Identification of Banana Plants from Unmanned Aerial Vehicles (UAV) Photos Using Object Based Image Analysis (OBIA) Method (A Case Study in Sayang Village, Jatinangor District, West Java)

Agung Budi Harto, Prila Ayu Dwi Prastiwi, Farah Nafisa Ariadji, Deni Suwardhi, Fenny M. Dwivany, I Wayan Nuarsa, Ketut Wikantika

Abstract


 

 Banana is one of the leading fruit commodities of Indonesia and ranks the sixth position as one of the largest banana producers in the world. There are more than 200 types of banana in Indonesia. The utilization of bananas is influenced by the local culture, where in every 10 horticultural households, 5 of them plant bananas both as garden plants or field plants. This horticultural crop is expectantly being one of the actions to improve economic prosperity especially in rural areas. In maintaining the diversity of the growing bananas in rural areas, a geospatial approach to identify the vegetation is required. Remote sensing technology is one of the solutions to observe and to develop banana plants with one of the methods namely Object Based Image Analysis (OBIA). This method consists of segmentation, classification, and validation. In classification process, the OBIA method distinguishes objects not only based on pixel values but also on the basis of the shape, area, and texture around them. This research has proven that the classification using OBIA method is better than the traditional classification such as maximum likelihood classification method to identify banana plants. OBIA method can quickly identifies the vegetation and non-vegetation, also the regular plants and banana plants.


Keywords


Banana; Object Based Image Analysis (OBIA); Segmentation; Classification; Vegetation

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DOI: https://doi.org/10.4308/hjb.26.1.7

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Copyright (c) 2019 Agung Budi Harto, Prila Ayu Dwi Prastiwi, Farah Nafisa Ariadji, Deni Suwardhi, Fenny M. Dwivany, I Wayan Nuarsa, Ketut Wikantika

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This work is licensed under a Creative Commons Attribution 4.0 International License.