Extraction of complex plantations from VHR imagery using OBIA techniques

© Geoinformatics International. 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 co...

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Bibliographic Details
Main Authors: C. Suwanprasit, J. Strobl, J. Adamczyk
Format: Journal
Published: 2018
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Online Access:https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84930238709&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/44795
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Institution: Chiang Mai University
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Summary:© Geoinformatics International. 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.