Evaluation of different classification techniques for the detection of glass and plastic greenhouses from WorldView-2 satellite imagery

Dilek Koc-San

doi:10.1117/1.JRS.7.073553

29 May 2013 Evaluation of different classification techniques for the detection of glass and plastic greenhouses from WorldView-2 satellite imagery

Dilek Koc-San

Author Affiliations +

Journal of Applied Remote Sensing, Vol. 7, Issue 1, 073553 (May 2013). https://doi.org/10.1117/1.JRS.7.073553

Abstract

Greenhouse detection using remote sensing technologies is a challenging task for urban and rural planning, agricultural yield estimation, natural resource management, and sustainable development. The main objectives of this research are (1) to compare the supervised classification techniques including maximum likelihood (ML), random forest (RF), and support vector machines (SVM) for land cover classification with emphasis on greenhouse detection and (2) to investigate the utility of WorldView-2 satellite imagery for detecting and discriminating plastic and glass greenhouses. The study was implemented in an area selected from Muratpasa district of Antalya, Turkey, which includes both glass and plastic greenhouses extensively. Overall, the computed classification accuracies are quite high using all classification techniques. However, the most accurate classification result was obtained using SVM classifier, with overall accuracy of 93.88%. The performance of RF classification is slightly lower than SVM classification, with overall accuracy of 91.73%. On the other hand, SVM and RF classifiers significantly outperformed ML classifier, providing higher overall accuracies. When plastic greenhouse detection accuracies are considered, the obtained results revealed that all of the used classification techniques are quite successful. However, for glass greenhouse detection, the SVM and RF classifiers provided significantly higher accuracies than ML.

Citation Download Citation

Dilek Koc-San "Evaluation of different classification techniques for the detection of glass and plastic greenhouses from WorldView-2 satellite imagery," Journal of Applied Remote Sensing 7(1), 073553 (29 May 2013). https://doi.org/10.1117/1.JRS.7.073553

Published: 29 May 2013

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available