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Soil Type Identification Using Remotely Sensed Data for Agricultural Purpose

Jiji, G. Wiselin / Nadar, Pallavi

Abstract Soil assessment plays important role in making decisions for Agriculture. In this paper, an approach by integrating the image processing and pattern recognition techniques to find the type of soil has been presented. The soil from the area of interest is selected and soil indices are extracted as features. Indexing technique is used for faster retrieval. The efficiency of the proposed system is proved using sensitivity, specificity, precision and recall. Our empirical evaluation has a superior retrieval performance over the performance of other works. This work is of great use to the farmers, who need to identify their field’s soil type.

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Soil Type Identification Using Remotely Sensed Data for Agricultural Purpose

Jiji, G. Wiselin / Nadar, Pallavi

Abstract Soil assessment plays important role in making decisions for Agriculture. In this paper, an approach by integrating the image processing and pattern recognition techniques to find the type of soil has been presented. The soil from the area of interest is selected and soil indices are extracted as features. Indexing technique is used for faster retrieval. The efficiency of the proposed system is proved using sensitivity, specificity, precision and recall. Our empirical evaluation has a superior retrieval performance over the performance of other works. This work is of great use to the farmers, who need to identify their field’s soil type.

Soil Type Identification Using Remotely Sensed Data for Agricultural Purpose

Jiji, G. Wiselin / Nadar, Pallavi

Abstract Soil assessment plays important role in making decisions for Agriculture. In this paper, an approach by integrating the image processing and pattern recognition techniques to find the type of soil has been presented. The soil from the area of interest is selected and soil indices are extracted as features. Indexing technique is used for faster retrieval. The efficiency of the proposed system is proved using sensitivity, specificity, precision and recall. Our empirical evaluation has a superior retrieval performance over the performance of other works. This work is of great use to the farmers, who need to identify their field’s soil type.

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Title:

Soil Type Identification Using Remotely Sensed Data for Agricultural Purpose

Contributors:

Jiji, G. Wiselin (author) / Nadar, Pallavi (author)

Published in:

Journal of The Institution of Engineers (India): Series B ; 97 ; 405-411

Publication date:

2015-05-23

Size:

7 pages

ISSN:

2250-2114 , 2250-2106

DOI:

https://doi.org/10.1007/s40031-015-0202-8

Type of media:

Article (Journal)

Type of material:

Electronic Resource

Language:

English

Keywords:

SVM , Map server , WSDL , Classification Engineering , Communications Engineering, Networks

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