The 2017 Data Fusion Contest, organized by the Image Analysis and Data Fusion Technical Committee (IADF TC) of the IEEE Geoscience and Remote Sensing Society (GRSS), aims at providing a challenging image analysis opportunity, including multiresolution and multimodal fusion. The 2017 contest focuses on the classification of local climate zones (LCZs) [1] in various urban environments. LCZs are a generic, climate-based typology of urban and natural landscapes that deliver information on basic physical properties of an area that can be used by land-use planners or climate modelers [2]. They are used as first-order discretization of urban areas by the World Urban Database and Access Portal Tools (WUDAPT) initiative, which aims to collect, store, and disseminate data on the form and function of cities around the world [3].

2017 IEEE GRSS Data Fusion Contest: Open Data for Global Multimodal Land Use Classification [Technical Committees]

Tuia, Devis;Moser, Gabriele;
2017

Abstract

The 2017 Data Fusion Contest, organized by the Image Analysis and Data Fusion Technical Committee (IADF TC) of the IEEE Geoscience and Remote Sensing Society (GRSS), aims at providing a challenging image analysis opportunity, including multiresolution and multimodal fusion. The 2017 contest focuses on the classification of local climate zones (LCZs) [1] in various urban environments. LCZs are a generic, climate-based typology of urban and natural landscapes that deliver information on basic physical properties of an area that can be used by land-use planners or climate modelers [2]. They are used as first-order discretization of urban areas by the World Urban Database and Access Portal Tools (WUDAPT) initiative, which aims to collect, store, and disseminate data on the form and function of cities around the world [3].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/893543
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