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|Title:||A methodology to quantify built-up structures from optical VHR imagery|
|Authors:||PESARESI Martino; EHRLICH Daniele|
|Publisher:||CRC Press, Taylor & Francis Group|
|Type:||Articles in books|
|Abstract:||One of the basic ideas below this paper is that a really effective remote sensing of human settlements needs the harmonic development of three basic areas: the remote sensor technology, the information extraction methodology, and the conceptual tools able to handle the extracted information, say the classification scheme. These three areas should go together: an unbalanced progress only on sensor technology for example would make failures on application of outdated information extraction models. Similarly, progresses on sensor technology and information extraction methodology would be ineffective if we maintain the same classification schema tuned for the precedent situation. The present paper tries to address these issues applied to the analysis of human settlements by arguing i) a special status and characteristic of the settlement theme that make difficult the traditional approach of remote sensing ii) the need of new methodologies for extracting information on settlements from satellite data and iii) the need of a new paradigm for structuring the extracted geo-information in more effective data models. In particular, the special status of the settlement theme is described as complexity of the use context of the information about the human settlement, and as specific physical characteristics (the spatial heterogeneity of internal materials and mimetism with the surrounding areas) that break the standard remote sensing model postulating spectrally homogenous and distinguishable classes to be recognized. Because of the specific physical characteristics of the settlement theme, we argue the importance to process the image structural information in order to improve the effectiveness of the automatic discrimination and analysis of the settlement¿s elements using satellite data. Because of the specific use contest of the information about settlements, we argue the necessity to reduce the rigidity of the conceptual paradigm used for storing and representing the extracted information, say the LU/LC standard classification schema. This is done by modulating the semantic abstraction of the extracted information in three levels, and consequently by avoiding the rapid obsolescence of too abstract or high-level and user-specific semantics. As described in the following paragraphs, these abstraction levels have different matches with possible techniques for image automatic recognition and analysis, and they may have different logical compositional constraints.|
|JRC Institute:||Institute for the Protection and Security of the Citizen|
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