Vg = Vulnerability value in each gridWi = Weight of parametersPgi = Parameters population in each gridFv/h = Parameters value

IntroductionIntroduction

Findings

Community experience on hazard and risk based from a participatory census in 14 villages in Sangihe Islands.

Attributes Data types

Demography Population based on :

Age and gender group, pregnant, senior, infant, toddler, disabilities (mental and

physical),

Houses Types :permanent /semi-permanent / temporary , stories, livestock, distance from

rivers, elevation, water supply.

Present of hazard Flood, flush flood, Volcano : cold lava, hot lava, pyroclastic , volcanic dust, Hurricane,

storm surge, whirlwind

Spatial X and Y position for each houses

X and Y position for each Infrastructure

Other spatial data : ASTER DEM, Topography, Landuse and geology base maps. Volcano hazard maps from Indonesian Geological Research and Study Agency.

Indonesia is an archipelago with enormous disaster potential, while Sangihe

Archipelago regency is one of the most disaster-prone regency in Indonesia. Unfortunately, awareness on the need of disaster management has just begun in the last decade. Major problem in disaster management in Indonesia is the lack of available data and information on specific area particularly in remote and the most hazardous area due to the lack of human and budget resources. While some resources such community experience still did not consider as credible data resources. This study is trying to fill the gap on data limitation by using community experience on disaster with GIS analysis to create hazard and vulnerability maps.

GIS Analysis on community experienceto Multi-hazard events in Sangihe ArchipelagoNorth Sulawesi - Indonesia

Community Hazards Index Maps

Rank, Score and Weight

Vulnerability Index

Hazard Index

Spatial vulnerability dataGrids level

Spatial vulnerability data Household

level

CommunityCensus

Data

Spatial Vulnerability Index Maps

Housescoordinate(Community Surveys)

Rank, Weight & Scoring

Spatial Aggregation- Creating data grids- Spatial Joint- Dissolving data into grids level (50x50 m)

Vulnerability Criteria(Infant, pregnant, female,

seniors toddlers, disabilities, etc)

Base mapsTopographyLanduse ASTER DEM

Community experience is one of the most important asset in the field particularly for remote area which have a lot of limitation on data availability and funds. This project is trying to capture the hazard and risky area and define vulnerable population distribution by using the demography characteristic and hazard impact experience from the community. There are some major factors that need to address for future discussion in participatory multi-hazard mapping, such as building the exact assumption for each hazard that corresponding to the local characteristic (geographical and cultural properties)..

Discussion

Study area is located in Sangihe Archipelago Regency, North Sulawesi Province - Indonesia.

The focus study area is on the northern part of the island, where there 14 villages that always

experienced the natural disasters and also location of an active volcano (Mount Awu, 4,330 ft)

Study sites : Sangihe Islands. North Sulawesi -Indonesia

Hazard and Vulnerability Index per each villages

UrbanElFatihBaniAdamGeography Graduate Student at University of Hawaii at Manoa.

PLAN 673 Information System for Human Disaster Managementand Humanitarian Assistance

No Perimeters Rank Score Weight Notes

Natural Disasters 4 8 53.33

Damage by Hot lava 8.89 Houses that damage by each

Damage by Cold Lava 8.89 types of hazards will given one

Damage by Earthquake 8.89 weight per hazards.

Damage by Flooding 8.89

Damage by Hurricane 8.89

Damage by whirlwind 8.89

Housing types 3 4 26.67

Permanent 1 1 2.42 Low risk

Semi permanent 2 4 9.70 Medium risk

Temporer 3 6 14.55 High risk

Stories 2 2 13.33

one 2 2 8.89 High risk

two 1 1 4.44 Low risk

Livestock 1 1 6.67

A

B

C

E

D

A

C

B

D E

* 1 grid cell (50 x 50 m) = 2500 m 2

Villages Area Population

Vulnerable

Population

(Ha) Low Medium High Low Medium High

Bahu 20.5 559 138 30 62 0 38 44 0

Beha 38 493 63 83 76 0 84 38 30

Bungalawang 24 1235 99 4 158 27 84 12 0

Kalakube 28.25 503 136 28 92 0 40 52 21

Kalurae 13 370 45 2 80 0 29 20 3

Kendahe 49.5 1788 296 77 156 0 120 42 36

Kolongan Beha 35.75 1202 345 3 176 18 55 70 18

Mahena 29.5 1077 141 6 160 42 82 30 6

Mala 31.25 743 183 3 146 12 39 68 18

Moade 11 348 26 13 50 3 32 6 6

Raku 13 262 45 18 40 0 25 24 3

Santiago 9.75 441 85 31 6 0 28 8 3

Utaurano 30.5 692 85 52 94 0 78 38 6

Vulnerable Population

Index (Grid Cell)

Hazard Index

(grid cell)

Villages

Lh-Lv Lh_Mv Lh_Hv Mh_Lv Mh_Mv Mh_Hv Hh_Lv Hh_Mv Hh-Hv

Bahu 17 13 21 9 0 0 0

Beha 59 15 8 25 4 2 0 0 0

Bungalawang 4 0 0 72 5 8 1 0

Kalakube 16 9 3 24 17 4 0 0 0

Kalurae 1 1 28 9 1 0 0 0

Kendahe 53 13 10 67 8 2 0 0 0

Kolongan Beha 2 0 1 50 32 5 3 3 0

Mahena 4 2 65 12 2 13 1 0

Mala 1 1 1 37 30 5 1 3 0

Moade 13 0 0 19 2 2 0 1 0

Raku 11 7 0 14 5 1 0 0 0

Santiago 26 4 1 2 0 0 0 0 0

Utaurano 41 10 1 37 9 1 0 0 0

Vulnerable population distribution in hazardous area (grid cells)

* Lh(low risk), Mh (Medium risk), Hh(High risk), Lv(low vulnerable ), Mv (medium vulnerable) Hv (High vulnerable).

2

P e rim e ters Rank Sc ore W e ig ht Notes

Fe m ale 1 2 4 .76 Ran k b as ed on th e c o nc e pt

D isab i li ties 2 4 9 .52 o f evac u at io n / e m erge nc y

Se n io r c itize n 3 6 14 .29 res po n se d u rin g th e d is aster

T o dd ler (1 -5 ye ars) 4 8 19 .05 eve n ts in term o f s pe ed , a cc es s

P re gna nt 5 1 0 23 .81 stren gh t, exp erien c e, ec t.

In van t 0 -1 2 m o nth ) 6 1 2 28 .57

BungalawangSantiago, Mahena

Kolongan Beha

Kendahe Bahu, Mala, Kalakube Beha, Moade, Raku,Utaurano, Kalure

Community Hazard Index

Vulnerability population distribution on risky area

Scientific ApproachScientific Approach

SiteSite

Data SourceData Source

Data processing and computationData processing and computation

Findings

Discussion

Rank, Score and Weight