A New European Settlement Map From Optical Remotely Sensed Data

Florczyk, Aneta J.; Stefano, Ferri; Syrris, Vasileios; Kemper, Thomas; Halkia, Matina; Soille, Pierre; Pesaresi, Martino

doi:10.1109/jstars.2015.2485662

Cited by 53 publications

(42 citation statements)

References 29 publications

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“…-, whose potential is still to be exploited to a great extent because they are not "sufficient in terms of the resolution, thematic granularity, coverage or temporal span. None of the available products offers a wall-to-wall fine-scale and consistent representation of the built-up areas in Europe" (Florczyk et al, 2016).…”

Section: Big Data and New Cartographiesmentioning

confidence: 99%

“…In it, the city is defined as "a local administrative unit (LAU) where the majority of the population lives in an urban center of at least 50 000 inhabitants". Two other units are also defined, the Functional Urban Area -formerly known as larger urban zone (LUZ) -consisting of "a city and its commuting zone", and the Greater City as "an approximation of the urban center when this stretches far beyond the administrative city boundaries" (Dijkstra and Poelman, 2012 Other interesting initiatives have also been developed using these databases, such as the recent European Settlement Map (ESM) project, which uses very high-resolution satellite imagery combined with the general GHSL -Global Human Settlement Layermethodology to support urban policy makers (Florczyk et al, 2016), or the attempt to integrate the MOLAND and Urban Atlas geodatabases (Ribeiro Barranco et al, 2014). All of them are important projects of the Joint Research Center of the European Commission, whose aim is to track urban growth changes systematic and consistently.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Cartographying the real metropolis: A proposal for a data-based planning beyond the administrative boundaries

Selva-Royo

Mardones

Cendoya

2017

Proceedings 24th ISUF 2017 - City and Territory in the Globalization Age

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Cartographying the real metropolis: A proposal for a data-based planning beyond the administrative boundaries. Juan R. Selva-Royo¹, Nuño Mardones¹, Alberto Cendoya² ¹University of Navarra, School of Architecture, Department of Theory and Design, University of Navarra Campus, 31080 Pamplona, Spain; ²University of Navarra, ICS, Navarra Center for International Development, University of Navarra Campus, 31080, Pamplona, Spain E-mail: jrselva@unav.es, nmardones@unav.es, cendoya.alberto@gmail.com Keywords (3-5): Data planning, metropolitan areas, big data, urban extent, good governance Conference topics and scale: Cartography and big data Nowadays, there is a great gap between the functional reality of urban agglomerations and their planning, largely because of the traditional linkage of urban management to the administrative limits inherited from the past. It is also true that the regulation of urban activities, including census and statistical information, requires a closer view of its citizens that can only be addressed from the municipal level. In any case, it is clear that the metropolitan delimitation has met useful but often ethereal or exclusionary criteria (economic or labor patterns, functional areas...), which become disfigured by an administrative reality that does not always correspond to the real metropolis. This paper, aware of the new cartographic possibilities linked to the big data - CORINE Land Cover, SIOSE, multi-sector digital atlases (in many cases referred to the urban extent, etc.) and other open system platforms - explores the evidence that might base a new objective methodology for the delimitation and planning of large urban areas. Indeed, what if basic data for cities would arise not from administrative entities but from independent outside approaches such as satellite imagery? What if every single sensing unit (every citizen, company, building or vehicle) directly issued relevant and dynamic information without going through the municipal collection? Finally, the research analyzes the eventual implications of this data-based planning with administrative structures and urban planning competencies in force through some current case studies, with the purpose of achieving a more efficient and clear metropolitan governance for our planet. References (100 words) Aguado, M. (coord.) (2012) Áreas Urbanas +50. Información estadística de las Grandes Áreas Urbanas españolas 2012 (Centro de Publicaciones Secretaría General Técnica Ministerio de Fomento, Madrid). Angel, S. (dir.) (2016) Atlas of Urban Expansion (http://www.atlasofurbanexpansion.org) accessed 29 January 2017. Brenner, N. and Katsikis, N. (2017) Is the World Urban? Towards a Critique of Geospatial Ideology (Actar Publishers, New York). Florczyk, A. J., Ferri, S., Syrris, V., Kemper, T., Halkia, M., Soille, P., and Pesaresi, M. (2016). ‘A New European Settlement Map from Optical Remotely Sensed Data’, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 9, 1978-1992.

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Section: Big Data and New Cartographiesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Cartographying the real metropolis: A proposal for a data-based planning beyond the administrative boundaries

Selva-Royo

Mardones

Cendoya

2017

Proceedings 24th ISUF 2017 - City and Territory in the Globalization Age

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“…It has been applied in many applications, including urban planning (Hinz and Baumgartner, 2003), disaster evaluation (Turker and Sumer, 2008), change detection (Ji and Yuan, 2007) and map updating (Florczyk et al, 2016). In recent decades, remote sensing images have been widely used in man-made object extraction.…”

Section: Introductionmentioning

confidence: 99%

Man-Made Object Extraction From Remote Sensing Imagery by Graph-Based Manifold Ranking

Wang

et al. 2018

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:The automatic extraction of man-made objects from remote sensing imagery is useful in many applications. This paper proposes an algorithm for extracting man-made objects automatically by integrating a graph model with the manifold ranking algorithm. Initially, we estimate a priori value of the man-made objects with the use of symmetric and contrast features. The graph model is established to represent the spatial relationships among pre-segmented superpixels, which are used as the graph nodes. Multiple characteristics, namely colour, texture and main direction, are used to compute the weights of the adjacent nodes. Manifold ranking effectively explores the relationships among all the nodes in the feature space as well as initial query assignment; thus, it is applied to generate a ranking map, which indicates the scores of the man-made objects. The man-made objects are then segmented on the basis of the ranking map. Two typical segmentation algorithms are compared with the proposed algorithm. Experimental results show that the proposed algorithm can extract man-made objects with high recognition rate and low omission rate.

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“…In particular, the need of performing massive unsupervised image processing tasks in a statistical-model-free approach, i.e., avoiding clustering based on the statistical distribution of the DMP/DAP features, was addressed. The image data scale-decomposed and described by the CSL schema can be used for knowledge-driven image information mining and selection [39,40], supervised and unsupervised classification [41][42][43][44] and visualization purposes [39,45]. In the case of DAPs as with DMPs the problems with memory load and compute time can be addressed using Max-Trees, and their dual Min-Trees [19].…”

Section: Introductionmentioning

confidence: 99%

An Efficient Parallel Algorithm for Multi-Scale Analysis of Connected Components in Gigapixel Images

Wilkinson

Pesaresi

Ouzounis³

2016

IJGI

Self Cite

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Differential Morphological Profiles (DMPs) and their generalized Differential Attribute Profiles (DAPs) are spatial signatures used in the classification of earth observation data. The Characteristic-Salience-Leveling (CSL) is a model allowing the compression and storage of the multi-scale information contained in the DMPs and DAPs into raster data layers, used for further analytic purposes. Computing DMPs or DAPs is often constrained by the size of the input data and scene complexity. Addressing very high resolution remote sensing gigascale images, this paper presents a new concurrent algorithm based on the Max-Tree structure that allows the efficient computation of CSL. The algorithm extends the "one-pass" method for computation of DAPs, and delivers an attribute zone segmentation of the underlying trees. The DAP vector field and the set of multi-scale characteristics are computed separately and in a similar fashion to concurrent attribute filters. Experiments on test images of 3.48 to 3.96 Gpixel showed an average computational speed of 59.85 Mpixel per second, or 3.59 Gpixel per minute on a single 2U rack server with 64 opteron cores. The new algorithms could be extended to morphological keypoint detectors capable of handling gigascale images.

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A New European Settlement Map From Optical Remotely Sensed Data

Cited by 53 publications

References 29 publications

Cartographying the real metropolis: A proposal for a data-based planning beyond the administrative boundaries

Cartographying the real metropolis: A proposal for a data-based planning beyond the administrative boundaries

Man-Made Object Extraction From Remote Sensing Imagery by Graph-Based Manifold Ranking

An Efficient Parallel Algorithm for Multi-Scale Analysis of Connected Components in Gigapixel Images

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