Urban and Regional Data Management

Rumor, Massimo; Coors, Volker; Fendel, Elfriede M.; Zlatanova, Sisi

doi:10.4324/9780203931042

Cited by 11 publications

(2 citation statements)

References 6 publications

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“…Nowadays, digital databases implemented into Geographical Information Systems (GIS) have become a fundamental tool in the procedure of preparation of geo-engineering maps. Recent engineering geological maps at urban environments are based on ground databases, which are generally manipulated using GIS software (Chaminé et al, 2016;Culshaw & Northmore, 2015;El May, Dlala, & Chenini, 2010;Faccini, Robbiano, Roccati, & Angelini, 2012;Forster, Lawrence, Highley, Cheney, & Arrick, 2004;Masoud, 2016;Merritt & Whitbread, 2007;Oliveira, Gomes, & Guimarães, 2009;Zuquette, Pejon, & Dos Santos Collares, 2004), and therefore, this methodology seems to be fully consolidated to approach these environments subsoil studies.…”

Section: Introductionmentioning

confidence: 99%

Geotechnical map of a coastal and industrialized urban area (Avilés, NW Spain)

et al. 2017

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Geotechnical mapping of urban environments is usually constrained by the scarcity of outcrops during fieldwork. Such is the case of Avilés, a coastal Spanish city that has been heavily industrialized since the middle of the last century. This research approaches the study of its urban subsoil through the development of a Geographical Information Systems-based relational database containing thousands of unpublished ground data, partially extracted from geotechnical reports. This allowed analysing the distribution and changes of thickness of the superficial deposits and lithostratigraphic formations as well as the evaluation of their main geotechnical properties. Thus, 14 geotechnical units were differentiated (hierarchically displayed in three categories) depending on lithological, geotechnical and constructive criteria. As a result, this investigation provides a geo-engineering map at scale 1:25,000.

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Section: Introductionmentioning

confidence: 99%

Geotechnical map of a coastal and industrialized urban area (Avilés, NW Spain)

et al. 2017

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“…For instance, some of these used specific landscape spatial metrics to characterize the configuration and composition of urban areas (e.g., [15][16][17][18][19]). While many such parameters have been identified, it is generally difficult to distinguish between those that are useful and those that are not.…”

Section: Introductionmentioning

confidence: 99%

Is Spatial Resolution Critical in Urbanization Velocity Analysis? Investigations in the Pearl River Delta

et al. 2017

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Grid-based urbanization velocity analysis of remote sensing imagery is used to measure urban growth rates. However, it remains unclear how critical the spatial resolution of the imagery is to such grid-based approaches. This research therefore investigated how urbanization velocity estimates respond to different spatial resolutions, as determined by the grid sizes used. Landsat satellite images of the Pearl River Delta (PRD) in China from the years 2000, 2005, 2010 and 2015 were hierarchically aggregated using different grid sizes. Statistical analyses of urbanization velocity derived using different spatial resolutions (or grid sizes) were used to investigate the relationships between socio-economic indicators and the velocity of urbanization for 27 large cities in PRD. The results revealed that those cities with above-average urbanization velocities remain unaffected by the spatial resolution (or grid-size), and the relationships between urbanization velocities and socio-economic indicators are independent of spatial resolution (or grid sizes) used. Moreover, empirical variogram models, the local variance model, and the geographical variance model all indicated that coarse resolution version (480 m) of Landsat images based on aggregated pixel yielded more appropriate results than the original fine resolution version (30 m), when identifying the characteristics of spatial autocorrelation and spatial structure variability of urbanization patterns and processes. The results conclude that the most appropriate spatial resolution for investigations into urbanization velocities is not always the highest resolution. The resulting patterns of urbanization velocities at different spatial resolutions can be used as a basis for studying the spatial heterogeneity of other datasets with variable spatial resolutions, especially for evaluating the capability of a multi-resolution dataset in reflecting spatial structure and spatial autocorrelation features in an urban environment.

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