primary applications of spatial analysis in humanitarian ... · • gis-based analysis falls into...

Primary Applications of Spatial Analysis in Humanitarian Emergencies

Firoz Verjee, D.Sc.

February 19, 2009

Session: Humanitarian Affairs, Global Health, and Food Security

ESRI Federal Users Conference 2009

Introduction• Systems-based assessment of how beneficial GIS-based

analysis is for coordinating humanitarian operations during UN-led interventions

• Humanitarian applications of GIS have, so far, been primarily cartographic, i.e. map making

• The coordination of humanitarian “clusters” requires information exchange and analysis to create situational awareness

• This research investigates what types of GIS-based analysis are helpful to decision makers in UN and non-UN agencies during the relief and recovery phases of an emergency

Literature Review• GIS-based analysis falls into six categories, excluding

cartography

• Scholarly research in GIS applications for humanitarian assistance has been sporadic and unsystematic

• Aside from Health applications, the tradition of peer-reviewed research in humanitarian applications of GIS is weak, although there are some signs of change

• Humanitarian community is weary of techno-centric solutions or any centralized approach which threatens its independence or autonomy

• A new school of thought in coordination is emerging, which abandons ICS idealism in favor of trust-based pragmatism

GIS Phenomena

Boundary Condition A: Limited to UN-led Interventions using the Clusters ApproachBoundary Condition B: Excludes Cartographic (i.e. map making) Applications of GIS

Queries & Measurements

Transformations

Optimization

Statistical Analysis

Geovisualization

Remote Sensing & GPS

Information Sharing

Data Models

Geospatial & Humanitarian Standards

Web-based GIS

Data Availability & Collection

Humanitarian ClustersCluster Coordination (UNOCHA)

Water & Sanitation (UNICEF)

Health (WHO)

Emergency Shelter (IFRC/UNHCR)

IT & Communication (UNICEF/WFP)

Logistics (WFP)

Camp Management (IOM/UNHCR)

Early Recovery & Reconstruction (UNDP)

Education (UNESCO)

Nutrition (UNICEF)

Livelihoods (FAO)

Protection (UNICEF/UNHCR/OHCHR)Education, Research & Training

Map Templates & Symbology

Hypothesis Testing & Simulation

Major Hypothesis & MethodNull: GIS-based analysis cannot have a decisive impact upon the

coordination of humanitarian assistance

Alternate: GIS-based analysis can have a decisive impact upon the coordination of humanitarian assistance

Method: Sequential Exploratory Mixed Method, involving:

1. Qualitative survey using expert interviews

2. Design of representative examples of most promising types of GIS-based analysis

3. Quantitative survey of humanitarian decision makers

Phase 1: Expert Interviews• A total of 40 interviews, averaging 57.5 minutes each and

conducted primarily by phone

• Research subjects selected because of their familiarity with humanitarian coordination and/or application of GIS applications, as well as their ability to reflect the humanitarian community at-large

• Subjects provided with a review of the study’s objectives and clarification that their responses would be de-identified

• Researcher then began open-ended interview technique geared towards the subject’s specific area(s) of expertise

• Nevertheless, standard questions such as, “What types of GIS products or services does (or would) your organization use during humanitarian emergencies?” were asked of all those interviewed

Phase 1: Expert InterviewsType of Organization Name of Organization Country

Government Donor United States Agency for International Development, Office for Foreign Disaster Assistance (USAID/OFDA)

USA

Department for International Development (DFID) UK

National Government United States Geological Survey, Department of the Interior (USGS) USA

Humanitarian Information Unit, Department of State (HIU) USA

Federal Emergency Management Agency, Department of Homeland Security (FEMA/DHS)

USA

Private Sector/Vendor ESRI USA

Academia/Research Institute for Crisis, Disaster & Risk Management, The George Washington University (ICDRM)

USA

American Association for the Advancement of Science (AAAS) USA

Association of American Geographers (AAG) USA

Institute for the Study of International Migration, Georgetown University (ISIM)

USA

Virginia Polytechnic Institute (Virginia Tech) USA

Lahore University of Management Sciences (RISEPAK/LUMS) Pakistan

Type of Organization

Name of Organization Country

International Organizations

United Nations Joint Logistics Center, World Food Programme (UNJLC) Italy

United Nations Office for the Coordination of Humanitarian Affairs (UN OCHA)

USA, Switzerland & Israel / Occupied Palestinian Territories

Food and Agriculture Organization of the United Nations (FAO) Italy

United Nations High Commissioner for Refugees (UNHCR) Lebanon & Switzerland

United Nations Children’s Fund (UNICEF) USA

United Nations Department of Peacekeeping Operations (UN DPKO) USA

World Health Organization (WHO) Switzerland

United Nations Development Programme (UNDP) Haiti

United Nations System Influenza Coordination, United Nations Development Group

USA

The World Bank USA

Non-Governmental Organizations

FOCUS Humanitarian Assistance USA & Pakistan

Veterans for America USA

Mercy Corps USA

Oxfam UK

MapAction UK

World Vision USA

Phase 1: Conclusions• Gap Analysis is the most urgent priority in humanitarian

coordination – irrespective of whether GIS is employed to calculate the difference between Assessed Needs and Relief Activities

• Situational awareness will only be possible by improved data sharing – field-level mechanisms to facilitate timely, no-hassle reporting are crucial to the ultimate success of GIS-based analysis

• GIS must be advocated with caution – it must provide unique and decisive intelligence, that is simple, easily-comprehendible, reliably reproducible, and field-tested.

Priority List of GIS-based AnalysesCategory Suggested Application

Queries & Measurements 1. Gap Analysis: Calculation of actual or percentage of relief needs met over time2. Measurement: Computation of distance or area of various lines or polygons of interest3. Range Analysis: Determine population within or beyond some distance of certain

humanitarian services4. Zone Analysis: Calculate total relief capacity within a certain area, and/or compliance

with humanitarian standards

Transformations 5. Vulnerability Estimation: Anticipate most vulnerable populations based upon proximity to hazard(s) and distance from relief distribution infrastructure

6. Site Selection: Identify potential locations for humanitarian services given certain terrain, land use and proximity criteria

Optimizations 7. Service Optimization: Determine best locations for humanitarian services given a transportation network

8. Route Optimization: Calculate the shortest or fastest route between two or more locations

Geostatistics 9. Central Feature Analysis: Compute the most central (i.e. median) point amongst a set of points

10. Exact Center Analysis (Weighted): Compute the centre of a set of weighted points (i.e. mean)

11. Cluster Analysis: Detect the correlation of a set of points with one another, andunderlying phenomena

Geovisualization 12. Orientation & Situation Reporting: Communicate the response environment and humanitarian activity through Geovisualization

Hypothesis Testing 13. “What If?” Analysis: Simulate the impact of a change to one or more variables that affect humanitarian operations

Phase 2: Web Survey

Phase 2: Web Survey• A total of 156 qualified survey respondents, averaging 24 minutes to

complete the 28 questions

• A total of 3,200 individuals invited response rate of 5.4%

• Subjects first provided with a review of the study’s objectives and assurances that their responses would be de-identified and aggregated

• Questions 1-6 captured basic demographic about the respondents

• Questions 7-13 gauged their views and comprehension of GIS

• Questions 14-27 elicited their opinion of the 13 priority applications

• Question 28 calibrated and cross-checked their utility rankings

Phase 2: Web Survey Participants • Affiliation: 1/3 from international NGOs, 1/3 from UN agencies

• Roles: 50% Program Managers or Technicians

• Base: 30% USA, 15% Pakistan, 8% Sudan + 32 other countries

• Focus: #1 South Asia, #2 Sub-Saharan Africa, #3 Middle East

• Cluster: #1 ERR, #2 Livelihoods, #3 Coordination

• Experience: 40% (< 5 years), 49% (5-15 years), 11% (>15 years)

• GIS Expectations: 59% (Optimistic), 37% (Curious), 6% (Cautious) & 2% (Skeptical)

Phase 2: Web Survey Participants

Poor Basic Good ExcellentUnderstanding of GIS

0

10

20

30

40

50

60

# of

Res

pond

ents

9.6 % %

26.3 %

34.0 % %

30.1 % %

None Basic Intermediate Advanced ExpertLevel of GIS Training

0

10

20

30

40

50

# of

Res

pond

ents 17.9 % %

32.1 %

21.2 % %

14.1 % %14.7 % %

Phase 2: Web Survey

Utility Assessment of the 13 types of GIS-based Analysis

Question 14: Gap Analysis (Single Cluster)

Population without Shelterbetween Week 1 – Week 8 for Neelum District

Week 1

Week 2

Week 3

Week 4Week 5

Wee

k 6

Wee

k 7

Week 8

0

20

40

60

80

100% Week 1

Week 2

Week 3

Week 4Week 5

Wee

k 6

Wee

k 7

Week 8

0

20

40

60

80

100% Week 1

Week 2

Week 3

Week 4Week 5

Wee

k 6

Wee

k 7

Week 8

0

20

40

60

80

100%

0

20

40

60

80

100%

Week 1

Week 2

Week 3

Week 4Week 5

Wee

k 6

Wee

k 7

Week 8

0

20

40

60

80

100% Week 1

Week 2

Week 3

Week 4Week 5

Wee

k 6

Wee

k 7

Week 8

0

20

40

60

80

100% Week 1

Week 2

Week 3

Week 4Week 5

Wee

k 6

Wee

k 7

Week 8

0

20

40

60

80

100%

0

20

40

60

80

100%

Week 1

Week 2

Week 3

Week 4Week 5

Wee

k 6

Wee

k 7

Week 8

0

20

40

60

80

100% Week 1

Week 2

Week 3

Week 4Week 5

Wee

k 6

Wee

k 7

Week 8

0

20

40

60

80

100% Week 1

Week 2

Week 3

Week 4Week 5

Wee

k 6

Wee

k 7

Week 8

0

20

40

60

80

100%

0

20

40

60

80

100%

Week 1

Week 2

Week 3

Week 4Week 5

Wee

k 6

Wee

k 7

Week 8

0

20

40

60

80

100% Week 1

Week 2

Week 3

Week 4Week 5

Wee

k 6

Wee

k 7

Week 8

0

20

40

60

80

100% Week 1

Week 2

Week 3

Week 4Week 5

Wee

k 6

Wee

k 7

Week 8

0

20

40

60

80

100%

0

20

40

60

80

100%

Diagram size represents # of People Affected

(Data for illustrative purposes only)

Week 1

Week 2

Week 3

Week 4Week 5

Wee

k 6

Wee

k 7

Week 8

<100

<500

<1000

<5000

<10000 Week 1

Week 2

Week 3

Week 4Week 5

Wee

k 6

Wee

k 7

Week 8

<100

<500

<1000

<5000

<10000

<100

<500

<1000

<5000

<10000

Number of People without ShelterRadius shows Gap remaining, where:

Gap = Assessed Need – Relief Distributed

Weeks after EarthquakeCircumference shows Time after the Emergency

Question 14: Gap Analysis (Multiple Clusters)


HealthProtectionLivelihoodsWat/San

Aug 1-15

Aug 15-31

Sep 1-15

Sep 15-30Oct 1-15

Oct 15-31

Nov 1-15

Nov 15-30

20

40

60

80

100% Aug 1-15

Aug 15-31

Sep 1-15

Sep 15-30Oct 1-15

Oct 15-31

Nov 1-15

Nov 15-30

20

40

60

80

100%

Aug 1-15

Aug 15-31

Sep 1-15

Sep 15-30Oct 1-15

Oct 15-31

Nov 1-15

Nov 15-30

20

40

60

80

100% Aug 1-15

Aug 15-31

Sep 1-15

Sep 15-30Oct 1-15

Oct 15-31

Nov 1-15

Nov 15-30

20

40

60

80

100%

Percentage of Gaps Remaining

Semi-monthly Reporting Period

Gap Analysis “Compared to existing methods of tracking the progress of

humanitarian response, how useful is this type of analysis to you?”

• 109 out of 156 respondents provided comments, ranging from “100x better than a list of needs” to “too complex for decision makers”

• The scale of examples should have been at the village-level

N/A8.3% Not useful

4.5%

Somewhat useful 28.2%

Essential 13.5%

Very useful 45.5%

Question 15: Range Analysis

20 km

# of Villages BEYOND one day walk to Clinic: 8=> Population needing Mobile Field Vaccination: 1,750

# of Villages WITHIN one day walk to Clinic: 10=> Population that can visit Clinic: 2,150

Range Analysis “The figure above shows how GIS can be used to calculate the

number of settlements (or schools, hospitals, people, etc.) within a certain distance of a vaccination clinic (or road, food distribution point, etc.). How useful is this type of analysis to you?”

• 110 out of 156 respondents provided comments, and suggested that the simplicity of Range Analysis was both good and bad

N/A5.1% Not useful

3.2%Essential 23.1% Somewhat

useful 17.3%

Very useful 51.3%

Zone of Interest (user defined)

Settlement Population: 4,800Communal Refuse PitsWater Tanks (total # of taps = 35)Latrine Sites (total # of toilets = 150)Security Zone (50km cordon)⇒ SPHERE Compliance for max. 3,000⇒ Extra Capacity Needed for 1,800


Question 16: Zone Analysis

Zone Analysis “The figure above shows how GIS can be used to calculate the total

relief capacity (and compliance with humanitarian standards) within a certain area. How useful is this type of analysis to you?”

• 90 out of 156 respondents provided comments, ranging from “Excellent for ensuring compliance with standards” to “SPHERE guidelines are only indicators and should not be considered out of context”

N/A9.6%

Not useful 3.8%


Essential 19.2%

Very useful 44.2%

Origin

Destination

Flying Distance (Helicopter) = 63 km

Driving Distance (Paved Roads): 135 kmDriving Distance (Gravel Roads): 20 km⇒Total Driving Distance: 155 km⇒Estimated Fuel (Return Trip): 40 litres

North Rd.Motorway

South Rd.

Main St.

Logging Rd.

Mosquito-breeding Swamps: 15 sq.kms.⇒Volume of Chemical Agent: 450 litres⇒Estimate Spraying Time: 3.5 hours

Question 17: Measurement

Measurement Analysis “Compared to existing methods of distance and areal measurement,

how useful is this type of analysis to you?”

• One of the most obvious and simplest types GIS-based analysis, particularly for logistics planning

• But is precise measurement outweighed by overall imprecision?

N/A16.7%

Not useful 7.1%


Essential 15.4%

Very useful 39.7%

Question 18: Vulnerability Estimation

Muzaffarabad (near epicentre)

Worst Affected Areas(30 km buffer around

quake faultine)

Areas far from main routes & local

capitals

Areas near district boundaries

Areas far from main routes & local

capitals, AND near district boundaries

+

=

Villages most vulnerable to being underserved by relief agencies:

1. Within Worst Affected Area (predicted)2. Far from main routes & capitals3. Near district boundaries

Vulnerability Estimation “Compared to existing methods of vulnerability estimation, how useful

is this type of analysis to you?”

• 95 out of 156 respondents provided enthusiastic comments, but stressed the need for accurate gazetteer as well as Who-What-Where data

N/A5.1%

Essential 23.1%

Not useful 0.6%


Very useful 51.3%

Question 19: Site Selection“GIS can be used to identify the best locations for campsites (or schools,

hospitals, helipads, etc.), based upon certain criteria such as water availability, land cover, accessibility, hazards, etc. In other words, by layering existing knowledge of land cover, terrain, hydrology and relief activities, it is possible to apply GIS-based analysis to optimize the locations for relief operations. How useful is this type of analysis to you?”

N/A4.5%

Essential 30.8%

Not useful 1.9%


Very useful 49.4%

Question 20: Service Optimization

Optimal Locations for Health, Educational & Financial Services

Clinics Service Goal: < 60 minutes from any village by Landcruiser (4x4)Schools Service Goal: <7.5 kms from any village by footBank Service Goal: Minimum Aggregate Travel time by bus

Main Town

VillagesMain RoadsSecondary RoadsTrails

Service Optimization “Compared to existing methods of selecting locations for humanitarian

services, how useful is this type of analysis to you?”

• 88 out of 156 respondents provided comments, and cautioned that local politics often dictates such decision making

N/A8.3%


Essential 18.6%

Not useful 2.6%

Very useful 48.7%

Question 21: Route Optimization“You may be familiar with Internet-based route planning services, which allow

the user to input an origin and destination and then obtain a turn-by-turn set of directions. When transportation networks are complex (or constantly changing), GIS-based analysis can quickly identify the shortest or fastest route between two or more locations. Compared to existing methods of navigation and route planning during humanitarian operations, how useful is this type of analysis to you?

N/A7.1% Not useful

7.7%


Essential 16.7%

Very useful 38.5%

Question 23: Exact Center Analysis (Weighted)

Most Central Village (unweighted)

(see Question 22)

Exact CenterIdeal location for a grain processing facility, if the same villagesare weighted according to total wheat production, and assumingthat modes of local travel are unknown.

Central Feature & Exact Center Analysis “The figures above shows how GIS can be used to calculate the most central

and the exact center amongst a set of points (weighted to reflect village populations, agricultural output, AIDS/HIV infection rates, etc.). Compared to existing methods, how useful are these type of analysis to you?”

• Two of three types of geostatistics tested in the survey

Not useful 20.5%

Very useful 21.8%

N/A12.8%


Essential 5.8%

Not useful 12.8%

Very useful 27.6%

N/A17.9%


Essential 7.1%

Question 22: Central Feature Analysis Question 23: Exact Center Analysis

Question 24: Cluster Analysis

Rebel attacks with a correlation to the village’s ethnic affiliation, considered statistically “clustered”.

Rebel attack without an identifiable pattern, considered statistically “random”.

Cluster Analysis “The figure above shows how GIS can be used to identify if a series of

features is correlated (i.e. clustered) with other phenomena. The purpose of cluster analysis is to determine if the distribution of a set of features is related or random, and to investigate cause-and-effect relationships. The most common applications of cluster analysis have been in epidemiology (detecting possible sources of disease outbreaks) and crime analysis (anticipating the location and tactics of criminals). How useful is this type of analysis to you ?”

Very useful 49.4%

N/A9.0%


Essential 18.6% Not useful

5.1%

Question 25: “What if?”Analysis

=

Snow Extent as of January 7, 2006Data for illustrative purposes only

Main Access Roads⇒Roads above 3,500 metres will probably be impassable after January 15, 2006

Villages bordering snow-level⇒These 21 villages in District A will need priority for blanket & tent distribution (total affected population: 7,500)

Epicentre

“What if?” Analysis • 75 out of 156 respondents provided comments, split between a

majority who felt it could be the most powerful type of analysis, and a minority who argued there was neither the time, data nor sophistication to conduct hypothesis testing and simulations during a crisis situation

Very useful 46.8%

N/A7.1%


Essential 17.9% Not useful

3.8%

Question 27: Geovisualization for Orientation & Situation Reporting

Object: Building Status = DestroyedSource = UNOSATConfidence = LowDate = Aug 14, 2006

Object: Road Status = Severe DamageSource = UNOSATConfidence = Very HighDate = Aug 14, 2006

Object = OrchardStatus = UXO Mine HazardSource = Local ResidentConfidence = MediumDate = Aug 12, 2006

Village = Tair Debba, LebanonStatus = Partially DisplacedSource = UNDPConfidence = HighDate = Aug 25, 2006

Note: Data for demonstrative purposes only.

Geovisualization “Compared to other methods of orientation and situation reporting,

how useful is this Geovisualization to you?”

• Unquestionably strong application but enthusiasm was tempered byvalid concerns about data reliability, Internet dependency & resolution

No, 15.4%

Yes, 84.6%

Very useful 52.9%

N/A4.6%


Essential 22.2%

Not useful 1.3%

Question 26: Are you familiar with Google Earth, MS Virtual Earth or ArcGIS Explorer?

Question 28: Top 5 Types of Analysis

• Without doubt, Gap Analysis had the highest relative utility amongst the 87 qualifying responses, followed by Vulnerability Estimation.

• Geovisualization, Cluster Analysis & Site Selection also ranked well

• Range Analysis had lowest variance, standard deviation and the second highest mode

Overall Analysis• This was a voluntary survey, and therefore the survey respondents

are representative of the population inclined to exploit GIS-based analysis. Broader extrapolation or inference was avoided, and not necessary to assess “utility”

• The benchmark for statistically determining “utility” is arbitrary: I defined this a being a clear majority (>55%) of the sample stating that a type of analysis was either “Very Useful” or “Essential”

Con

fiden

ceIn

terv

al

Total Population

Confidence Level = 95%

6%

7%

8%

500

9%

10%

5,000 100,000

Confidence Level = 99% Key Point: With a sample size (n) =156, the total population is not significant for determining utility, but it is for determining feasibility

Testing the Minor Alternative HypothesesCategory Suggested Application >55% Very Useful or Essential

Queries & Measurements 1. Gap Analysis2. Measurement3. Range Analysis4. Zone Analysis

YesYesYesYes

Transformations 5. Vulnerability Estimation6. Site Selection

YesYes

Optimizations 7. Service Optimization8. Route Optimization

YesYes

Geostatistics 9. Central Feature Analysis10. Exact Center Analysis (Weighted)11. Cluster Analysis

NoNoYes

Geovisualization 12. Orientation & Situation Reporting Yes

Hypothesis Testing 13. “What If?” Analysis Yes

“More than 55% of the statistically-representative sample population says that GIS-based analysis type x can have a decisive impact upon the coordination of humanitarian assistance, within a confidence level of 95% and interval of 7.15%”(calculated for a target population = 10,000)

At the 55% threshold, it is possible to conclude that GIS-based analysis can have a decisive impact upon the coordination of humanitarian assistance, but:

• The need for Gap Analysis seems indisputable, however the Phase 1 & 2 results were inconsistent and we cannot conclude that GIS-based analysis is critical

• More study is also required to determine the utility of “What if?”Analysis, since it is too complex to test with just one example

• Optimizations and Geostatistics may have limited utility and feasibility in typical humanitarian situations

Final Conclusions

GIS Tutorial for Humanitarian Assistance

ESRI Press, to be released end of 2009

Thank you

primary applications of spatial analysis in humanitarian ... · • gis-based analysis falls into...

Documents