Integrating earth observation and GIScience for high resolution spatial and functional modeling of urban land use

Aubrecht, Christoph; Steinnocher, Klaus; Hollaus, Markus; Wagner, Wolfgang

doi:10.1016/j.compenvurbsys.2008.09.007

Cited by 76 publications

(40 citation statements)

References 13 publications

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“…Population models can be further improved by using more up-to-date and detailed land use/land cover data detailing functional use, ideally by city block or building (Aubrecht et al, 2009). This improvement was already demonstrated for part of the study area in the context of exposure to tsunami .…”

Section: Discussionmentioning

confidence: 99%

Integrating population dynamics into mapping human exposure to seismic hazard

Freire

Aubrecht

2012

Nat. Hazards Earth Syst. Sci.

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Abstract. Disaster risk is not fully characterized without taking into account vulnerability and population exposure. Assessment of earthquake risk in urban areas would benefit from considering the variation of population distribution at more detailed spatial and temporal scales, and from a more explicit integration of this improved demographic data with existing seismic hazard maps. In the present work, "intelligent" dasymetric mapping is used to model population dynamics at high spatial resolution in order to benefit the analysis of spatio-temporal exposure to earthquake hazard in a metropolitan area. These night-and daytime-specific population densities are then classified and combined with seismic intensity levels to derive new spatially-explicit four-classcomposite maps of human exposure. The presented approach enables a more thorough assessment of population exposure to earthquake hazard. Results show that there are significantly more people potentially at risk in the daytime period, demonstrating the shifting nature of population exposure in the daily cycle and the need to move beyond conventional residence-based demographic data sources to improve risk analyses. The proposed fine-scale maps of human exposure to seismic intensity are mainly aimed at benefiting visualization and communication of earthquake risk, but can be valuable in all phases of the disaster management process where knowledge of population densities is relevant for decisionmaking.

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Section: Discussionmentioning

confidence: 99%

Integrating population dynamics into mapping human exposure to seismic hazard

Freire

Aubrecht

2012

Nat. Hazards Earth Syst. Sci.

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“…In addition, the thematic components of urban systems are increasing in utility and importance in areas such as monitoring urban developments, land cover change detection and mapping of natural hazards. Technologies such as very high resolution remote sensing and airborne laser scanning (ALS) offer a wide range of new possibilities for modelling urban systems and require applied research to develop and implement new methodologies [54]. While LiDAR was introduced earlier, we note, that for ALS point clouds and derived products we may even more urgently need integrations methods.…”

Section: Thoughts On Urban Morphology and Functionmentioning

confidence: 99%

“…Thomas et al [16] compared traditional pixel-based classification methods in an urban environment with two methods that incorporated shape, texture, and context. There are also convincing examples of combining remote sensing and GIS data to derive particular land use-rather than land cover-classes or environmental indicators, see for instance [53][54][55][56][57]. Zhou et al [55] investigate how remotely sensed lawn characteristics, such as parcel lawn area and parcel lawn greenness, combined with household characteristics, can be used to predict household lawn fertilization practices on private residential lands.…”

Section: Integrating Remote Sensing and Gis For Urban Analysismentioning

confidence: 99%

Collective Sensing: Integrating Geospatial Technologies to Understand Urban Systems—An Overview

et al. 2011

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Cities are complex systems composed of numerous interacting components that evolve over multiple spatio-temporal scales. Consequently, no single data source is sufficient to satisfy the information needs required to map, monitor, model, and ultimately understand and manage our interaction within such urban systems. Remote sensing technology provides a key data source for mapping such environments, but is not sufficient for fully understanding them. In this article we provide a condensed urban perspective of critical geospatial technologies and techniques: (i) Remote Sensing; (ii) Geographic Information Systems; (iii) object-based image analysis; and (iv) sensor webs, and recommend a holistic integration of these technologies within the language of open geospatial consortium (OGC) standards in-order to more fully understand urban systems. We then discuss the potential of this integration and conclude that this extends the monitoring and mapping options beyond "hard infrastructure" by addressing "humans as sensors", mobility and human-environment interactions, and future improvements to quality of life and of social infrastructures.

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“…For example, sensors like IKONOS and Quickbird are used to discriminate between duplex, triplex or condominium units. Researchers have also been experimenting with Airborne Laser Scanning (ALS) data to improve the classification of urban structures [18]. Additionally, land cover types were differentiated based on their relative height above ground, enabling the creation of a 3D building model.…”

Section: Urban Studiesmentioning

confidence: 99%

Remote Sensing in Social Science Research~!2009-12-28~!2010-03-26~!2010-06-25~!

Hall¹

2010

TORMSJ

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Abstract:Since the early days of satellite remote sensing in the 1950's, accessibility, quality, and scope of remote sensing image data has been continuously improving, making it a rich data source with a wide range of applications. Today, the use of remote sensing techniques and data is commonplace within many disciplines in the natural sciences. Although there are quite a few examples of remote sensing to be found in the social sciences, developments here have, on the whole, been less pronounced. This paper investigates 1) how remote sensing data has been put to use in social science studies, and 2) how social science could better utilize the huge potential of remote sensing data. The first part of the paper gives an overview of existing types of remote sensing techniques and data collection. The second part consistsof a review of social science applications of remote sensing data. In the conclusions it is argued that remote sensing data is at its most valuable in the social sciences when used in combination with traditional methods such as surveys, public records, interviews and direct observation.

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Integrating earth observation and GIScience for high resolution spatial and functional modeling of urban land use

Cited by 76 publications

References 13 publications

Integrating population dynamics into mapping human exposure to seismic hazard

Integrating population dynamics into mapping human exposure to seismic hazard

Collective Sensing: Integrating Geospatial Technologies to Understand Urban Systems—An Overview

Remote Sensing in Social Science Research~!2009-12-28~!2010-03-26~!2010-06-25~!

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