A Platform for Spatial Data Labeling in an Urban Context

Lesbegueries, Julien; Lachiche, Nicolas; Braud, Agnès; Skupinski, Grzegorz; Puissant, Anne; Perret, Julien

doi:10.1007/978-3-642-10595-1_4

Cited by 9 publications

(5 citation statements)

References 8 publications

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“…In order to analyze the interactions between climate and urban shape, the territory is partitioned into elementary areas: the « city blocks » (Lesbegueries et al 2009). This partitioning is generic and automatic: morphologically homogeneous city blocks are defined from the road network as illustrated in Figure 2 to respect the spatial organization of the city and the building configurations.…”

Section: Elementary Spatial Unit: the City Blockmentioning

confidence: 99%

Radiative and heat storage properties of the urban fabric derived from analysis of surface forms

Bernabé

Bernard

Musy³

et al. 2015

Urban Climate

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Highlight-Urban albedo is computed at city block scale from solar simulations.-Temperature signal time shift is calculated from three years of measurements.-Urban albedo is strongly related to sky view factor and facade density.-Temperature signal time shift is explained by aspect ratio H/W and facade density.-Climatic maps could be directly produced from geographical data. AbstractRadiative balance and heat storage capacity modifications play a major role in urban heat island formation. Urban shape determines the receipt and loss of radiation and consequently the heat storage potential, thus resulting in a higher air temperature.In order to analyze the interactions between climate and urban shape, the territory is partitioned from the road network into elementary areas: the city blocks.Nine geographical and two climatic indicators are computed at city block scale. The geographical ones are produced thanks to OrbisGIS platform from geographical data supplied by the French IGN. The first climatic indicator, the urban albedo, is computed from solar simulations with Solene model on 230 city blocks to characterize the radiative balance. The second one, the air temperature time shift, is calculated from three years of measurements between eight city blocks and a reference sites to characterize the heat storage properties of the urban fabric.Relationships between those climatic and geographical indicators are investigated using linear regression analysis. Facade density is the geographical indicator which best explains both radiative and heat storage properties at city block scale. From the relationships identified previously and geographical data, climatic maps are produced to assess urban vulnerability to climate change.

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Section: Elementary Spatial Unit: the City Blockmentioning

confidence: 99%

Radiative and heat storage properties of the urban fabric derived from analysis of surface forms

Bernabé

Bernard

Musy³

et al. 2015

Urban Climate

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“…The method to create these historical databases has been presented in (Perret et al 2009). During the project we created historical databases at different dates on different areas.…”

Section: Experimental Results and Commentsmentioning

confidence: 99%

Advances in Cartography and GIScience. Volume 2

Ruas¹

2011

Lecture Notes in Geoinformation and Cartography

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“…Finally, some additional errors may be caused by the false topological relations of the objects that appear during the generalization. And some problems arising while overlapping and labeling objects should be mentioned as well [11]. Some uncertainness still to mention: shadows from the buildings, directions of roofs, etc.…”

Section: Limitationsmentioning

confidence: 99%

Topology, homogeneity and scale factors for object detection: application of eCognition software for urban mapping using multispectral satellite image

Lemenkova¹

2019

Preprint

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The research scope of this paper is to apply spatial object based image analysis (OBIA) method for processing panchromatic multispectral image covering study area of Brussels for urban mapping. The aim is to map different land cover types and more specifically, built-up areas from the very high resolution (VHR) satellite image using OBIA approach. A case study covers urban landscapes in the eastern areas of the city of Brussels, Belgium. Technically, this research was performed in eCognition raster processing software demonstrating excellent results of image segmentation and classification. The tools embedded in eCognition enabled to perform image segmentation and objects classification processes in a semi-automated regime, which is useful for the city planning, spatial analysis and urban growth analysis. The combination of the OBIA method together with technical tools of the eCognition demonstrated applicability of this method for urban mapping in densely populated areas, e.g. in megapolis and capital cities. The methodology included multiresolution segmentation and classification of the created objects.

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A Platform for Spatial Data Labeling in an Urban Context

Cited by 9 publications

References 8 publications

Radiative and heat storage properties of the urban fabric derived from analysis of surface forms

Radiative and heat storage properties of the urban fabric derived from analysis of surface forms

Advances in Cartography and GIScience. Volume 2

Topology, homogeneity and scale factors for object detection: application of eCognition software for urban mapping using multispectral satellite image

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