Niger Vulnerability Map - March 2014 PURPOSE OF MAP: The purpose of the map is to identify "hot spots" of vulnerability based on a confluence of a wide variety of overlapping vulnerability indicators. Seeing where many relevant indicators overlap can allow one to begin to question causal relationships and underlying issues in particular zones . Hot spots identified in this map speak to the need for both further assessments (ground truthing) and multisectoral approaches to programming . Vulnerability is composed of a complexity of factors and no single intervention can create resilience. This map is primarily meant to be a thought piece to generate further discussions and the evolution of development programming.
Legend
Vulnerability Score
Value High: 100
Lack of Ada
Legend
Vulnerability Score Value
High : 100
tive Ca a cit
More Red=
Low: 0
% of Households Farm Landless
SOURCE: VVorld bank. 2011 livi ng ~tandards rr.easurement sun:ey (LSMS)
Soil Organic Carbon Density (proxy for soil fertility)
+
Y..b rlrl So illr1fmmalion , 2013
+
+
Lower Adaptive Capacity (less ability to adapt to shocks)
Population Count Distribution (general proxy for access to services)
SOURCE: Afripop 2015 Esiim~te
Tropical Livestock Units (TLU) Composite Index for Livestock Assets
+
SOURCE: World bank 201 1 1iving standards measurement sur,•ey (LSMS)
MoreRed= + Less Livestock Assets
% of Children who Passed CFEPD (End of primary school exam)
SOURCE: M inistry of Educa1icn Niger - 2013
More Red= Less% Children Passed
~ · .a.• I
Total Time Required to Get Water
SOURCE: Worlo;t bank. 2011 Irving staMaro;ts measurement su rvey (LSMS)
Poverty Rates by Region
__ __,,....--.., SOURCE: INSiMEF, OUIBB 2005 • Agadez & Diffa from 2004
More Red= Higher Poverty
+
Legend
Vulnerability Score by Commune Legend
MEAN
- 3 - 14
** Communes with vulnerability score > 55 have been labeled on map
- 15-22
23 - 28
0 29-35
CJ 36 - 42
CJ 43-49
D 50 - 55
- 56 - 60
- 61 - 67
- 68 - 88
Sensitivit
Vulnerability Score
Value High · 100
More Red=
Low: 0
Historic Zones of Undernutrition (SMART, Admissions as % of Pop)
*Double Weighting
.... ... HISTORIC Severe Acute Malnu1rition (SAM)
· Double 'J\Ie ighting
HISTORIC Severe Malnutrition Admissions as % of 1otal Pop. • Ooub :e weighting
HISTORIC Chronic Malnutrition Rates
+
More Sensitivity to future shocks
Conflict/Stability Composite Index +
HISTORIC Locations and Intensity Current Refugee Loc ations of Conflicts (ACLED Database) and by Count (UNHCR)
·Doub le 'JVeighting
+ % Head of Households having
Quranic Education
CVE Core and Non..core Communes (USAID- PDEV)
SOURCE: USAIO PDEV Program
More Red= .._ More USAID CVE work
Historical Zones of Food Insecurity (FEWSNET, SAP, WFP)
t ..
More Red= Higher Prediction of Food Insecurity
.. HISTORIC Food Insecurity
Outlook IPC Ratings (FEWSNET)
r-l i'::~~~;~~ - FEVVSNET _... · , 2009 - 2013
+ HISTORIC SAP (na tional early warning
sys1em) Vulnerable Communes
HISTORIC WFP % of Pop. Severely Food Insecure
+
Top 50 Vulnerable Communes COMMUNE REGION POPULATION
TAN OUT ZINOER 134074
ZINOER ZINOER 274530
GOUCHI ZINDER 47978
TENHIA ZINOER 21205
OUNGASS ZINOER 100431 GANGARA ZINOER 40796
FAlANKO ZINOER 4561
ALBER KARAM ZINOER 15414 TARKA ZINOER 89533 WAM E ZINOER 32695
DAMAGARAM TAKA YA ZINOER 46178
MOA ZINOER 26290
MALlAOUA ZINDER 67329
WACHA ZINOER 67334 DOGO OOGO ZINOER 42011
GADABEDJI M ARAOI 5328
OLLELEWA ZINOER 105167
DAKOUSSA ZINOER 54330
GOUDOUMAR IA DIFFA 102800 DOGO ZINDER 86306 TESKER ZIN OER 34641
GUIOIM OUNI ZINOER 54579
GAFFATI ZINOER 43097 ZERMOU ZINOER 24987
TCAOAOUA MA RADI 91507
ARLIT AGADEZ 112432 TIRMINI ZINDER 97247
TOU MOUR DIFFA 1336
MIRRIAH ZINOER 60805
OOUNGOU ZINOER 32081
BOSSO DIFFA 521 77 MAZAMNI ZINOER 8994
KO LERAM ZINOER 25978
HAM OARA ZINDER 32006
KANTCHE ZINDER 51333
GO UNA ZINDER 55666
TIBIRI MA RADI 114424 GANGARA MA RADI 40796
SASSOUMBROU M ZINOER 57166
AGAD EZ AGADEZ 124324
ALLAKOS ZINOE R 21279
KELLE ZINDER 62003 KO ROHANE MA RAOI 9551
MAIYARA MA RADI 56087
GARAGOUMSA ZINDER 64257 GUIDAN ROUMOJI MA RADI 88690
AGU IE MA RADI 142182 MAINE SOROA DIFFA 94074
NGUELBEYLI DIFFA 1413
ICHIRNAWA ZINOER 35045
USAID FROM THE AMERICAN PEOPLE
Basic Methodology:
Step 1: Define relevant i n d ic~tors of vu lnerability to use in analysis
Step 2 : Co nvert geographically disaggregated indicator data to raste r format
Step 3: Winsorize data where appropriat e based on histogra m CJna lysis
This is done to prevent data fro m being skewed by outlie r da ta.
Step 4: Rescale al l data sets to a common 0-JOO sca le so that they are compara ble.
Step 5 : Average composites of releva nt indicators. Use weight ine when
appropr iate based on expert judgment
Niger Border Countries and Population Distribution
Algeria
Niger
More Red= Less Population
Nigeria
Chad
African Republic
Ex osure
Legend
Vulnerability Score Value
High: 100
Low 0
• "S~ . .
•
More Red= More Exposure to Climate and Price Shocks
HISTORIC Frequency of Dry Spells (no rain for >=15 days during season)
HISTORIC Average Temperature (during rainy season, JJAS)
HISTORIC Coefficient of Variation of NDVI (variability of "greenness"- 2000 onwards) ~Doub l e weighting since cvNDVI is such a commonly
used dataset (as a proxy) for measuring rainfall va riabi lity
SOURCE: ARC2 - gridded da ily ra infa ll estimates (RFE) - 1994 to 2013
Higher Frequency of Dry Spells
+ SOURCE: Univero;ity of Eas\Angl ra's Climabc Research Un ite (UEA'CRU)- 2000 thru 2D 11
More Red= Higher Average Temperature +
SOURCE: MOD IS EVI 2000-2014 , SP.ctmd lmlf of Aug.
More variability in green (proxy for rainfall)
HISTORIC Millet Price Volatility (price shock)
HISTORIC Rainfall Variability (cvRFE)
+ SOURCI: : FI: '~'SNI:T
cvRFE 2001 - 2013
MoreRed= + Higher Rainfall Variability
T Double weighting to balance against large amount of climate shock data layers . This layer represents I he only PRICE SHOCK data layer
SOURCE: SIMA & USA!D FE\NS-NET, '•993-2012 {Mar~h )
More Red= Higher Millet Price Volatility
For more information contact: Jeremy Chevrier
Regional Geospatial Analyst Sahel Regional Offi ce
USAID/Senegal Email: [email protected]
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