Potential of High-Resolution Satellite Data in the Context of Vulnerability of Buildings

Mueller, Marina; Segl, Karl; Heiden, Uta; Kaufmann, Hermann

doi:10.1007/s11069-005-8637-x

Cited by 39 publications

(27 citation statements)

References 13 publications

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“…Exposure information related to the building stock can be extracted either directly at a building-by-building scale from high-resolution satellite images, or indirectly based on the identification of the urban structure types in which the buildings are located [13]. Urban structure types are in this study defined as areas that are relatively homogeneous in medium-resolution satellite images in terms of their physical appearance (landcover) and usage (landuse) as well as their approximate age.…”

Section: Analysis Of Medium-resolution Optical Satellite Imagerymentioning

confidence: 99%

Exposure Estimation from Multi-Resolution Optical Satellite Imagery for Seismic Risk Assessment

Wieland

Pittore

Parolai

et al. 2012

IJGI

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Given high urbanization rates and increasing spatio-temporal variability in many present-day cities, exposure information is often out-of-date, highly aggregated or spatially fragmented, increasing the uncertainties associated with seismic risk assessments. This work therefore aims at using space-based technologies to estimate, complement and extend exposure data at multiple scales, over large areas and at a comparatively low cost for the case of the city of Bishkek, Kyrgyzstan. At a neighborhood scale, an analysis of urban structures using medium-resolution optical satellite images is performed. Applying image classification and change-detection analysis to a time-series of Landsat images, the urban environment can be delineated into areas of relatively homogeneous urban structure types, which can provide a first estimate of an exposed building stock (e.g., approximate age of structures, composition and distribution of predominant building types). At a building-by-building scale, a more detailed analysis of the exposed building stock is carried out using a high-resolution Quickbird image. Furthermore, the multi-resolution datasets are combined with census data to disaggregate population statistics. The tools used within this study are being developed on a free-and open-source basis and aim at being transparent, usable and transferable.

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Section: Analysis Of Medium-resolution Optical Satellite Imagerymentioning

confidence: 99%

Exposure Estimation from Multi-Resolution Optical Satellite Imagery for Seismic Risk Assessment

Wieland

Pittore

Parolai

et al. 2012

IJGI

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“…However, vulnerability of landscapes to earthquake hazards can be quantified with fault and demographic data. Mueller et al (2006) explored the potential utility of satellite images to determine the vulnerability of buildings to earthquakes using IKONOS and QuickBird imagery. They examined features such as building characteristics (material, height, shape), geologic and edaphic conditions, and context (the position of a house in relation to its surroundings).…”

Section: Predictionmentioning

confidence: 99%

Assessment and prediction of natural hazards from satellite imagery

Gillespie

Chu

Frankenberg

et al. 2007

Progress in Physical Geography: Earth and Environment

106

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Since 2000, there have been a number of spaceborne satellites that have changed the way we assess and predict natural hazards. These satellites are able to quantify physical geographic phenomena associated with the movements of the earth's surface (earthquakes, mass movements), water (floods, tsunamis, storms), and fire (wildfires). Most of these satellites contain active or passive sensors that can be utilized by the scientific community for the remote sensing of natural hazards over a number of spatial and temporal scales. The most useful satellite imagery for the assessment of earthquake damage comes from high-resolution (0.6 m to 1 m pixel size) passive sensors and moderate resolution active sensors that can quantify the vertical and horizontal movement of the earth's surface. High-resolution passive sensors have been used to successfully assess flood damage while predictive maps of flood vulnerability areas are possible based on physical variables collected from passive and active sensors. Recent moderate resolution sensors are able to provide near real time data on fires and provide quantitative data used in fire behavior models. Limitations currently exist due to atmospheric interference, pixel resolution, and revisit times. However, a number of new microsatellites and constellations of satellites will be launched in the next five years that contain increased resolution (0.5 m to 1 m pixel resolution for active sensors) and revisit times (daily ≤ 2.5 m resolution images from passive sensors) that will significantly improve our ability to assess and predict natural hazards from space.

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“…Recently, apart from applications in post-earthquake impact assessments [24][25][26][27][28][29][30][31], many studies have addressed the application of high-resolution remote sensing technology to pre-earthquake exposure, vulnerability, and risk. In these pre-earthquake studies, the and/or -relevant issues (see Equation (1)) of various buildings were widely discussed, including various optical imagery-based specific analyses (Table 1) [32][33][34][35][36][37][38][39][40][41][42][43][44][45][46][47][48][49][50], some attempts at fusing optical imagery and LiDAR or SAR data [51][52][53] to help extract the heights of buildings, and several comprehensive reviews [54][55][56][57]. Table 1.…”

Section: Introductionmentioning

confidence: 99%

An Integrated Method Combining Remote Sensing Data and Local Knowledge for the Large-Scale Estimation of Seismic Loss Risks to Buildings in the Context of Rapid Socioeconomic Growth: A Case Study in Tangshan, China

Zhang

et al. 2015

Remote Sensing

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Rapid socioeconomic development in earthquake-prone areas can cause rapid changes in seismic loss risks. These changes make it difficult to ensure that risk reduction strategies are realistic, practical and effective over time. To overcome this difficulty, ongoing changes in risk should be captured timely, definitively, and accurately and then specific and well-timed adjustments of the relevant strategies should be made. However, methods for rapidly characterizing such seismic disaster risks over a large area have not been sufficiently developed. By focusing on building loss risks, this paper presents the development of an integrated method that combines remote sensing data and local OPEN ACCESSRemote Sens. 2015, 7 2544 knowledge to resolve this problem. This method includes two key interdependent steps.(1) To extract the heights and footprint areas of a large number of buildings accurately and quickly from single high-resolution optical remote sensing images; (2) To estimate the floor areas, identify structural types, develop damage probability matrixes, and determine economic parameters for calculating monetary losses due to seismic damage to the buildings by reviewing building-relevant local knowledge based on these two parameters (i.e., the building heights and footprint areas). This method is demonstrated in the Tangshan area of China. Based on the integrated method, the total floor area of the residential and public office buildings in central Tangshan in 2009 was 3.99% lower than the corresponding area number obtained by a conventional earthquake loss estimation project. Our field-based verification indicated that the mean relative error of the method for estimating the floor areas of the assessed buildings was 2.99%. A simulation of the impacts of the 1976 Ms 7.8 Tangshan earthquake using this method indicated that the total damaged floor area of the residential and public office buildings and the associated direct monetary loses in the study area could have been 8.00 and 28.73 times greater, respectively, than in 1976 if this earthquake had recurred in 2009, which is a strong warning to the local people regarding the increasing challenges they may face.

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Potential of High-Resolution Satellite Data in the Context of Vulnerability of Buildings

Cited by 39 publications

References 13 publications

Exposure Estimation from Multi-Resolution Optical Satellite Imagery for Seismic Risk Assessment

Exposure Estimation from Multi-Resolution Optical Satellite Imagery for Seismic Risk Assessment

Assessment and prediction of natural hazards from satellite imagery

An Integrated Method Combining Remote Sensing Data and Local Knowledge for the Large-Scale Estimation of Seismic Loss Risks to Buildings in the Context of Rapid Socioeconomic Growth: A Case Study in Tangshan, China

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