Estimation of mango growing areas using remote sensing
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DOI:
https://doi.org/10.5958/0974-0112.2017.000040.8Keywords:
Mango, acreage estimation, remote sensing, decision tree.Issue
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Copyright (c) 2017 Indian J. Hortic.

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Abstract
An attempt was made to estimate acreage and to depict the spatial distribution of mango growing areas using linear imaging self-scanning image of remote sensing data for Saharanpur district of Uttar Pradesh. The image was processed using ENVI software. Unsupervised, supervised and decision tree classification were used for the acreage estimation. The study has clearly demonstrated the usefulness of remote sensing image for identifying and acreage estimation of mango orchards. The results also indicated that mango acreage estimation was more accurate in decision tree approach (92.92%) as compared to other two methods (81.73 and 80.43%, respectively). The overall result revealed that the finer resolution the time series data, better the accuracy of area estimation. The above study proves that the remote sensing data could be effectively used for other perennial horticultural crops with finer resolution time series data.
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