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Reseach Article

Land cover Classification and Crop Estimation using Remote Sensing Techniques

by Najam Aziz, Nasru Minallah, Ahmad Junaid
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 155 - Number 2
Year of Publication: 2016
Authors: Najam Aziz, Nasru Minallah, Ahmad Junaid

Najam Aziz, Nasru Minallah, Ahmad Junaid . Land cover Classification and Crop Estimation using Remote Sensing Techniques. International Journal of Computer Applications. 155, 2 ( Dec 2016), 1-6. DOI=10.5120/ijca2016912259

@article{ 10.5120/ijca2016912259,
author = { Najam Aziz, Nasru Minallah, Ahmad Junaid },
title = { Land cover Classification and Crop Estimation using Remote Sensing Techniques },
journal = { International Journal of Computer Applications },
issue_date = { Dec 2016 },
volume = { 155 },
number = { 2 },
month = { Dec },
year = { 2016 },
issn = { 0975-8887 },
pages = { 1-6 },
numpages = {9},
url = { },
doi = { 10.5120/ijca2016912259 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Journal Article
%1 2024-02-07T00:00:10.198219+05:30
%A Najam Aziz
%A Nasru Minallah
%A Ahmad Junaid
%T Land cover Classification and Crop Estimation using Remote Sensing Techniques
%J International Journal of Computer Applications
%@ 0975-8887
%V 155
%N 2
%P 1-6
%D 2016
%I Foundation of Computer Science (FCS), NY, USA

Due to the rapid growth of population the food need also increases which is the center of focus for various researchers and governments. For this purpose crop information system has been made, the aim of crop information system is to monitor the crop health and estimate the needs for the next four to five years. Geo graphic information system plays an important role in crop estimation and identification. GIS uses remote sensing technique to identify various crops and their yield. In this paper novel approaches are used for the identification and estimation of tobacco. SPOT 5 imagery having resolution of 2.5m is used for the estimation and identification of tobacco. For post processing, statistics like kappa coefficients and Receiver operating curves are utilized. This study mainly focuses on the Mardan region in KPK Pakistan. Classification is done for four categories, these categories are then classified using state of the art machine learning classifiers and the accuracy of these various classifiers has been compared.

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Index Terms

Computer Science
Information Sciences


Remote sensing Receiver operating curves kappa coefficient SVM Maximum likelihood Minimum distance Mahalanobis distance.