Introduction to object-based landscape analysis

This article may be used for research, teaching and private study purposes. Any substantial or systematic reproduction, redistribution , reselling , loan, sub-licensing, systematic supply or distribution in any form to anyone is expressly forbidden. The publisher does not give any warranty express or implied or make any representation that the contents will be complete or accurate or up to date. The accuracy of any instructions, formulae and drug doses should be independently verified with primary sources. The publisher shall not be liable for any loss, actions, claims, proceedings, demand or costs or damages whatsoever or howsoever caused arising directly or indirectly in connection with or arising out of the use of this material. Current environmental challenges often require regular and wide-area monitoring, which in theory Earth observation (EO) can provide. Commonly, these challenges do not focus on individual point targets, as represented by image pixels, but require consideration of whole landscapes and assessment of features in broader spatial contexts. Object-based approaches, which operate at the scale of real-world objects rather than pixels, offer a means of analysing EO data in a realistic context and integrating associated ancillary information to support real-world applications. The development of object-based image analysis has accelerated over the past decade and can now be considered mainstream, with commercially available software and a wide user community. For full and rigorous consideration of the implementation of object-based analysis in environmental applications, we propose an extension of the discussion to object-based 'landscape' analysis. This article serves as an introduction to a Special Issue on this theme, drawing on a technical meeting held in 2009 at The University of Nottingham, UK. The meeting's aim was to bring together practitioners in remote sensing, geographic information science (GIScience) and environmental science to identify best practice in the development and application of object-based landscape analysis techniques. The papers presented outline new opportunities for object-based landscape analysis, showing the expansion of object-centred classification studies beyond routine use of image data, engaging with fundamental GIScience concepts such as spatial accuracy and scale and demonstrating the wider and growing relevance for the EO, GIScience, landscape ecology and broader environmental science communities. 1. Introduction Earth observation (EO) imagery is an important source of information for characterisa-tion of the earth's surface, especially when considering current environmental challenges, such as climate change and biodiversity assessment. Many of these challenges require regular , wide-area monitoring and do not focus …