Mango Area Mapping Using Very High-Resolution Satellite Data in Major Blocks of Krishnagiri District, Tamil Nadu, India

A research study was carried out for mapping mango plantation from LISS IV data in the major blocks of Krishnagiri district, Tamil Nadu where there is substantial production of Mango. A very high-resolution satellite data namely LISS IV was acquired and processed with GIS tools. Ground truth data gathered during the survey were utilized to identify significant dB values for mango plantations, which were then used to classify the mango pixels in the study region using supervised classification technique. The Mango area in major blocks of Krishnagiri district was found to be 9077.9 ha during the year 2023. Accuracy assessment and cross validation was done using confusion matrix with the ground truth points collected. The classification resulted with an overall accuracy of 91.2 per cent with a kappa score of 0.62.

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Publication Details

Published
2025-08-12
DOI
https://doi.org/10.31234/osf.io/ufmp6_v1
Primary Topic
Agricultural Economics and Practices
Type
article
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Mango Area Mapping Using Very High-Resolution Satellite Data in Major Blocks of Krishnagiri District, Tamil Nadu, India

Research Notes
Agricultural Economics and Practices
article

Mango Area Mapping Using Very High-Resolution Satellite Data in Major Blocks of Krishnagiri District, Tamil Nadu, India

Research Notes
article en

Abstract

A research study was carried out for mapping mango plantation from LISS IV data in the major blocks of Krishnagiri district, Tamil Nadu where there is substantial production of Mango. A very high-resolution satellite data namely LISS IV was acquired and processed with GIS tools. Ground truth data gathered during the survey were utilized to identify significant dB values for mango plantations, which were then used to classify the mango pixels in the study region using supervised classification technique. The Mango area in major blocks of Krishnagiri district was found to be 9077.9 ha during the year 2023. Accuracy assessment and cross validation was done using confusion matrix with the ground truth points collected. The classification resulted with an overall accuracy of 91.2 per cent with a kappa score of 0.62.

Openalex Percentile: Top 68%
Agricultural Economics and Practices
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