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1520 IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, VOL. 45, NO. 6, JUNE 2007
Satellite Image Analysis for Disaster
and Crisis-Management Support
Stefan Voigt, Thomas Kemper, Torsten Riedlinger, Ralph Kiefl, Klaas Scholte, and Harald Mehl
Abstract—This paper describes how multisource satellite data
and efficient image analysis may successfully be used to con-
duct rapid-mapping tasks in the domain of disaster and crisis-
management support. The German Aerospace Center (DLR) has
set up a dedicated crosscutting service, which is the so-called
“Center for satellite-based Crisis Information” (ZKI), to facil-
itate the use of its Earth-observation capacities in the service
of national and international response to major disaster situa-
tions, humanitarian relief efforts, and civil security issues. This
paper describes successful rapid satellite mapping campaigns
supporting disaster relief and demonstrates how this technology
can be used for civilian crisis-management purposes. During the
last years, various international coordination bodies were estab-
lished, improving the disaster-response-related cooperation within
the Earth-observation community worldwide. DLR/ZKI operates
in this context, closely networking with public authorities (civil
security), nongovernmental organizations (humanitarian relief
organizations), satellite operators, and other space agencies. This
paper reflects on several of these international activities, such as
the International Charter Space and Major Disasters, describes
mapping procedures, and reports on rapid-mapping experiences
gained during various disaster-response applications. The example
cases presented cover rapid impact assessment after the Indian
Ocean Tsunami, forest fires mapping for Portugal, earthquake-
damage assessment for Pakistan, and landslide extent mapping
for the Philippines.
Index Terms—Crisis information, disaster monitoring, rapid
mapping, risk management, satellite remote sensing.
I. IN TRO DU CT IO N
IN RECENT years, satellite systems and image-analysis
techniques have developed to an extent where civil and
commercial Earth-observation instruments can contribute sig-
nificantly to support the management of major technical and
natural disasters, as well as humanitarian crisis situations. Com-
paring today’s availability of satellite imagery to the situation
about ten years ago, the amount, timeliness, and availability of
satellite imagery covering a certain crisis situation or disaster
Manuscript received February 26, 2006; revised December 27, 2006. This
work was supported in part by the research and development grants of the
German Aerospace Agency (DLR), by the project funds of the Global Mon-
itoring for Environment and Security (GMES) program of the European Space
Agency, namely the RESPOND and RISK-EOS projects, and by research
funding granted within the 6th Research Framework Program of the European
Commission for the Network of Excellence “Global Monitoring for Stability
and Security” (GMOSS).
The authors are with the German Remote Sensing Data Center (DFD),
German Aerospace Center (DLR) at Oberpfaffenhofen, 82234 Wessling,
Germany (e-mail: stefan.voigt@dlr.de).
Color versions of one or more figures in this paper are available online at
http://ieeexplore.ieee.org.
Digital Object Identifier 10.1109/TGRS.2007.895830
event has improved substantially. There are several factors
which have lead to this fact. First of all, ground pixel spacing
of civil Earth-observation systems has developed to the meter
domain for optical and radar systems and to the decameter
domain for thermal imaging satellites. Second, during the
1990s, communication, networking, and interoperability among
the different satellite systems have improved substantially to
facilitate international satellite-based disaster-response capac-
ities. Third, through a number of international scientific and
technical coordination bodies, international cooperation mech-
anisms were established, such as the Disaster Management
Support Group (DMSG) of the International Committee on
Earth Observing Satellites or the International Charter Space
and Major Disasters. The main task of the DMSG is to per-
ceive the specifications, basic observations, and monitoring
requirements of current and future observing systems fully or
partially dedicated to disaster management tasks. Based on con-
clusions of the DMSG [1] and the UNISPACE III conference,
the International Charter Space and Major Disasters [2], from
here onwards referred to as International Charter, was founded
in 1999. Since this time, the International Charter has been
providing a crucial mechanism for globally coordinated disaster
response by civilian governmental satellite operators and space
agencies for natural and man-made disasters.
Currently, the International Charter is operated by a num-
ber of space agencies (Table I) and has been activated over
100 times (July 2006, [2]), providing meaningful mapping and
analysis products to the civil-protection and relief organizations
at appropriate scale in time and space. Taking into account
the increasing rate of natural and technological disaster situa-
tions affecting human activities on this planet, the International
Charter still bares potential for extension and improvement.
First of all, the commitment to provide only plain satellite
imagery, rather than analysis results, should be extended to also
formally committing the provision of ready to use information
products (maps) applicable in the domain of humanitarian
and natural crisis situations. Second, the speed of data and
information delivery may still be improved in the context of
the Charter, as natural, humanitarian or technical disaster often
cannot be predicted in space and time and thus requires max-
imum responsiveness to maximize mitigation efforts. Third,
the actors in the domain of satellite-based response to civilian
crisis and disaster situations may improve their mutual coordi-
nation and cooperation to allow best use of existing systems
and mechanisms and to exploit their synergistic potential to
the maximum level possible. Such coordination shall address
technical and organizational matters, as well as information
sharing or capacity building.
0196-2892/$25.00 © 2007 IEEE
VOIGT et al.: SATELLITE IMAGE ANALYSIS FOR DISASTER AND CRISIS-MANAGEMENT SUPPORT 1521
TABLE I
OVE RVIE W OF SPAC E AGEN CI ES AND SPACE RE SOU RC ES O F TH E INTE RNATI ONA L CHA RTER
After several years of research and development in the
domain using satellite systems for civilian crisis and disaster
response, the German Aerospace Center (DLR) has set up a
dedicated crosscutting service, the Center for satellite-based
Crisis Information (ZKI), to combine and facilitate the use of
its Earth-observation capacities in the service of national and
international response to major disaster situations, humanitar-
ian relief efforts, or civil security issues. The aim of this paper
is to describe and discuss the assessment of multiple satellite
data sources, the crisis support service cycle, the multisource
image analysis, and adding of the geospatial context to satellite
information in order to rapidly supply self-explaining geospa-
tial information products for disaster and crisis-management
support.
II. AC CE SS IN G MULTI PL E SATELLITE DATA SOU RC ES
Maps, geospatial information, and thematic analysis derived
from satellite imagery can support decision making and situa-
tion awareness during all phases of the disaster and crisis cycle.
This is defined through preparedness, alertness, rapid analy-
sis, response, recovery, and reconstruction [3]. In particular,
during the analysis, response, and recovery phase, only very
fast delivery of up-to-date, accurate, and comprehensive image-
analysis products can significantly help in the assessment of
large disaster situations, in particular in remote areas, where
other means of assessment or mapping either fail or are of
insufficient quality. Before the formation of the International
Charter, it was mainly by chance or in very special cases where
programming, access, delivery, and analysis of civil satellite
imagery was fast enough so that a response time of hours or
a few days was reached and allowed a proper use for relief-
work purposes. Only with the installation of the International
Charter, a globally functioning mechanism was established
to coordinate the tasking of multiple satellites and archiving
systems in very short time, without hindering formalities.
Hence, a meaningful satellite observation information capacity
was established for a variety of nonexpert users such as civil
protection, humanitarian relief workers, and donor/funding
organizations.
Shortly after the International Charter was introduced, very
high resolution (VHR) commercial satellite imaging in the
1-m domain became publicly available. Also, this 1-m domain
imagery allowed nonexperts in many situations to read informa-
tion intuitively from the carefully processed imagery itself or to
allow the analysts to generate fast and easy-to-read space maps
showing location, situation, scale, or extent of a given disaster
or crisis situation. In spite of these crucial developments in the
domain of satellite imagery provision, it is important to note
that no decision maker or relief worker can work with raw
satellite imagery—it always takes a very careful processing,
analysis, mapping, and interpretation process to generate the
required situation maps, reports, or statistics which can be
read and understood by nonsatellite expert users. It has to be
mentioned that the International Charter still has quite some
shortcomings in this respect as it formally only commits to
provide raw satellite imagery to the users. All analysis and
value adding work has to be conducted in other frame works
and contexts such as described next.
III. CR IS IS SU PP ORT SE RVICE CYCLE
In order to process the full cycle, from an emergency call
or request for assistance, through satellite tasking, data ac-
quisition, analysis, map provision, and interpretation, one has
to go through a chain of various steps involving coordination
of satellite commanding and data reception tasks, as well as
data ingestion, preprocessing, correction, and analysis. Just as
important as the data processing and delivery is the close con-
tact and interaction with the key actors in the user community
(Fig. 1) [4].
Experience over the past years has shown that neither sophis-
ticated image analysis and processing nor mapping capacities
or geographic information system (GIS) skills alone allow
providing a meaningful disaster-related information service to
crisis response staff and within operational scenarios. Only if
it is possible to operate the whole crisis support service cycle,
linking Earth-observation systems, information extraction, and
dissemination with specifically trained decision makers, or field
staff of the relief organizations without interrupt, space-based
crisis mapping can have a positive impact on disaster-relief
operations.
IV. MULTISOURCE IM AGE ANALYSIS
Satellite image analysis for disaster and crisis-management
support has to rely on whatever geoinformation is available
1522 IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, VOL. 45, NO. 6, JUNE 2007
Fig. 1. DLR-ZKI service cycle. ZKI touches both the space segment and
decision-maker cycles, and due to this interlinking network, it is possible to
provide optimal service delivery to its users.
fast in order to respond as quickly as possible. Moreover,
for each disaster type, different data and analysis techniques
are required. Consequently, a wide expertise and capacity for
various types of data is essential. The most important data
sources are VHR optical data, thermal imagery, and synthetic
aperture radar (SAR) systems.
Optical data are of great importance for disaster management
support such as planning the logistics of relief actions in the
field immediately after, for example, an earthquake or tsunami
[5]. One major advantage of VHR optical data is that their
interpretation is also intuitive for nonexperts. For example, a
map at scale 1 : 7500 using predisaster VHR imagery gives the
aid workers in the field an overview of the predisaster building
structure. Such information is highly valuable to search and
rescue operations, as well as for reconstruction planning after
earthquakes.
The thermal imagery offers excellent possibilities for map-
ping of hot spots caused by wild fires. Operational wild-
fire-detection systems using Advanced Very High Resolution
Radiometer (AVHRR) data have been developed for use in
Canada [6] and Finland [7], among other countries. Thermal
satellite data can give an overview information about the ex-
tent and the number of actually burning fires due to the fact
that the sensors of the National Oceanic and Atmospheric
Administration (NOAA) AVHRR and Moderate Resolution
Imaging Spectroradiometer (MODIS) are sensitive to fires that
are much smaller than their spatial resolution [8]. In partic-
ular, the MODIS sensor is also useful for large-scale flood
monitoring [9].
Although most of the commercial or research Earth-
observation satellite systems are optical/thermal systems, the
SAR systems onboard European Remote Sensing satellites
(ERS), Radarsat, ENVISAT, or the Advanced Land Observing
Satellite (ALOS) are of great value for the fast response map-
ping and analysis tasks as they allow imaging at wavelengths
almost unaffected by atmospheric disturbances such as rain
or cloud. Although radar imagery is somewhat less intuitive
to be interpreted by nonexperts, they resemble a very useful
source for flood events [6], [10], oil spills [11], landslides, and
earthquakes [12], particularly when postevent imagery can be
jointly analyzed with archived reference imagery for change
detection or interferometric coherence or displacement mea-
surements. The German TerraSAR-X System and the Italian
Cosmo-Skymed, which are to be launched in 2007, will extend
the civilian SAR availability to the 1-m domain, allowing VHR
all weather image acquisitions.
For many disaster-related image analysis and mapping tasks,
the availability of appropriate and accurate topographic eleva-
tion data on the affected area is of uttermost importance. Thus,
interferometrically derived digital elevation models (DEMs),
such as which resulted from the Shuttle Radar Topogra-
phy Mission (SRTM) [13], are of very high value for im-
age processing (e.g., orthorectification) and map generation
(e.g., hillshading).
V. ADDING THE GEOSPATIAL CONTEXT
It is evident that satellite-derived information alone does not
suffice to generate a meaningful analysis of a given disaster
situation. Experiences gathered during the work with relief
organizations show that it is an absolute key to fuse the satellite-
based information with additional data to present it in a proper
geospatial context. Thus, in addition to the expertise in image
analysis, an equally important task is the generation of compre-
hensive and easy-to-use map products. For this purpose, refer-
ence data sets such as place names, road network, rivers, critical
infrastructure, and topographic information are required.
The most crucial problem is the availability and the access to
accurate and up-to-date spatial data, particularly in remote re-
gions. The benefits of interoperable spatial data infrastructures
(SDI) for data access and dissemination in the framework of
disaster response are already demonstrated [14]. This promising
approach implies that different organizations provide the data
that they are responsible for by web-based systems. However,
up to the present, only few countries established and operate
an SDI; this is particularly the case for Africa and the Asian-
Pacific countries due to technical or legal constraints [15].
Therefore, there is still a gap in the availability, particularly of
local-scale geodata.
Fast and easy accessible global data sets such VMap [16]
are often not accurate enough for a high-resolution mapping.
Hence, high-resolution data sets on infrastructure and settle-
ment boundaries have to be derived by visual interpretation
of satellite imagery. Global gazetteers such as the GEOnet
Names Server [17] can be used for labeling settlements and
physiographical features like rivers and mountains. For a rough
estimation of the population affected by a disaster, the Land-
Scan database [18] gives a good representation of rural and
urban population densities. A combination of interferometri-
cally derived DEMs from SRTM X- and C-band, ERS, and
GLOBE 30-arcsecond data [19] provides a global basis for the
derivation of contour lines as an adequate representation of the
topography.
Generally, the map-generation process consists of different
steps: integration of spatial data, data analysis, layout, quality
control, map editing, and dissemination, as well as possible
VOIGT et al.: SATELLITE IMAGE ANALYSIS FOR DISASTER AND CRISIS-MANAGEMENT SUPPORT 1523
Fig. 2. High-resolution satellite map from new and archived satellite imagery of the northern Khao Lak Region, Thailand (1: 12.500). The archived predisaster
and new acquired postdisaster satellite images allow easy and quantitative damage assessment by visual change detection. Tsunami-affected areas are delinated
using a red polygon signature, and in blue, the coastline before the tsunami is indicated.
updating of the map. The following section will show some
examples and in more detail how the rapid mapping can suc-
cessfully be accomplished.
VI. EX AM PL ES F OR AP PLYI NG SATELLITE-BASED
INF OR MATI ON I N DIS AS TE R REL IE F
Going back only for the last two years, several outstanding
examples can be given where satellite-based maps could pro-
vide information supporting international humanitarian relief
teams or domestic disaster-relief operations in very fast and
efficient ways. Four of the most prominent internationally
relevant application examples, on which DLR/ZKI has worked,
are described in the following section and cover disaster
situations in the following geographic regions: Southeast Asia
(Tsunami), Portugal (fire hot spots), Pakistan (earthquake),
and the Philippines (landslide). It is important to note that
the following examples of satellite imagery application for
disaster relief intend to showcase swift and synergistic use of
state-of-the-art processing techniques and rapid data access.
These rapid-mapping results could be achieved by building on
existing scientific results and long-term engineering experience
in the domain of satellite data processing. It is not indented to
report major generic methodological research results or method
comparison here.
A. Impact Assessment for the Indian Ocean Tsunami
In the early morning of December 26, 2004, a severe earth-
quake (30 km below sea level, magnitude 9) caused Tsunami
flood waves in the Indian Ocean, which struck the coastal
regions of Sumatra, Thailand, Sri Lanka, and southern India,
and killed more than 200 000 people. Due to the immense
extent of the affected coastal areas, the International Charter
was triggered three times for India, Sri Lanka, and Indonesia/
Thailand. After consultation and coordination with various
international partners, DLR/ZKI concentrated its activities on
Thailand and Indonesia. Until postdisaster imagery became
available, reference maps using archived satellite data were
produced giving first basic information about the affected areas.
These archived satellite data from the global land-cover facility
[20] were combined with geospatial information.
The first postdisaster images of Sumatra were delivered on
December 29, 2006, three days after the disaster. Due to the
scale of the damage, both medium [Landsat-7 Enhanced The-
matic Mapper (ETM), SPOT, disaster monitoring constellation
(DMC)] and very high-resolution imageries (IKONOS, Quick-
bird) were used for quantitative damage assessment mainly
by means of visual change detection (Fig. 2). This up-to-date
mapping, covering large parts of the affected area, enabled
disaster managers to achieve an overview of the situation, to
1524 IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, VOL. 45, NO. 6, JUNE 2007
Fig. 3. Satellite map of the Serra do Estrela, Portugal (1 :50.000). The image shows in red the area that burned until August 25, 2005, where the different colored
circles denote the MODIS-derived hot spots between August 14 (dark red), August 16 (red), August 17 (orange), and August 21 (yellow), allowing a detail tracing
of the fire propagation.
assess the damage, and to supply local logistic teams with
reliable information on a short notice. ZKI provided this ser-
vice in cooperation with its partners in the Global Monitor-
ing for Environment and Security/RESPOND consortium and
followed requests of the crisis reaction team of Germany’s
Federal Foreign Office (Auswärtiges Amt), the joint federal
situation and information center, the German technical relief
agency, the German Red Cross, and Medicines Sans Frontiers.
The products were also provided to a wide international user
community, as well as the press and the public via the Internet.
B. Providing an Overview on Forest Fires in Portugal
In the Mediterranean, each summer, natural- and human-
induced wildfires are a threat not only to the environment but
also to the local population. In the year 2005, after one of the
most severe droughts over the Iberian Peninsula, the wildfires
were raging out of control across central and northern Portugal,
killing 15 people and destroying more than 150 000 ha of
agricultural land and urban area.
The worst-hit areas included the central region of Portugal,
where fires were threatening the outskirts of Coimbra, which
is the third largest city of the country. Wildfires were also con-
tinuing to burn in the northern districts of Viseu and Viana do
Castelo. After a request of the Portuguese fire-fighting service,
the International Charter was triggered, and the burned area was
mapped using SPOT, Landsat-7 ETM, DMC, and IKONOS.
The burned area was mapped from visual image comparison
of pre- and postdisaster data, as it proofed to be faster and more
accurate than automated classification tools. Due to the large
areas that were affected, medium resolution satellites such as
SPOT-5, Landsat-7 ETM, and DMC proofed to be more ad-
vantageous over the very high-resolution IKONOS data, which
were used only for the affected urban areas.
In parallel, the situation was monitored using the sensors
NOAA-AVHRR 17 and MODIS Aqua and Terra for the de-
tection of fire hot spots. Near-real time hot-spot detection for
the Mediterranean is achieved at DLR through an inhouse
reception of NOAA AVHRR and MODIS data and direct
processing. This processing chain is based on the adapted
APOLLO tool for NOAA AVHRR [21] and the enhanced
MODIS fire detection developed by [22]. The value-added
product was delivered daily, 2 to 5 h after the satellite over-
pass via the Internet and for direct integration into GISs
of the civil-protection units. This continuous monitoring al-
lowed a detailed tracing of the fire propagation and a better
planning of fire-fighting capacities by the Portuguese civil
protection (Fig. 3).
VOIGT et al.: SATELLITE IMAGE ANALYSIS FOR DISASTER AND CRISIS-MANAGEMENT SUPPORT 1525
Fig. 4. Damage assessment for the northern Muzaffarabad city area, Muzaffarabad District, Pakistan (1 : 7500). Visual interpretation on pre- and postdisaster
images with 250 ×250 m grid cells is applied to interpret damage to infrastructure and build-up areas by means of UN housing damage classification: no damage,
moderately damage (<33%), severely damage (33%–66%), and completely destroyed (>66%). Semitransparent color map overlay is used to visualize damages,
and blue-colored grid cells show those areas with moderate (light blue) to high (dark blue) damage to infrastructure, whereas the orange- and red-colored grid
cells show damage to build-up areas.
C. Earthquake Relief Support for Pakistan
A series of severe earthquakes (maximum magnitude of 7.6)
struck the Kashmir region on Saturday October 8, 2005. The
epicenter was located on the India–Pakistan border, which is
about 100-km northeast of Islamabad, and Pakistani authori-
ties reported some 49 700 casualties and over 74 000 injured.
On October 11, which is two days after activation of the
International Charter, DLR produced several detailed maps
(1 : 7500) of a number of cities in the earthquake-affected
region, which are derived from very high-resolution IKONOS
imagery. Typical image preprocessing for such rapid-mapping
services includes atmospheric corrections [23], orthorectifica-
tion [24], pansharpening [25], filtering, contrast enhancements,
and visualization.
The positional accuracy of uncorrected VHR imagery is poor
in mountainous areas such as the Kashmir region, and therefore,
VHR imagery requires orthorectification before application
in high-resolution earthquake-damage (change) mapping. The
initial positional accuracy of about 300 to 1000 m, which
was acquired with 15◦–30◦off-nadir viewing angles [26],
was improved to about 3–5 m to meet the CE90 accuracy
requirement [27].
However, since rapid mapping often places very difficult time
constraints on production, time-consuming processes such as a
full sophisticated atmospheric correction [23] are only applied
when crucial for the image analysis and interpretation process.
This is because the emphasis in rapid mapping is primarily
on visual interpretation rather than on automated extraction of
quantified environmental variables.
Damage assessment is an important task within the frame-
work of rapid mapping, and there are almost unlimited ap-
plications of change analysis [5]. However, standard change
analyses are not always suitable for VHR, e.g., object-based
classification is very time demanding (up to 30 h or more)
and not as straightforward as the more conventional Bayesian
methods. Change analysis using polygons of varying size and
type is a very time-consuming approach, as the identification
of homogeneous image sections is a very difficult and time-
consuming task. SAR imagery may be used for assessing
damages to houses and buildings [28]; however, depending
on the type of damage and the type of structures affected,
results may also be limited. Another common approach is to
visualize change analysis through color coding by means of the
predisaster image, e.g., in green, and the postdisaster image,
e.g., in red. Hence, an image combination by superimposing
the different colors (color additive mixing process) will then
reveal unchanged properties in yellow. This method requires
very accurate image coregistration and does not allow intuitive
reading by the user.
Therefore, a new damage-assessment method was tested for
the city of Muzaffarabad (Fig. 4) using visual interpretation on
pre- and postdisaster images with 250 ×250 m grid cells. This
method, which was proposed by the European Joint Research
Center team working on the satellite-based disaster-response
efforts, interprets damage to infrastructure and build-up areas
for each grid cell by means of the UN housing damage classifi-
cation [29]: no damage, moderately damage (<33%), severely
damage (33%–66%), and completely destroyed (>66%). The
method uses semitransparent color map overlay to visualize
damages (Fig. 4) where blue-colored grid cells show those
areas with moderate (light blue) to high (dark blue) damage to
infrastructure whereas the orange- and red-colored grid cells
1526 IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, VOL. 45, NO. 6, JUNE 2007
Fig. 5. Crisis map at a scale of 1 : 25 000 of the landslide-affected area around Guinsaugon, Saint Bernard, Southern Leyte Island, Philippines. The backdrop
image shows a predisaster SPOT5 image, and the landslide extent was derived from a number of different sensors: Radarsat, ASAR, and ALOS AVNIR-2.
show damage to build-up areas. If enough time is available,
map overlay with critical infrastructure information (bridges,
airports, tunnels, ports, hospitals, clinics, and schools) should
be generated.
According to the users’ feedback, the maps and layers
(streets, damage, etc.) yield vital information with respect to
evacuation planning, general “pathfinding/tracking,” to get a
better overview and understanding of problems on site. In
addition, the maps proved very useful for negotiations about
logistics and joint operation among relief organizations in the
field.
D. Mapping a Devastating Landslide in the Philippines
On Friday, February 17, 2006, a landslide triggered by
heavy rains buried the village of Guinsaugon, Saint Bernard,
Southern Leyte Island, Philippines. Most of the approximately
300 houses and the elementary school were fully covered by
the mudslide, affecting the 1411 village inhabitants (including
246 elementary school pupils and 7 teachers) at the time of the
incident.
The crisis map at a scale of 1 : 25 000 of the landslide-
affected area uses a predisaster SPOT5 image, which was
acquired on June 1, 2003, as image backdrop. Image process-
ing carried out includes atmospheric correction [23] and the
generation of a synthetic blue channel (to provide a true color
image to the map users), orthorectification by means of direct
georeferencing of SPOT HRS stereo data [30], [31], and image
enhancement such as stretching and filtering. VMAP level 0
yielded input as the main gazetteer information source, whereas
Google Earth and Microsoft Encarta provided additional infor-
mation where the VMAP data were missing or inaccurate.
The landslide extent was derived and crosschecked from
a number of different satellite sensors: Radarsat, Advanced
Synthetic Apperture Radar (ASAR), and ALOS Advanced
Visible and Near-Infrared Radiometer (AVNIR)-2. Geocoding
of the radar imagery is carried out using a geocoding system
developed by DLR [32]–[34], which supports Envisat-ASAR,
ERS, J-ERS, Radarsat-1, SIR-C / X-SAR, and TerraSAR-X.
The pixel spacing of the in- and output data, as well as the
Doppler reference function, are parameterized and are stored in
configuration files used by the system. The geocoding product
is “enhanced” ellipsoid corrected, which means that the product
is projected and resampled to UTM using WGS-84 geodetic
reference, and terrain-induced distortions are corrected
considering a DEM. The geometric quality of the product is
good, due to the height accuracy and resolution of the used
SRTM (C-band and X-SAR), ERS-derived elevation models,
and the GLOBE elevation information, in combination with
the type of terrain and the incidence angle. Even though most
SAR processors refer to zero Doppler, the geocoding system
is able to consider other reference functions. Multipolarized
data are considered as multilayer images. Hence, the landslide
extent was derived by means of on-screen digitizing.
The ALOS imagery from the Japanese Aerospace Explo-
ration Agency, which was launched on January 24, 2006,
VOIGT et al.: SATELLITE IMAGE ANALYSIS FOR DISASTER AND CRISIS-MANAGEMENT SUPPORT 1527
yielded optical data input; however, the sensor only partially
imaged the landslide due to partially cloudy weather situation.
Hence, accurate geocoding using the SPOT reference scene was
established, and again, the landslide extent could be derived by
means of on-screen digitizing.
The landslide mapping (Fig. 5) shows the potential of the
usage of a number of data sources (SPOT, SRTM, and ALOS)
for the benefit of humanitarian relief organizations.
VII. CO NC LU SI ON A ND OU TL OO K
Examples could be shown how multiple satellite image
processing and analysis techniques may successfully be applied
individually or in a combined manor to serve rapid-mapping
tasks in the domain of disaster and crisis-management support.
It can be concluded that no single commercial or research-
oriented satellite system alone can effectively provide and guar-
antee fast and reliably image access on archive or new postevent
imagery. Thus, effective and well-balanced coordination among
the different observing systems is required in order to allow
best service to the civil-protection and humanitarian relief
community. As military observing capacities are usually even
more efficient with respect to temporal coverage and spatial
resolution, it may be interesting to improve civilian–military
cooperation in this domain in the future. There is still a need for
an improvement of the availability of consistent, comparable,
and reliable high-resolution geospatial data. Initiatives to estab-
lish SDI can facilitate the access to reference data, as well as
the dissemination of rapid-mapping products. As discussed in
this paper, just as with the civil-protection work itself, effective
satellite-based disaster-relief efforts rely on international, inter-
disciplinary, and interorganizational cooperation mechanisms
and team work. The European Initiative in GMES provides an
important frame in this context.
ACK NOW LE DG ME NT
The authors would like to thank the various colleagues of
German Remote Sensing Data Center and DLR working in the
frame of ZKI, as well as all other national and international
institutions cooperating in the global disaster-relief efforts.
The authors would also like to thank all the colleagues and
institutions involved in the International Charter—Space and
Major Disasters and to the team of European Space Imag-
ing in Munich, Germany, and GeoEye for the rapid imagery
provision efforts. They would also like to thank D. Ehrlich,
C. Louvrier, and D. Khudhairy of the Joint Research Centre
for the excellent collaboration and for providing the grid-cell
damage-assessment procedure.
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Stefan Voigt received the M.Sc. degree in physi-
cal geography, physics, and remote sensing
from Ludwig-Maximilians-University, München,
Germany, in 1997, and the Ph.D. degree, working
on a European Commission research project on the
remote sensing and runoff/flood forecasting, from
Berne University, Berne, Switzerland, in 2000.
Since then, he has been with the German Re-
mote Sensing Data Center (DFD) of the German
Aerospace Center (DLR), Wessling, leading a
research team on “Crisis Information and Rapid
Mapping.” Furthermore, he is in charge of the scientific and operational
coordination of the DLR/DFD’s Center for satellite-based Crisis Information
(ZKI) which is contributing to several national and international activities
and projects in the field of disaster mitigation, humanitarian relief, as well as
civil security. Since 2001, he has been coordinating an international research
initiative on innovative technologies for detection prevention and monitoring
uncontrolled of coal seam fires in China.
Thomas Kemper was born in Wickede, Germany, in
1969. He received the degree in physical geography
and the Ph.D. degree from the University of Trier,
Trier, Germany, for his work on quantification of
heavy metals in soils using reflectance spectroscopy,
in 1997 and 2003, respectively.
From 1998 to 2004, he was with the Institute for
Environment and Sustainability of the Joint Research
Centre (JRC) in the context of soil degradation and
desertification. He joined the German Remote Sens-
ing Data Center of the German Aerospace Center in
October 2004 and is currently working in the Center for satellite-based Crisis
Information, Wessling, Germany.
Torsten Riedlinger received the M.Sc. degree in
physical geography, climatology, and soil science
from the University of Trier, Trier, Germany, in 1999.
From 2000 to 2003, he had a Ph.D. scholarship
on analyzing and modeling the landscape evolution
of a semiarid watershed in southeast Spain. Since the
spring of 2003, he has been working in the Center for
satellite-based Crisis Information at the German Re-
mote Sensing Data Center of the German Aerospace
Center (DLR), Wessling, Germany, including remote
sensing and geographic information system analysis,
as well as national and international coordination, related to man-made and
natural disasters, humanitarian relief, and civil security. Furthermore, he is
responsible for DLR’s project management within the International Charter
on Space and Major Disasters, and he is Project Manager for the German
Contribution to the Indian Ocean Tsunami Early Warning System.
Ralph Kiefl received the Diploma degree in physical
geography, with a major in geographic information
systems (GIS), from Johannes Gutenberg-University,
Mainz, Germany, in 2002.
Since April 2002, he has been working at the
German Remote Sensing Data Center of the German
Aerospace Center, Wessling, in projects for land-
cover classification. Since autumn 2003, his main
task has been the application of desktop and web-
based GIS in the context of satellite-based crisis
information.
Klaas Scholte received the M.Sc. degree in physical
geography from Utrecht University, Utrecht, The
Netherlands, in 1998, and the Ph.D. degree, focus-
ing on geologic applications by using hyperspectral
remote sensing, InSAR, and geophysical methods,
from the Delft University of Technology, Delft, The
Netherlands, in 2005.
He worked for two years with the International
Institute for Geo-Information Science and Earth Ob-
servation, The Netherlands, and JRC-Ispra, Italy,
on remote sensing methods for desertification and
vegetation monitoring. Since the autumn of 2005, he has been working with
the German Remote Sensing Data Center of the German Aerospace Center,
Wessling, in the context of the European Space Agency Global Monitoring
for Environment and Security Service Element RESPOND on satellite-based
information for humanitarian relief.
Harald Mehl received the Diploma degree in ge-
ography and the Ph.D. (Dr. rer nat) degree in re-
mote sensing from Ludwig-Maximilians-University
of Munich, Munich, Germany, in 1988 and 1991,
respectively.
He was a Senior Scientist with the Working Group
Remote Sensing at the Institute for Applied Geology
of the Ludwig-Maximilians-University of Munich:
organization and realization of research projects in
Latin America and South East Asia, in 1992–1996.
In 1996–1998, he was Head of the Executive Office
of German Aerospace Center Organization and Management. Since 1999, he
has been Head of the Unit Environment and Security of the German Remote
Sensing Data Center, Wessling, Germany: Management of the unit and defini-
tion of new application areas. His profile includes the following: Specialist in
remote sensing, geographic information system, geography, geology, and land
use, and Education Generalist in agriculture, forestry, soil science, cartography,
and hazards.
