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Land evaluation for major crops in the Indo-Gangetic Plains and black soil regions using fuzzy model

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Title Land evaluation for major crops in the Indo-Gangetic Plains and black soil regions using fuzzy model
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Creator Chatterji, S., Tiwary, P., Sen, T.K., Prasad, J., Bhattacharyya, T., Sarkar, D., Pal, D.K., Mandal, D.K., Chandran, P., et al.
 
Subject Benchmark sites, fuzzy model, land evaluation, minimum datasets
 
Description Not Available
Land evaluation is carried out to assess the suitability
of land for a specific use. Land evaluation procedures
focus increasingly on the use of quantitative procedures
to enhance the qualitative interpretation of land
resource surveys. Conventional Boolean retrieval of soil survey data and logical models for assessing land suitability, treat both spatial units and attribute value ranges as exactly specifiable quantities. They ignore the
continuous nature of soil and landscape variation and uncertainties in measurement, which may result in the
failure to correctly classify sites that just fail to match strictly defined requirements. The objective of this article
is to apply fuzzy model to land suitability evaluation for major crops in the 15 benchmark sites of the Indo-
Gangetic Plains (IGP) and 17 benchmark sites of the black soil regions (BSR). Minimum datasets of land
characteristics considered relevant to rice and wheat in the IGP and cotton and soybean in the BSR were identified to enhance pragmatic value of land evaluation. The use of fuzzy model is intuitive, robust and helpful
for land suitability evaluation and classification, especially in applications in which subtle differences in land
characteristics are of a major interest, such as development of threshold values of land characteristics.
Not Available
 
Date 2020-06-30T14:18:21Z
2020-06-30T14:18:21Z
2014-11-10
 
Type Research Paper
 
Identifier Not Available
Not Available
http://krishi.icar.gov.in/jspui/handle/123456789/37741
 
Language English
 
Relation Not Available;
 
Publisher The Current Science Association