2012 ©
             Publication
Journal Publication
Title of Article OBJECT-BASED IMAGE ANALYSIS APPLIED FOR DIFFERENT STAGES OF RUBBER PLANTATIONS MAPPING USING THAICHOTE SATELLITE DATA. 
Date of Acceptance 26 January 2019 
Journal
     Title of Journal JOURNAL OF THEORETICAL AND APPLIED INFORMATION TECHNOLOGY 
     Standard SCOPUS 
     Institute of Journal Little Lion Scientific 
     ISBN/ISSN 1992-8645 
     Volume 97 
     Issue
     Month มีนาคม
     Year of Publication 2019 
     Page  
     Abstract During 2000 to 2011, rubber plantations rapidly expanded in northeast Thailand, which had not been historically planted. Information about planted areas and their distribution is a prerequisite for formulating land use planning and understanding its consequences on ecosystems. This study aimed to establish a model for digitally devising a synergistic approach to distinguishing the different stages of rubber plantations in the northeasternmost region of Thailand and a small portion of the Lao People's Democratic Republic (Lao PDR). The combination of Object-Based Image Analysis (OBIA), Vegetation Canopy Density (VCD), plant phenology and intensive ground observation was applied to THAICHOTE satellite data. Two levels of classification based on OBIA approach were performed. At the first level, multi-scale image segmentation of pansharpened imagery was performed to divide the image set into objects with different spectral and spatial characteristics. Incorporating the normalized difference vegetation index (NDVI) and brightness index (BI) into the objects, the image set was subdivided into four different subsets of VCD. Analyses were then performed at the next level classification on each of VCD subsets by using certain and a range of different approaches to discriminate stand age rubber tree plantations. Rubber tree phenology and OBIA feature optimization were used to differentiate the different stages of rubber plantations. The results indicated that the agreement between field-based classification and image-based classification was well correlated. The overall accuracy of 79.00 % and Cohen’s kappa coefficient of 0.77 were achieved for the integrated models for the different stage of rubber plantations. 
     Keyword THAICHOTE satellite data; Different stages of rubber plantations; Object-based image analysis (OBIA); Vegetation canopy density (VCD); Plant phenology; Northeast Thailand 
Author
557020068-3 Miss WASANA PUTKLANG [Main Author]
Science Doctoral Degree

Reviewing Status มีผู้ประเมินอิสระ 
Status ได้รับการตอบรับให้ตีพิมพ์ 
Level of Publication นานาชาติ 
citation true 
Part of thesis true 
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