10CUEE CONFERENCE PROCEEDINGS
10th International Conference on Urban Earthquake Engineering
March 1-2, 2013, Tokyo Institute of Technology, Tokyo, JapanEVALUATION OF SEISMIC VULNERABLE AREAS IN LIMA CITYBY USING SATELLITE INFORMATION

Miguel Estrada1), Masashi Matsuoka2), and Hiroyuki Miura3)
1) Associate Professor, Faculty of Civil Engineering, National University of Engineering, Peru
2) Associate Professor, Department of Built Environment, Tokyo Institute of Technology, Japan
3) Associate Professor, Faculty of Engineering, Hiroshima University, Japanestrada@uni.edu.pe, matsuoka.m.ab@m.titech.ac.jp, hmiura@hiroshima-u.ac.jp

Abstract: Within the project Enhancement of Earthquake and Tsunami Disaster Mitigation Technology in Peru, one ofthe objectives is to know the most vulnerable areas in the event of a big earthquake. In Lima, the capital city of the Peru,
for many years has become the destination of inhabitants of the interior of the country, which has led to use unsuitableterrain areas as for example the slopes of the hills. This disorderly development has caused that the cadastral maps are not
updated and therefore the extension occupied by these populations cannot be quantified. This article presents the use andintegration of two sources of satellite information for the determination of vulnerable areas in the city of Lima, highresolution optical satellite images and images from PRISM sensor, which allows getting the digital elevation model. With
this integration, it is possible to delineate and evaluate the likely areas of urban concentration in areas of threat. Also it iscarried out the integration with social information obtained from national census in order to determine the homes ofpeople with low economic resources that occupy this type of land.

1.

INTRODUCTION

It is well known that seismic activity in Peru is very
high, due to its location in the circum-Pacific seismic belt,
therefore, the evaluation of the building vulnerability it very
important issue to prevent and mitigate the effects of aneventual occurrence of an earthquake. In Peru thedevelopment of cities is carry out, in many cases, without
development planning projects, people from the countrysidethat comes to the capital city, looking for better live
conditions, settles where they can, and this situation
generates two big problems: first, they occupy land that areinadequate for construction of buildings, like soils withincompetent conditions as soils with low load capacity or
they occupy the hillside surrounding the city. On the other
hand, those peoples build their houses as they can, using low
quality materials and without any technical direction.
Therefore, these non-engineered buildings located innon-suitable locations, makes them very vulnerable
structures in the case of an earthquake, thus theiridentification is very important for local authorities to makepreparedness and mitigation plans.
Other problem to be faced is the lack of cadastral andtopographic information that do not allow to make abuilding inventory and thus to evaluate the building seismic
vulnerability (Estrada et. al., 2012). Therefore, it isnecessary to use a technology that allows the identificationof populated areas, especially those that are occupied on thehillside.
Additionally to the physical information, another typeof data is the social one. The social information allows toknow the economic situation of the building owner and thus
to infer the quality and condition of the building.
In this paper it is proposed the use of PRISM sensorimagery to determine the location of those populated placedon hillsides and with the census data added to complement
the study of the vulnerability.
2.

PRESENT SITUATION

2.1 Study area
The study area is located in Lima, the capital city ofPeru. Lima city is politically divided in 43 districts; one ofthem is Comas district. This district has a growing
population of more of less half a million people, and the flatarea of the district is already densely occupied, this is thereason that the hillsides are being populated rapidly,
therefore the evaluation of these areas are necessary.
Figure 1 shows the location of the study area. There it canbe seen that the flat area is already populated and the growthof the city is towards the hills.
Figure 2, shows the conditions of the buildings built on
the hillsides. It can be appreciated the informality ofbuildings and poor building practices, like building theirhouses on land fill, to accommodate to the topography of theland. This situation generates a highly risky area in case of- 1613 -the occurrence of a severe earthquake.

Besides of the population density, another importantfactor if the social class of the people. The social class is agood indicator of the quality of the building where thepeople live. It is obvious that well accommodated people
lives in houses well constructed, while low income people
construct their houses as they can and as they want, making
these non-engineered buildings very vulnerable against
seismic forces.
Information about social classes is shown in Table 2.
As it can be seen mainly the population in this area isrepresented for low and middle low social class people,
being almost 90% of the total number of blocks withinformation.
Table 2. Type of social class from census data.
Socioeconomic level
Low
Middle low
MiddleMiddle highHighNo Data

Figure 1 Map of the Comas District and selected study
area.

Number of blocks
289
474
82
40167

Another important parameter to evaluate thevulnerability of buildings is the material used in theconstruction. Table 3 shows the number of houses built withthe different material used in this area:
Table 3. Type of social class from census data.
Material
Masonry
Adobe
WoodQuincha (bamboo with wood frame)
BambooOther/No Data

Figure 2 Photograph of the condition of the buildings onthe hillsides.
2.1 Cadastral Information
In 2007 the National Institute of Statistics andInformatics (INEI) carried out the National Census 2007: XIof population and VI of Housing (INEI, 2007). The
information is aggregated in each block from where it isextracted the following information, within the study area,
shown in Table 1:
Table 1. Census data of the study area.
Description
Number of blocks
Average number of houses per block
Total number of houses
Total number of habitants
Average Number of habitants per house

Value10162214374
77900
5.42

As it can be seen in Table 1, the density of habitants ineach house is relativity high, this situation makes this area ahighly risk one in case of a severe earthquake.

Number of houses
11200
101
1979
17446
631

As it can be seen in this table, the main material used
for construction is masonry, but even the masonry is a goodmaterial for construction the quality of the construction
process is the problem, since the people built their houses bythemselves, without any technical direction, these houses do
not accomplish the requirements of national code, therefore
their vulnerability is very high.
The presented tables show statistical values of thesocial condition of the people that live in this area. This is ahigh density populated area that is under developing withproblems that make this area very vulnerable in case of anoccurrence of an earthquake. Mainly there are two big
problems the self-construction of the houses and the bad soil
condition, as it can be seen in Figure 2. The topography of
the area is very rugged and the uneven soil forces people tobuild their houses on landfill. Therefore, it is necessary toevaluate the topography of the area to determine theoccupied land with important value of slope.

- 1614 -Table 4.
3. UMBRELLA PROJECTThis research is under the project “Enhancement ofEarthquake and Tsunami Disaster Mitigation Technology inPeru”. Generally speaking, the purpose of this project is todeveloped technologies and measures for prediction andmitigation of earthquake/tsunami disasters caused bylarge-magnitude inter-plate earthquakes occurring off thecoast of Peru (Yamazaki et. al., 2012)
This project is divided into five active groups. Group1, researches on seismology and geotechnical issues, andgive the final response of the soils, like probable peakground acceleration. Group 2, studies the source, effects
and countermeasures of tsunamis produced by an earthquake,mainly the output is the travel time and high of the tsunami
waves to evaluate the possible damage in the affected area.
Group 3, identifies the most typical building problems andwill propose retrofitting methods or will give some advises
to improve the actual building code. Group 4, will develop
methodologies to identify the land use, by using the satellite
imagery and integrating all the information in a GIS
platform to assess the risk of the building as well as todevelop a methodology for fast assessment of the damaged
area by an earthquake or tsunami. Finally, Group 5 willtake the entire group’s output and will disseminate thisknowledge and propose policies for a sustainable
development of the population. This project is under thesupport of Japan International Cooperation Agency (JICA),
Japan Science and Technology Agency (JST) and Peruvian
International Cooperation Agency (APCI). The institutions
directly involved in this project are Chiba University,Tohoku University, Building Research Institute, Yokohama
University, Tokyo Institute of Technology, Tsukuba
University and Kyoto University, from the Japanese side andthe Japan Peru Center for Earthquake Engineering Researchand Disaster Mitigation (CISMID), Hydrograph National
Direction (DHN), Geophysics Institute of Peruvian (IGP),
Ministry of Construction, Housing and Sanitation, NationalCommission of Aerospace Research and Development(CONIDA), National Institution of Civil Defense andNational Center of Assessment, Prevention and Mitigationof risk Disasters (CENEPRED).

Figure 3 Schematic view of PRISM sensor, with three
optical systems: nadir, forward and backward. Source:
http://en.alos-pasco.com/common/images/prism2.gif
Table 4. Main characteristics of PRISM sensor.
Description
Value
Number of bans
1
Wavelength
0.52 – 0.77 µm
Number of optics
3: nadir, forward, backward
Ground resolution
2.5 m (nadir view)
Swath
70 km
Source: http://en.alos-pasco.com/alos/prism/index.html

The raw PRISM satellite images are processed to obtaintwo kinds of images: First the digital Surface Model (DSM)
and the panchromatic image, as shown in Figure 4.

Within this project is Group 4 who is in charge ofdeveloping methodologies to assess the vulnerability in
Lima by using geo-informatics technologies.
4. SATELLITE IMAGERY INFORMATIONThe original images come from the Panchromatic
Remote Sensing Instrument for Stereo Mapping (PRISM)
sensor that is one of the three sensors that are on board of theAdvanced Land Observing Satellite (ALOS). The capabilityof this sensor to generate three dimensional models, comesfrom the simultaneous acquisition from three optical systems,
as shown in Figure 3 (Pasco Corp. 2013). The generalcharacteristics of this sensor are shown inFigure 4 PRISM digital Surface Model and panchromaticimage.

- 1615 -Since the cadastral information is not updated and sincethe idea is to generate actual risk map it is used another typeof optical satellite image, the WorldView-2.
Thecharacteristics of this image are shown in Table 5.

The result of the slope analysis is shown in Figure 7.

Table 5. Main characteristics of WorldView-2 sensor.
Description
Number of bans (MS – P)
Wavelength
Spatial resolution
Swath
Acquisition date

Value
8-1
0.427 – 0.908µm MS, 0.632 µm P
2.0 m MS/0.5 m PAN
70 km
10 April 2010

Source: https://www.digitalglobe.com/The raw WorldView-2 image is pansharpened by using
Gram-Schmidt Spectral Sharpening (ENVI program) to takeadvantage of the spectral information of the bands. Then thisimage is georeferenced to geographically match the blocklayer. The WorldView-2 image is shown in Figure 5.

Figure 5 WorldView-2 pansharpened image integrated withblocks layer.
5. EVALUATION OF VULNERABLE AREAS
Once the images have been georeferenced with theblock layer the next step is the integration of three sources ofinformation: digital surface model, the high resolution image
and the census data. Figure 6 shows the integration of thesethree sources:

Figure 7 Slope map obtained from the DSM raster image.
Finally, this raster image that represents the slope isconverted into point data, where the point value is the slope
in percent. Then this point layer is aggregated into the blocklayer, given to each block an average of the slope. Themap showing the slope in the block is shown in Figure 8.

Figure 8 Percent slope integrated in the block layer.
As it can be seen those blocks that are on the hillside
have been identify in red and orange color. Those blocks
are settled in a land with an important slope that may
produce slides in case of an earthquake and therefore people
may be affected by this disaster.
6.

CONCLUSIONSThe social vulnerability is very related with the social
condition of the people.
It has been identified the location of low income people
in the hillside that may produce a big loss in case ofoccurrence of an earthquake.
This proposed methodology may be used to makeprevention plans to mitigate the effects of an earthquake.
Acknowledgements:
The authors would like to express their sincere gratitude to theJapan Science and Technology Agency (JST) Japan International
Cooperation Agency (JICA) under the SATREPS project“Enhancement of Earthquake and Tsunami Disaster Mitigation
Technology in Peru”.

Figure 6 Integration of cadastral information, high resolution
satellite image and digital surface model.
Next step is to calculate the percent of slope or gradientof the terrain in the study area. This is carried out bycomparing the rate change of pixel values of the DSM image
in the horizontal and vertical directions (ArcGIS Slope tool).

References:
Instituto Nacional de Estadística e Informática (2007), “CensosNacionales 2007” INEI, Lima, Peru
Estrada, M., Miura, H., Yamazaki, F. and Midorikawa, S. (2012)“Evaluation of Social Seismic Vulnerability through High
Resolution Satellite Imagery” Proceedings of the 15th World
Conference on Earthquake Engineering
Yamazaki, F., et. al (2012) “Progress of JST-JICA Project on
Earthquake and Tsunami Disaster Mitigation in Peru”
Proceedings of the 15th World Conference on Earthquake
Engineering.

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