Tools and Methods for Estimating Populations at Risk from Natural Disasters and Complex Humanitarian Crises (2007) / Chapter Skim
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3 Data Dissonance in Disasters
3 Data Dissonance in Disasters
Pages 72-108
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From page 72... ...
Without appropriate demographic data, responders have difficulty setting short-term priorities, allocating scarce resources efficiently, or establishing strategic plans for longer-term recovery efforts. This chapter addresses the dissonance created by the existence of detailed local demographic data and the data vacuum that appears in the midst of most disasters.
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From page 73... ...
The common theme is that in all four scenarios, the existing population and spatial data were underutilized, making the disaster response less effective and ultimately worsening the plight of victims. The Izmit, Turkey Earthquake, 1999 Turkey is in a seismically active region affected by the northward collision of the Arabian plate with the Eurasian plate along the Anatolian fault system, which is more than 900 kilometers long (Figure 3.1)
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From page 74... ...
FIgURE 3.1 Location of major earthquakes in Turkey along the North Anatolian Fault prior to the 1999 Izmit earthquake. SOURCE: Adapted from USGS, http://quake.wr.usgs.gov/research/geology/turkey/images/turkey_loc.gif.
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From page 75... ...
While personal locators and handheld GPS devices, or potentially, cell phones, for individual responders or the general public may be part of the future in some countries or specific communities, current technologies and population survey methods are still challenged by the issue of collecting demographic data when people are forced to migrate in response to a disaster. This issue is also explored in the section below on Hurricane Katrina and has been the topic of an earlier National Research Council report (NRC, 2001)
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From page 76... ...
FIgURE 3.2 Status map of affected population and infrastructure on November 3, 2005. SOURCE: OCHA Humanitarian Information Centre Pakistan (HICP)
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From page 77... ...
These circumstances exacerbated the demographic and geospatial data dissonance that occurred at the time of the crisis. Pakistan has a population of 165 million, which is 66 percent rural.
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From page 78... ...
Therefore, up-to-date, local area demographic data were available in these countries when the tsunami struck. In India, the national statistical office (NSO)
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From page 79... ...
FIgURE 3.3 Impact area of the 2004 South Asian tsunami. SOURCE: International Coordination Group for the Tsunami Warning System in the Pacific (http://ioc3.unesco.org/itic/)
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From page 80... ...
0 toolS aND MethoDS foR eStIMatING populatIoNS at RISk FIgURE 3.4 The top satellite picture of Kalutara, Sri Lanka, was taken about an hour after the first tsunami wave hit on December 26, 2004. Water is rushing back out to sea after inundating the land.
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From page 81... ...
. Ultimately, the numbers of people who were killed or affected were reconstructed through interviews of survivors, but these numbers lacked the support that could have been provided from pre-existing demographic data.
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From page 82... ...
2 toolS aND MethoDS foR eStIMatING populatIoNS at RISk FIgURE 3.5 Hand-drawn maps of Kameswaram village, derived from information collected from villagers by aid responders (Subramanian, 2006)
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From page 83... ...
3 Data DISSoNaNCe IN DISaSteRS assessments of the condition and numbers of the affected population relied on handdrawn maps in this region. This map contains not only subnational, but villagespecific, population data relevant to assistance providers and demonstrates that adequate aid does not necessarily require advanced technology -- rather advanced technology requires appropriate and timely input of data.
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From page 84... ...
As demonstrated in the preceding examples, the underutilization of existing demographic data in a crisis is not necessarily a function of having too few data, too little money, or a lack of local and international response to help disaster victims. Data dissonance -- or the lack of coordination between existing demographic and geospatial data sets and their accessibility and use by responders -- is rather a function of several features of the data themselves and the operations of the institutional structures employing the data.
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From page 85... ...
Out-of-Date Data Census demographic data are the most detailed data available for local areas, and the age of the data is one important aspect of evaluating how likely population determinations derived from the data are to represent the present-day, local situation. Nonetheless, age is not the sole criterion on
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From page 86... ...
Sources: FEMA; Census Bureau; Queens College Sociology Department FIgURE 3.6 Gross counts and Jodi Wilgoren/The New York Times people subsequent to Hurricane Katrina showing their widespread geographic Matthew Ericson, Archie Tse of internally displaced distribution and impact outside the immediately affected Gulf Coast region. Hurricane Katrina became the costliest natural disaster in U.S.
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From page 87... ...
. Simple algorithms to estimate these intercensal changes are rarely employed in pre-disaster preparedness or post-disaster response situations but would greatly improve data accuracy and usefulness in the event of a disaster response situation and could also be used for other types of normal development and planning programs in education, health care and housing.
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From page 88... ...
Some of the inaccessibility of the data occurs because the demographic data and the geographic boundary files are so voluminous that they overwhelm the transmitting systems (Bagiire, 2006)
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From page 89... ...
. CHANgES NEEDED TO MAkE EXISTINg DEMOgRAPHIC DATA ACCESSIbLE TO DECISION MAkERS In order to make the existing demographic data more useful in responding to disasters several steps would have to be taken: • Update local-area census data routinely (at least every five years)
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From page 90... ...
If the data are not presented in a form for rapid and accurate decision making, they would not be used no matter how good they are. This realization is as important for pre-disaster demographic data as for post-disaster data.
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From page 91... ...
For example, spatial analysis of demographic data can help identify regions in which a particular event or need is concentrated. Information can be presented spatially by area-based rates, which can help guide the disaster response by tar geting geographic areas (e.g., visually displaying unmet needs or reported service access)
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From page 92... ...
However, the cost of the equipment and software to generate these types of analyses, as well as the requirements for detailed local data and analytical training, may be prohibitive for many countries or local communities. Therefore, the feasibility and relevance of these sophisticated techniques for a disaster situation depend heavily on FIgURE 3.7 The three-dimensional scatter plot of GeoDa can be used to examine the relationship among three area-based variables and their spatial manifestation, dynamically linked with a map (see Anselin, 2004)
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From page 93... ...
Adopt a Principle of Minimally Essential Data Sets The pre-disaster demographic data provide a baseline to assess the human impact of the disaster, but the pre-disaster data themselves cannot provide an assessment of the post-disaster impacts. Each disaster leaves its own unique footprint on the population and the landscape.
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From page 94... ...
Surprisingly little attention has been devoted to defining minimum standards for demographic data collection, develop ing methodologies and tools for rapid demographic assessment, and improving population estimates. The need for population data collection depends greatly on the geographical region, the capacity of the host country, the type of emergency, and the scope of the response.
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From page 95... ...
; most disaster responses will also require spatial information on settlements and their power grids, alternative sources of power, gas stations, and backup systems.
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From page 96... ...
, the United Nations, and Environmental Systems Research Institute (ESRI) , are surveying the international disaster response community for the kinds of data they need at different stages of a disaster.
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From page 97... ...
and other disaster response entities. Increasingly, the practice is to make census boundaries available, usually through collection of a fee, because the "business model" for producing these data has been one of cost recovery, either for the total investment or on an on-demand basis for a particular data product.
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From page 98... ...
at CIESIN, Columbia University, which serves simply as an example of the architecture; this particular gateway currently serves gridded demographic data but not population data associated with finely resolved subnational units. Data Availability Simply sharing existing population data is admirable but may be insufficient if disaster management is to be effective.
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From page 99... ...
1 South Africa <1 1 1,217,645 Enumeration Area 83125 43,309 2 Guam 2 1 546 Block Group 203 155 3 Slovenia 2 0 20,224 Settlement 5989 1,988 4 Malta 2 6 315 Locality 67 390 5 Macao 3 142 19 Peninsula/Island 3 444 6 Maldives 3 13 189 Atoll 21 291 7 Malawi 3 1 94,958 Enumeration Area 9219 11,308 8 Mauritius 3 6 1,993 Municipal Ward/ 186 1,161 Village Council Area 9 Netherland 3 2 818 Geozone 71 215 Antilles 10 United States 3 3 374 Blocks 32 121 Virgin Islands 11 Czech Republic 4 2 78,616 Obec 6258 10,272 12 Switzerland 4 2 38,975 Commune 2912 7,170 (continued on next page)
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From page 100... ...
100 TAbLE 3.1 continued Population Number of Population Resolution per Unit (in Area Administrative Administrative (in thousands) Country (km)
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From page 101... ...
The paper discussing the development of the model referenced the Homeland Security, Defense-Intelligence, and Transportation Data Models are potential references for the structure of the HDM. SOURCE: http://www.humanitariangis.com/?
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From page 102... ...
Geospatial data standards that facilitate data sharing and interoperability need to be developed and adopted long before disasters occur. In addition, there are several important considerations when establishing the database or information system for emergency response (Goodchild, 2003b)
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From page 103... ...
Training is not free, but it need not be expensive if it is integrated into the job requirements of those who will be expected to use data during a disaster. Demographic data training is essential for basic disaster management competency and is also important
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From page 104... ...
One of the obstacles to the full employment of spatial demographic data during disasters, despite the clear need to do so, is the pressing human resource issue. Responding to disasters and humanitarian crises requires shared geographic and demographic thinking and training.
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From page 105... ...
To improve the effectiveness of response, the integration of spatial data and demographic data would be most useful prior to the disaster, not afterward. The development of MEDS to provide the baseline for preparedness and response is one avenue for reducing the demographic dissonance that plagues so many responders to disasters.
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From page 106... ...
Identify ways in which sub-national demographic and geographic data and tools could be used to help decision makers provide useful information to populations at risk. In National Research Council, tools and Methods for estimating populations at Risk from Natural Disasters and Complex humanitarian Crises.
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From page 107... ...
Geospatial data in emergencies.
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From page 108... ...
United Nations; presentation to the committee at a workshop held on March 13-14 at the National Academies Keck Center, Washington, D.C. Presentation available through the National Academies Public Access Records Office.
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