Table Of Contents

Datasets

The data used in this course is available for download at data.inasafe.org. Ask your trainer what data you will need to download for the course, if it is not provided.

If you are working through the training independently, use the following data packages:

Hazard data

Flood Model

File name:

Jakarta_Flood_HKV_WGS84.tif
Training data:

A flood similar to the 2007 Jakarta event
Geometry:

Raster
Data Type:

Continuous
Scenario:

Single event
Unit:

metres
Source:

HKV
URL:

http://deltares.nl
Date:

2012
Licence:

Creative Commons by Attribution (CCbyA)
Coverage:

Jakarta
Description:

The flood model was created by scientists/engineers in coordination with DKI Jakarta Public Works based on the 2007 flood conditions. The water depth is the maximum depth occurring across the entire flooding period.
../../_images/005_data_flood_model.png

Flood Footprint

File name:

Jakarta_Flood_18113_WGS84.shp
Training data:

A flood in Jakarta like 2013
Geometry:

Polygon
Data Type:

Classified
Scenario:

Single event
Attribute field:

FLOODPRONE
Attribute value map:

Wet (Yes), Dry (No)
Source:

OSM and BPBD DKI Jakarta
Date:

18 January 2013
Licence:

Creative Commons by Attribution (CCbyA)
Coverage:

Jakarta
Description:

Along with sub-village boundaries that were mapped during the DKI mapping project, this dataset was used to identify flood areas based on information provided by the villages.
../../_images/005_data_flood_footprint.png

Earthquake

File name:

Padang_EQ_2009_WGS84.tif
Training data:

Earthquake in Padang 2009
Geometry:

Raster
Data type:

Continuous
Scenario:

Single event
Unit:

MMI
Source:

Badan Geologi and Australian Government
Date:

2012
Licence:

Creative Commons by Attribution (CCbyA)
Coverage:

Padang
Description:

A shakemap is a representation of ground shaking produced by an earthquake. This particular scenario was modelled on the 30th September 2009 Mw 7.9 earthquake in Padang. ShakeMaps are generated automatically following moderate and large earthquakes by USGS. For more information go to http://earthquake.usgs.gov/earthquakes/map/. Pre-event / scenario based shakemaps must be modelled by earthquake specialists.
../../_images/005_data_earthquake.png

Tsunami

File name:

Maumere_Tsunami_WGS84.tif
Training data:

Tsunami in Maumere (Mw 8.1)
Geometry:

Raster
Data type:

Continuous
Scenario:

Single event
Source:

Australian Government and Badan Geologi
Date:

2012
Licence:

Creative Commons by Attribution (CCbyA)
Coverage:

Maumere, Flores
Description:

In September 2011, the Indonesian government held a national exercise in Maumere, Flores. AIFDR and Australian Government assisted Badan Geology to develop a tsunami model for Maumere based on an Mw 8.1 earthquake. The Tsunami was modelled using open source software called ANUGA and elevation data from NEXTMap. The water depth is the maximum depth occurring across the entire tsunami event. For more information visit http://anuga.anu.edu.au/ and http://intermap.com/
../../_images/005_data_tsunami.png

Volcano

File name:

Sinabung_Hazard_Map_2015_WGS84.shp
Training data:

Sinabung Hazard Map
Geometry:

Polygon
Data type:

Classified
Scenario:

Multiple event
Attribute field:

KRB
Attribute value map:

Kawasan rawan bencana III - High; Kawasan rawan bencana II - Medium; Kawasan rawan bencana I - Low
Source:

PVMBG
URL:

http://vsi.esdm.go.id/gallery/picture.php?/63/category/7 (published map)
Date:

2015
Licence:
Coverage:

Sinabung
Description:

This map contains information about the hazard level for each zone. It can be used to identify the potential impact.
../../_images/005_data_volcano_hazard.png

Volcano Point

File name:

Sinabung_Mount_WGS84.shp
Training data:

Sinabung Mt
Geometry:

Point
Data type:

Classified
Scenario:

Multiple event
Attribute field:

Name
Attribute value:

Sinabung
Source:

PVMBG
URL:

http://vsi.esdm.go.id/gallery/picture.php?/63/category/7 (publish map)
Date:

2015
Licence:
Coverage:

Sinabung
Description:

The data shows the location of Mount Sinabung peak.
../../_images/005_data_volcano_sinabung.png

Volcanic Ash

File name:

Sinabung_Volcanic_Ash_1Feb14_WGS84.shp
Training data:

Sinabung Volcanic Ash
Geometry:

Polygon
Data type:

Classified
Scenario:

Single event
Attribute field:

KRB
Attribute value map:

High; Medium; Low
Source:

PVMBG - BNPB
URL:
Date:

2014
Licence:
Coverage:

Sinabung region
Description:

The data show the spread of volcanic ash from Mount Sinabung during the 2014 eruption.
../../_images/005_data_volcanic_ash.png

Landslide

File name:

NGK_Landslide_Vulnerability_WGS84.shp
Training data:

Landslide Hazard Zone
Geometry:

Polygon
Data type:

Classified
Scenario:

Single event
Attribute field:

KRB
Attribute value map:

High Landslide Vulnerability Zone - High; Moderate Landslide Vulnerability Zone - Medium; Low Landslide Vulnerability Zone - Low
Source:

PVMBG
URL:

http://vsi.esdm.go.id/gallery/picture.php?/230/category/14 (published map)
Date:

2009
Licence:
Coverage:
Description:

Landslide vulnerability maps show the regions where landslides may occur. Topographic and landuse changes after mapping can change the landslide zone in the map. The high vulnerability zone is to be avoided for settlement areas or strategic infrastructure. If it can’t be avoided, build on the moderate zone, but detailed research is needed to avoid landslide happen. In moderate zone, detailed research is also needed when planning to cut the slope.
../../_images/005_data_landslide_zones.png

Exposure data

Population

File name:

World_Population
Training data:

see table below
Geometry:

Raster
Data type:

Continuous
Unit:

Count
Source:

World Pop
URL:

http://worldpop.org.uk
Date:

2010
Licence:

Creative Commons by Attribution (CCbyA)
Coverage:

ASEAN +
Description:

High resolution (1 pixel represents 100m x 100m, contemporary data on human population distributions are a prerequisite for the accurate measurement of the impacts of population growth, for monitoring changes and for planning interventions. The AsiaPop project was initiated in July 2011 with the aim of producing detailed and freely-available population distribution maps for the whole of Asia. This project has expanded as the World Pop project to include other continents.
../../_images/005_data_asiapop.png

Training data provided:

Training Package

Name

Coverage

Basic InaSAFE

Jakarta_Population_WGS84

Jakarta

Intermediate InaSAFE

Jakarta_Population_WGS84

Jakarta

Other Hazards

West_Sumatera_Population_WGS84

Padang

Other Hazards

NGK_Population_WGS84

Nagekeo

Buildings

Name:

OSM Buildings
Training data:

see table below
Geometry:

Polygon or point
Data type:

Classified
Attribute field:

Type
Attribute value map:

hospital, school, clinic, etc
Source:

OpenStreetMap
URL:

http://openstreetmap.org
Date:

July 2015
Licence:

Open Data Commons Open Database License (ODbL)
Coverage:

World - incomplete
Description:

OpenStreetMap is a collaborative project to create a free editable map of the world. Two major driving forces behind the establishment and growth of OSM have been restrictions on the use or availability of map information across much of the world and the advent of inexpensive portable satellite navigation devices.
../../_images/005_data_osm_building.png

Australian Government has been working with the Humanitarian OpenStreetMap Team (HOT) since 2011 to pilot and train OpenStreetMap data capture in Indonesia. So far over 12 million buildings have been mapped. Some of the scenarios we use in the training materials are situated in Jakarta, Yogyakarta (Merapi), Sumatra (Padang) and Flores (Maumere).

Training data provided:

Training Package

Name

Coverage

Basic InaSAFE

Jakarta_Buildings_WGS84

Jakarta

Other Hazards

Padang_Buildings_WGS84

Padang

Other Hazards

Maumere_Buildings_WGS84

Maumere

Other Hazards

NGK_Buildings_WGS84

Nagekeo

Other Hazards

Sinabung_Buildings_WGS84

Sinabung

Other Hazards

Sinabung_Building-points_WGS84

Sinabung

Each one of these areas has a different OpenStreetMap data collection methodology. Below the data collection methodologies used in Jakarta and Padang are explained:

Jakarta:

BPBD DKI Jakarta (Regional Disaster Managers) and BNPB (National Disaster Managers) with assistance from Australian Government, the World Bank, UNOCHA, HOT and University of Indonesia, held workshops in each of Jakarta’s six districts in order to help village heads map their community boundaries and major infrastructure. Over 500 representatives from Jakarta’s 267 villages participated in these workshops and have mapped an impressive 6,000 buildings and all 2,668 sub-village boundaries (Rukun Warga-RW). For more information go to AIFDR Website

Padang:

After the Haiti earthquake in 2010, there was a large effort to map Haiti through OSM. Coordinating this effort was difficult, and so Australian Government funded the creation of the OSM Tasking Manager. The OSM Tasking Manager is a web-based tool in which a designated area is easily divided into a grid, and individual users can select one piece at a time to quickly work together and digitally map the target area. The tool was first piloted in Padang, where contributors from around the world helped digitise over 95,000 buildings. However, the buildings are only footprints - an on the ground mapping effort is needed to record attributes about each building. The tool is now being used across the world to coordinate OSM mapping efforts. It is available at tasks.hotosm.org

Roads

Name:

OSM Roads
Training data:

see table below
Geometry:

Line
Data type:

Classified
Attribute field:

Type
Attribute value map:

types of roads
Source:

OpenStreetMap
URL:

http://openstreetmap.org
Date:

July 2015
Licence:

Open Data Commons Open Database License (ODbL)
Coverage:

World - incomplete
Description:

OpenStreetMap is a collaborative project to create a free editable map of the world. Two major driving forces behind the establishment and growth of OSM have been restrictions on use or availability of map information across much of the world and the advent of inexpensive portable satellite navigation devices.
../../_images/005_data_osm_road.png

Training data provided:

Training Package

Name

Coverage

QGIS Introduction

Jakarta_Roads_WGS84

Jakarta

Aggregation Data

Administrative Boundary

Name:

Administrative Boundary
Training data:

see table below
Geometry:

Polygon
Data type:

Classified
Attribute field:

Kabupaten / Kecamatan / Desa
Attribute value map:

toponymy of the area
Source:

BPS
URL:
Date:

2010
Licence:
Coverage:
Description:

Administrative boundaries in Indonesia

Training data provided:

Training Package

Name

Coverage

Run Intermediate InaSAFE

Jakarta_District_Boundary_WGS84

Jakarta

Run Intermediate InaSAFE

Jakarta_Subdistrict_Boundary_WGS84

Jakarta

Other Hazards

Sikka_Village_Boundary_WGS84

Maumere

Other Hazards

NGK_Villages_BPS_WGS84

Nagakeo

Other Hazards

Padang_Village_Boundary_WGS84

Padang