie, China. Springer, IFIP Advances in Information and Communication Technology, AICT-393 (Part II), pp.211-220, 2013, Computer and Computing Technologies in Agriculture VI. 〈10.1007/978-3-642-36137-1_26〉. 〈hal-01348234〉

Partager

Métriques

Consultations de la notice

107

Téléchargements de fichiers

141