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

Abstract

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.