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What is Object-Based Classification

Chapter 681
Encyclopedia of Information Science and Technology, Fourth Edition
Object-based image analysis, a technique used to analyze digital imagery, was developed relatively recently compared to traditional pixel-based image analysis. While pixel-based image analysis is based on the information in each pixel, object-based image analysis is based on information from a set of similar pixels called objects or image objects.
Published in Chapter:
Determination of Urban Growth by the Night-Time Images
Emre Yücer (Erzincan University, Turkey) and Arzu Erener (Kocaeli University, Turkey)
Copyright: © 2018 |Pages: 12
DOI: 10.4018/978-1-5225-2255-3.ch681
Abstract
Urbanization in Turkey and in the world continues is increased especially in the last 30 years. Therefore, urban areas having a dynamic structure should be regularly monitored and the urban region should be determined. There is a need of accurate current data that enables to monitor the temporally changing urban development and land use at regular intervals. In order to determine the urban sizes the 2010 DMSP - OLS (US Air Force Meteorological Satellite Program – operational line scan system) night-time images are used. This study is adapted to all provinces of Turkey. Night-time images in the literature are mainly used for examining the global economic and demographic differences between countries. In order to determine the urban growth from night-time images two different image analysis including object-based and cell-based methods are used in this study. Object-oriented image analysis method includes image segmentation studies and cell-based classification method contains natural breaks and otsu method.
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Chapter 12
Application of Conventional UAVs for the Identification and Classification of Dense Green Spaces
While pixel-based classification is based solely on the spectral information in each pixel, object-based classification uses both spectral and spatial information for classification. The process involves categorization of pixels based on their spectral characteristics, shape, texture, and spatial relationship with the surrounding pixels.
Published in Chapter: Application of Conventional UAVs for the Identification and Classification of Dense Green Spaces; From: Methods and Applications of Geospatial Technology in Sustainable Urbanism
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