Object Based Image Analysis for Remote Sensing

Dear Colleagues,

Object-based Image Analysis (OBIA) has evolved to a widespread methodology for image analysis, especially in the context of remote sensing. With the emergence of Very High Resolution (VHR) remote sensing data it turned out that methods which operate on image segments instead of single pixels show lots of advantages when analyzing the content of remote sensing data. With the advent of user friendly software, which allowed to analyze remote sensing data in OBIA manner, OBIA has been further boosted in the remote sensing and GIS community. The numerous scientific publications dealing with OBIA in the remote sensing and GIS domain show, that this methodology has meanwhile established – probably even as a paradigm for image analysis. Simultaneously, the methodology itself underwent a step-by-step evolution, comprising the development of new segmentation methods, the integration of new classification methods and the development of new methods for change detection and monitoring, just to name a few. Meanwhile, the integration of new methods - mainly originating in AI - plays an important role for OBIA. Exemplary, the explicit formulation and management of knowledge, the application of artificial learning and learning mechanisms, but also self-organizing agent-based systems are interesting new developments in OBIA which originate in AI.

In this special issue, we first intend to outline the state-of-the-art in OBIA for remote sensing and the methodologies it comprises meanwhile. Further, we intend to present recent concepts, frameworks and new methods which found their way to OBIA in conjunction with recent applications and success stories of OBIA in remote sensing. This will span a wide spectrum ranging from: image segmentation methods, software engineering in the context of OBIA, semantic modelling and reasoning, ontologies and knowledge representations, classification methods including Complex Neural Networks (CNNs) to self-organizing approaches such as multi-agent systems. Further, OBIA-specific approaches of change detection and monitoring as well as the incorporation of non-remote sensing and even unstructured data are further aspects we want to deal with. Last but not least cloud computing and Big Earth Data in the context of OBIA are challenging fields we would like to spot at.

We would like to invite colleagues to submit articles about their recent research on any of the following topics but not restricted to:

• Image segmentation and joined aspects, such as optimization, quality assessment, transferability, etc.
• Software development and engineering in the context of OBIA including robustness and quality assessment.
• Knowledge representation and management, including ontologies and reasoning.
• Classification methods including CNNs and other ANN-based methods.
• Self-organizing methods such as Multi-Agent Systems in OBIA.
• Object-based change detection and monitoring methods.
• Data integration and usage.
• Cloud computing and Big Earth Data in OBIA.
• Applications of OBIA in remote sensing and success stories with OBIA.

Prof. Dr. Raul Queiroz Feitosa
Dr. Peter Hofmann
Prof. Dr. Cláudia Maria de Almeida
Prof. Dr. Gilson Alexandre Ostwald Pedro da Costa
Guest Editors

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