Extraction of Complex Plantations from VHR Imagery using OBIA Techniques

Main Article Content

C. Suwanprasit
J. Strobl
Z. Adamczyk

Abstract

The study aimed to extract complex plantation using Object Based Image Analysis (OBIA) techniques. GeoEye-1 image covering Pa Khlok sub-district, Phuket Thailand was used, and thirteen vegetation indices calculated and analyzed with the aim of exploring plantations coverage in the area. Five plantation classes were identified including young coconut, mature coconut, young rubber, mature rubber and oil palm, with another five non-plantation classes assigned to water, built-up land, bare ground, mangrove forest and all other, using rule based techniques. Results support also the idea of mixed plantations in heterogeneous patterns with mixed and missing classes, as experienced in traditional pixel based classification. OBIA techniques can be used successfully to classify complex plantation structures in the study area, with values of 88% and 79% for overall accuracy and kappa coefficients of 0.85 and 0.75 in empirical (development) rules set images and validation images, respectively.

Article Details

How to Cite
Suwanprasit, C., Strobl, J., & Adamczyk, Z. (2015). Extraction of Complex Plantations from VHR Imagery using OBIA Techniques. International Journal of Geoinformatics, 11(1). Retrieved from https://journals.sfu.ca/ijg/index.php/journal/article/view/600
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Articles
Author Biography

C. Suwanprasit, Department of Geography, Faculty of Social Sciences, Chiang Mai University, 239 HuayKeaw Road Mueang, Chiang Mai, 50200, Thailand

Department of Geography, Faculty of Social Sciences, Chiang Mai University, 239 HuayKeaw Road Mueang, Chiang Mai, 50200, Thailand

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