remote sensing for natural disaster management

8/8/2019 Remote Sensing for Natural Disaster Management

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Remote Sensing for Natural Disaster Management

Brian Shiro

Department of Space Studies, University of North Dakota, Grand Forks, ND 58202, USA

December 17, 2008

Introduction

Natural disasters pose serious threats to lives and property. The United Nations

International Strategy on Disaster Reduction (ISDR) defines a disaster as a serious disruption of

the functioning of a community or a society causing widespread human, material, economic or

environmental losses which exceed the ability of the affected community or society to cope using

its own resources (UN 2008). The relationship between a place's likelihood to have a disastrous

event (hazard) and the community's ability to cope with it (vulnerability) is its disaster risk. Risk

is directly related to hazard and vulnerability according to risk= hazardvulnerability. Since

hazards themselves cannot be controlled, disaster managers focus on reducing vulnerability.

Vulnerability can include socio-economic, physical or environmental factors such as poverty,

land use, and water quality. Risk can be reduced through hazard monitoring, vulnerability/risk

analysis, education/training of people, application of policies encouraging proper urban growth,

and early warning systems for the hazard itself (UN 2008).

Developing countries are hit harder by disasters due to their increased vulnerability

compared to developed countries. Lack of infrastructure, especially the internet, impedes data

dissemination and use in developing countries. Developing countries also often have problems

enforcing policies or laws meant to reduce vulnerability to the population. Since they sometimes

don't have the money or political strength to mitigate disasters themselves, poorer countries tend

to rely heavily upon external international aid agencies to help them after disasters happen

(George 2000). Over 60% of all major natural disasters occur in developing countries, which are particularly vulnerable to these hazards due to their primarily agrarian economies and high

population densities in coastal areas (Jayaraman et al. 1997). Although developed countries

sustain more economic damage from natural disasters, 94% of all people killed by disasters earn

low income, as is the case in most developing nations (NatCatSERVICE 2006).


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Disaster management involves a whole host of activities ranging from pre-disaster

planning, warning and response to the event, immediate post-disaster support, and longer term

inter-disaster recovery and preparedness. Space based systems provide valuable inputs for all

stages of the disaster cycle (Jayaraman et al. 1997). Remote sensing information is used by

policy makers, emergency managers, first responders, aid agencies, and scientists to make

decisions. There are generally two spheres of activity in this regard. Most of the pre-and post-

event activities involve using remote sensing data along with socioeconomic and other

information to form synoptic comprehensive risk assessments for pre-disaster planning and for

mapping the effects of an event for post-disaster response. The other major way remote sensing

information is used is for early warning, which is using real or near-real time data to rapidly

detect, characterize, and disseminate information on the event to protect lives and property.

Figure 1: The Disaster Management Cycle

Disasters have characteristic spatial and temporal scales, and this determined the

requisite remote sensing spatial and temporal resolution required to adequately monitor them.

Figure 2 illustrates this concept for many types of disasters (Iglseder et al. 1995). There are three

main groupings: short-term, medium-term, and long-term. Short-term events can happen in

minutes and include earthquakes, landslides, tsunamis, and fires. Medium-term events usually


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give us a few days or weeks of warning and include floods, hurricanes, and volcanic eruptions.

Long-term events span years and require greater political diligence to mitigate; these include

hazards such as global warming, desertification, and groundwater depletion. This paper will

primarily summarize the role of space-based remote sensing in short-term natural disaster

response and the international bodies that support information dissemination to developing

countries.

Applications

Many types of disasters benefit from multiple types of remotely-sensed information in

different spectral and spatial bands. This can include both active and passive types of sensors.

Examples of active sensors include synthetic aperture radars, altimeters, scatterometers,

precipitation radars, and cloud profile radars (Huneycutt 2007). Examples of these sensor types

and some applications are given in Tables 1 and 2.


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Table 1: Active spaceborne sensor characteristics (adapted from Huneycutt 2007)

Table 2 (next page): Passive spaceborne sensor characteristics (vonDeak 2007)

SAR Altimeter Scatterometer Precipitation

Radar

Cloud Radar

Viewing

Geometry

Side-looking

@20-55 deg offnadir

Nadir-looking Two conical

scanning beamsabout nadir

Nadir-looking Nadir-looking

Footprint/

Dynamics

(1) Fixed to one

side

(2) ScanSAR

Fixed at nadir Scanning in

azimuth

Scanning across

nadir track

Fixed at nadir

Typical

swath width

500 km max

(Radarsat)

26 km (Jason) 1800 km

(SeaWinds)

220 km (TRMM) 1-2 km

(Cloudsat)

Typical

altitude

790 km

(Radarsat)

1336 km (Jason) 803 km

(SeaWinds)

350 km (TRMM) 705 km

(Cloudsat)

Typical

inclination

98.5 deg

(Radarsat)

66 deg (Jason) 98.2 deg

(SeaWinds)

35 deg (TRMM) 98.2 deg

(Cloudsat)

Antenna

Beam

Fan beam Pencil beam Pencil beams Pencil beam Pencil beam

RadiatedPeak Power

5000 W(Radarsat)

8-25 W (Jason) 110W (SeaWinds) 600 W (TRMM) 1700 W(Cloudsat)

Waveform Linear FM pulses Linear FM

pulses

Linear FM pulses Short pulses Short pulses

Spectrum

Width

50 MHz

(Radarsat)

320 MHz

(Jason)

375 kHz

(SeaWinds)

0.6 MHz

(TRMM)

300 kHz

(Cloudsat)

Spatial

Resolution

100m x 100m

(Radarsat)

0.5m x 5km

with 1-2 cm

accuracy over

5km circle of

ocean (Jason)

6km x 25km

(SeaWinds)

250m x 4.3km

(TRMM)

500m x 1.5km

(Cloudsat)

Key

spectrum

bands

0.432-0.438 GHz

1.215-1.3 GHz

3.1-3.3 GHz5.25-5.57 GHz

8.55-8.65 GHz

9.5-9.8 GHz

3.1-3.3 GHz

5.25-5.57 GHz

8.55-8.65 GHz9.5-9.8 GHz

13.25-13.75

GHz

35.5-36.0 GHz

5.25-5.57 GHz

8.55-8.65 GHz

9.5-9.8 GHz13.25-13.75 GHz

17.2-17.3 GHz

35.5-36.0 GHz

13.25-13.75 GHz

17.2-17.3 GHz

24.05-24.25 GHz35.5-36.0 GHz

94.0-94.1 GHz

133.5-134.0

GHz237.9-238.0

GHz

Disaster

Management

Applications

Flooding, oil

spills, volcanic

eruptions, severe

storms,

landslides, ice,

earthquakes,

fires, tsunami

Flooding,

drought,

hurricanes,

tsunamis

Flooding, severe

storms, drought,

hurricanes, ice

Hurricanes, severe

storms

Hurricanes,

severe storms


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Earthquakes

Today, remote sensing data is not used much for earthquake detection and hazard

mitigation. GPS networks measuring ground deformation are becoming increasingly important,

and InSAR (interferometric synthetic aperture radar) can provide large regional, spatially

continuous views of an area with great accuracy (Tralli et al. 2005). If a SAR satellite in the

right place at the right, it is possible to produce rapid earthquake land deformation maps in near

real time. However, there aren't enough SAR satellites yet to do so, despite recommendations

from top scientists (NASA 2002; NRC 2004). Earthquakes may also have an effect on the

ionosphere due to the coupled gravity waves they emit into the atmosphere (Bleier and Freund

2005; Balasis and Mandea 2007). Satellite magnetometers can detect these signals before the

earthquake happens. In 2003, a company called Quakefinder launched QuakeSat-I to detect

these ELF magnetic signals, and they plan to launch their second satellite QuakeSat-II this year

(QuakeFinder 2008). There is a promising future for earthquake hazard mitigation using space-

based sensors. During the pre- and post-disaster phases, satellite imagery of all types is useful

for earthquake vulnerability analysis and damage assessment (Alparslan et al. 2008).

Tsunamis

Tsunamis can be generated by anything that moves a large volume of water in a short

amount of time such as an underwater earthquake, landslide, or volcanic eruption that shifts the

sea floor. The early warning part of tsunami hazard management currently relies upon sparse in

situ measurements of sea level and computer models to characterize the tsunami waves, but the

future for space-based detection and monitoring of tsunamis with satellite altimetry is promising.

For example, radar altimeters on board the Jason-1, TOPEX, Envisat, and GFO satellites

measured the 26 December 2004 tsunami as it crossed the Indian Ocean (Smith et al. 2005), but

the sparse data took several hours to collect and days to process. We need a constellation of

satellites with altimeters to make this technology useful for future tsunami warning. Surrey

Satellite Technology in the UK proposed a 24-satellite constellation of altimeters, but the

mission was never funded (Allan 2005). Today, remote sensing is heavily used during the pre-

and post-disaster phases to characterize land cover (Wood 2008) and morphology changes

(Shrestha et al. 2005).


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Figure 3: Jason-1 detection of the 26 December 2004 Tsunami (NOAA)

Landslides

Landslides are common hazards since they are associated with heavy rain or flood events.

Earthquakes or human-induced land cover changes such as vegetation removal and erosion can

trigger landslides too. Many types of remote sensing data are useful for finding past landslides,

predicting where future ones might occur. This includes measurements to characterize the land's

geomorphology (topography, slope), it's soil properties (moisture, strength), and of course land

cover data to see the landslides (e.g., optical, TM) (Tralli et al. 2005). This requires high spatial

and temporal resolution data in order to provide the rapid land change analyses needed for

warning purposes (Chadwick et al. 2005).


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Volcanoes

Unlike earthquakes or tsunamis, volcanoes usually give some warning before they erupt.

This can include observable surface deformation due to subsurface magma movements

(detectable with GPS or InSAR), gas and ash emissions (detectable with hyperspectral imaging),

temperature changes (detectable with infrared), and of course increased seismic activity (Tralli et

al. 2005). Thus, remote sensing, combined with in situ measurements does a pretty good job at

mitigating volcanic hazards. RS also allows for detailed mapping of predicted or actual lave

flow areas (Baldi et al. 2005), and it is crucial to aviation safety since ash clouds from volcanoes

are very dangerous to planes.

Other Hazards

Other natural disasters such as fires (Arroyo et al. 2008), hurricanes (Atlas et al. 2005),

and flooding (Tralli et al. 2005) are also extremely important but are not treated in this paper.

International Cooperation

Although remote sensing data can be critical to stakeholders in the disaster management

process, it is not always routinely available in a timely manner in useful formats or actionable

informational products. There are gaps that need addressing if remote sensing is to play a critical

role to those affected by natural disasters, especially in developing countries. In recent years, a

number of international groups and agreements governing the sharing of remote sensing data for

disaster mitigation have emerged to address these shortcomings. They are very much focused on

meeting the needs of developing countries. For recent reviews of these efforts, see Baueret al.

(2006) and Withee et al. (2004).

The International Charter on Space and Major Disasters is an international agreement

signed by 10 space agencies to make satellite resources and data available without delay during

period of crisis, beyond the specific data policy restrictions of providers (Bessis et al. 2003;

Bessis et al. 2004). The idea is to provide emergency responders with coordinated and free

access to space systems and data in the wake of a disaster. The Charter has been activated 179

times since it went into force in 2000, with 76% of the activations in developing countries

(Charter 2008). Figure 4 illustrates the different types of disasters that have comprised these


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activations of the charter. It is a major success story of international cooperation and is the first

step towards establishing a global earth observation information service (Ito 2005).

Figure 4: Activations of the International Charter by disaster type

The second major international agreement related to natural disasters is the 1998

Tampere Convention on the Provision of Telecommunication Resources for Disaster Mitigation

and Relief Operations (Tampere Convention) (Tampere 1998). It calls on its 75 member states

to provide or facilitate prompt telecommunication assistance to mitigate the impact of a disaster

and temporarily waives regulatory barriers that could impede these efforts. This is the only

legally binding international treaty related to disaster management, which came into force after

the 30th country ratified the treaty in January 2005. It also includes provisions to specifically

help developing countries use the information they receive in this manner, including active and

passive space-based remote sensing data.

The Global Earth Observation System of Systems (GEOSS) represents the latest and

most inclusive effort to coordinate and improve interoperability of earth observation systems.

Built upon existing efforts such as CEOS (Barbosa et al. 2001; CEOS 2003), GMES (GMES


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2008), and IGOS (IGOS 2007), GEOSS is coordinated by the ad-hoc inter-governmental group

known as GEO (Group on Earth Observations), which is comprised of 58 countries and 43

international organizations (GEO 2008). It has a 10-year implementation plan (begun in 2005) to

implement the GEOSS plan (Ohlemacher 2003; Christian 2005; Lautenbacher 2006). GEOSS is

user-focused with nine major themes including disaster management. GEOSS, while not a

binding international agreement, overlaps with other existing programs like the International

Charter on Space and Major Disasters (Macauley 2005). In fact, GEOSS plans to expand the

scope of the International Charter to encompass not only post-disaster response but also pre-

disaster forecasting and "now-casting.

The idea behind GEOSS is to assimilate earth observation data with earth system models

to generate predictions and analyses that can guide policy makers in decision-making. One way

this will be accomplished is by creating open and common data exchange formats and making

data freely available. GEONETCast is meant to the main data dissemination system for GEOSS.

GEONETCast will be a near real time, global network of satellite-based data dissemination

systems designed to distribute space-based, air-borne and in situ data, metadata and products to

diverse communities (GEONETCast 2008). GEOSS has recognized the special challenge with

developing countries' lack of access to data due to poor technical infrastructure and is taking

measures to address them.

Beyond the Tampere Convention, the United Nations is involved in other efforts related

to remote sensing and disaster management. UNOSAT is an program for delivering satellite

information to relief and development organizations to help with early warning, crisis response,

sustainable recovery, vulnerability reduction, and capacity building (UNOSAT 2008). Since its

start in 2003, UNOSAT has been activated 102 times for various types of natural disasters that

follow a distribution that bears a striking resemblance to that of the International Charter

activations seen in Figure 4. In 2006, the UN General Assembly established the United Nations

Platform for Space-based Information for Disaster Management and Emergency Response (UN-

SPIDER) to ensure that all countries and regional and international organizations have access to

and develop the capacity to use all types of space-based information to support the full disaster

management cycle (UN-SPIDER 2008). Most of its activities involve capacity-building and

institutional strengthening in developing countries.


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Other organizations provide satellite data to developing countries struck by natural

disasters. Some of these programs include the Center for International Disaster Information (run

by USAID), SERVIR (regional for Latin America), Sentinel-Asia (regional for Asia), and the

Pacific Disaster Center (regional for Pacific). These organizations all have websites boasting

one-stop shops of earth observation data relevant to their respective missions.

The Future of Satellite Constellations

If successful, GEOSS will create a "virtual constellations" of satellites in which disparate

operators agree to share data in a consistent way. However, the existing satellite coverage

provides too sparse spatial and temporal coverage for mitigating short-term hazards like

earthquakes or tsunamis. Thus, dedicated constellations consisting of small, low cost satellites

with a particular mission goal will provide the next leap in disaster management capability

(Iglseder et al. 1995; Tobias et al. 2000).

This is already starting to happen with the Disaster Monitoring Constellation (Curiel et al.

2005), which consists of 5 optical satellites operated by 5 nations (4 of which are developing

countries). COSMO-SkyMed is an Italian constellation of 4 SAR satellites that is just one

launch away from completing its network (COSMO-SkyMed 2008). Chinas Huan Jing

Constellation will consist of 11 visible, infrared, multi-spectral, and SAR satellites; so far, two

have been launched (ChinaView 2008). Canada is also planning a future 3-satellite SAR

constellation.

There is another very exciting development undergoing rapid development. Iridium is

poised to replace it's aging constellation of 66 LEO satellites with new ones in the coming few

years. Recognizing the value of hazard mitigation and monitoring, they have agreed to host

remote sensing payloads to create a global real-time constellation with both high spatial and

temporal resolution. Iridium is cooperating with GEOSS to form a public-private partnership

that will not only fill critical data voids; it will only cost a fraction of a typical conventional

mission (see Figure 5). The plan so far is to include 24 altimeters, 12 GPS occultation, 6 optical

imagers, and 24 radiometers (Thoma 2008). This will provide unprecedented sampling for

"now-casting" and disaster early warning. Applications include sea level monitoring (and

tsunamis), tracking extreme weather events, land cover change (fires, desertification, crops,


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fisheries), ocean color, just to name a few. Launches are set in the 2013-2016 timeframe with a

15+ year mission lifetime.

Figure 5: Iridium NEXT cost savings compared to stand-alone missions

Conclusion

Natural disasters know no national boundaries, so it is imperative that we develop

technical- and policy-based solutions that allow for egalitarian access to remote sensinginformation in order to reduce the impact disasters have on human life, property, and the natural

environment. The Outer Space Treaty says that the use of outer space shall be carried out for the

benefit and in the interests of all countries and shall be the province of all mankind. However,

states are generally concerned with the export of uncontrolled technology and the sharing of

sensitive data due to national security imperatives. Initiatives such as the International Charter,

Tampere Convention, and GEOSS are making strides in bridging this nationalistic divide to

provide timely free remote sensing data for humanitarian purposes to those who need it. These

types of programs especially critical for developing countries that may not have their own

domestic earth observation or disaster management programs. Disaster management

encompasses a whole cycle from pre-planning, early warning, to response and recovery, and

remote sensing has important roles to play at all stages of the cycle.


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