Volcanic Eruption

Recommended Practice: Disaster Preparedness Using Free Software Extensions

English

Teaser Recommended Practice: 

Remote sensing technologies can support all stages of the disaster management cycle. In the prevention and preparedness phases, they often find their application in risk assessments, scenario modelling and early warning. This UN-SPIDER Recommended Practice explains how remote sensing data about recurring floods, information about infrastructure and socio-economic data can be integrated using free and open source software to support prevention and preparedness efforts. It makes use, among others, of the InaSAFE plug-in for the desktop GIS software QGIS to estimate the number of people and infrastructure potentially affected by a 100-year flood. The resulting insights can be used to contingency planning and related efforts before a disaster strikes.

Flowchart Recommended Practices: 

Related Software: 

Objective: 

The objective of this step-by-step procedure is to identify potentially damaged buildings and streets, as well the number of potentially displaced persons for two different flood events in Africa. This information can be used for future contingency planning and to improve the design of preventive measures.

Disaster Cycle Phase: 

  • Preparedness

Main Hazards: 

  • Earthquake
  • Flood
  • Tsunami
  • Volcanic Eruption

Test Site: 

This Recommended Practice has been applied to flood scenarios in Mozambique and Ghana.

Context: 

The presented QGIS plug-in was developed jointly by the Indonesian Disaster Management Organization (BNPB), the Australian Government and the World Bank (GFDRR). It was created as free and open source software (FOSS) and is available in the QGIS plug-in library. The use cases provided on the website of InaSAFAE are primarily related to disasters in Indonesia such as floods in the city of Jakarta. For this Recommended Practice, two use cases in Africa have been chosen. The first one focuses on a past flood event in Beira, Mozambique, whereas the second one addresses the larger area of Accra, Ghana, and makes use of a 100-year returning flood layer from the Global Flood Awareness System (GloFAS) of the Joint Research Center (JRC) of the European Commission (EC).

Applicability: 

Both case studies provided show several options to adapt the calculations to other case studies. However, the plugIn does not give the exact number of people as the calculations are rather basic. This allows for faster processing, but also means that values are only an estimate of the expected damage and never an exact number. This practice should raise awareness about risk prevention and provide incentives to improve preparation and planning processes.

Peru - Technical Advisory Mission

As part of it advisory support activities, UN-SPIDER is carrying out out a Technical Advisory Mission (TAM) to Peru from 1 to 5 April to evaluate the current and potential use of space-based information in all aspects of disaster management. Based on exchanges with a wide range of stakeholders, UN-SPIDER will provide recommendations as to how to strengthen the use of space-based information in disaster risk management and emergency response in the country.

Dates: 

Mon, 01/04/2019 to Fri, 05/04/2019

Host Institution: 

National Institute of Civil Defense (INDECI) of Peru and National Commission of Aerospace Research and Development of Peru (CONIDA).

Country/Region: 

Mission Team: 

The team is comprised of eight experts from UN-SPIDER; the German Aerospace Centre (DLR); the Argentinian National Space Activities Commission (CONAE); the Mexican Space Agency (AEM); the Agustin Codazzi Geographic Institute of Colombia (IGAC); the Santa Ana Federal University of Brazil; the National Aeronautics and Space Administration (NASA) of the United States of America; and the Andean Community (CAN). CONAE, AEM and IGAC are UN-SPIDER Regional Support Offices.

Mission Profile: 

The team had a series of meetings with key stakeholder organizations to take account of the availability of geospatial information, current use of space-derived information, data sharing practices, applications of geospatial information, challenges and constraints, existing capacity and needs, institutional linkages and coordination and applications to strengthen disaster risk reduction and emergency response.

 

Recommended Practice: Exposure Mapping

English

Teaser Recommended Practice: 

Mapping the extent of a natural hazard (e.g., assessing areas with a high risk) or disaster is a first step in disaster risk management and emergency response. Subsequently, exposure mapping enables the estimation of the impact of hazards or disasters, for example, regarding the number of affected inhabitants or infrastructure. The following practice shows the use of Quantum GIS to analyze a disaster extent map in combination with auxiliary data such as population or land cover data.

Flowchart Recommended Practices: 

Related Software: 

Objective: 

The objective of this practice is to estimate the exposure of a natural hazard or disaster. As an example, the number of inhabitants affected by a flood event is estimated. The joint use of the flood mask, created by the Recommended Practice: Flood Mapping, and the WorldPop data set constitutes a viable solution to quickly estimate the impact of the flood regarding the population. The proposed methodology is a universal practice which combines a simple approach based on open-source software and free of charge data together with a beforehand created map covering the extend of a natural hazard or disaster.

Disaster Cycle Phase: 

  • Mitigation
  • Preparedness
  • Recovery & Reconstruction
  • Relief & Response

Main Hazards: 

  • Drought
  • Earthquake
  • Extreme Temperature
  • Forest Fire
  • Flood
  • Insect Infestation
  • Mass Movement
  • Pollution
  • Severe Storm
  • Tsunami
  • Volcanic Eruption

Test Site: 

Malawi

Context: 

The practice was applied in the context of the flood event in Malawi in January 2015. Since December 2014, heavy rains affected Malawi causing rivers to overflow. The flooded area in this analysis covered a part of the Nsanje district around Chiromo.

Applicability: 

This practice can be applied globally. Besides of the beforehand created hazard or disaster extent map, the practice does not need specific near real-time data as it is based on population, land cover, or other auxiliary geodata archives. The WorldPop data set provides population data for Africa, Asia as well as Central and South America with a spatial resolution of 100 meters. The Globeland30 data base provides global landcover data with a spatial resolution of about 30 meters.

Sri Lanka National Spatial Data Infrastructure (NSDI - MLLD Sri Lanka)

Data Type: 

satdata

Costs: 

rfree
English

Spatial Coverage: 

Sri Lanka

Temporal Coverage: 

arch

Data accessibility: 

exportdata

File types: 

GeoTIFF
TIFF

Disaster Cycle Phase: 

drm
Screenshot of Sri Lanka National Spatial Data Infrastructure (NSDI)

Spatial Resolution: 

2.50

Requirements: 

<p>Satellite data can be viewed by users on request with the approval of the Surveyor General at CRS Branch.</p>

Hazards Data Distribution System Explorer (HDDS - USGS)

Data Type: 

hazard
satdata

Costs: 

rfree
English

Spatial Coverage: 

Global

Temporal Coverage: 

arch
near

Data accessibility: 

exportdata
exportmap

File types: 

CSV
GeoTIFF
KML
shp
TIFF
XML

Disaster Cycle Phase: 

rr

Spatial Resolution: 

0.50

Requirements: 

<p>Find system and browser requierements in the <a href="http://hddsexplorer.usgs.gov/documents/hddshelp.pdf" target="_blank">help document</a></p>

Restrictions / Citation of the dataset: 

Sentinel 1 - SAR Dataset (ESA)

TerraSAR-X imagery (Airbus)

Data Type: 

satdata

Costs: 

rfree
English

Spatial Coverage: 

Global

Temporal Coverage: 

arch

Data accessibility: 

exportdata

File types: 

bin
cosar
TIFF
XML

Disaster Cycle Phase: 

drm
rr

Spatial Resolution: 

1.00

Requirements: 

<p>DLR gives only to Principal Investigators the opportunity to get a limited amount of free products upon the submission of a TSX Proposal.</p>

Satellites and Sensors: 

RADARSAT-1&2/SAR imagery (CSA, MDA)

Data Type: 

satdata

Costs: 

rfree
English

Spatial Coverage: 

Global

Temporal Coverage: 

arch

Data accessibility: 

exportdata

File types: 

TIFF
XML

Disaster Cycle Phase: 

drm
rr

Spatial Resolution: 

1.60

Space-based Information: 

RADARSAT-1&2/SAR

Requirements: 

<p>ESA gives only to European Principal Investigators (Europe28+Switzerland+Norway) the opportunity to get a limited amount of free products upon the submission of a project proposal.</p>

Satellites and Sensors: 

Earth Explorer (USGS)

Data Type: 

baseline
elevation
landuse
satdata

Costs: 

free
English

Spatial Coverage: 

Global

Temporal Coverage: 

arch
fore
near

Data accessibility: 

exportdata
exportmap
statistic
visdata
webproc

File types: 

bmp
DBF
GeoRSS
GeoTIFF
HDF
KML
shp
TIFF
txt
webmap
WMS

Disaster Cycle Phase: 

drm
rr
Screenshot of USGS

Spatial Resolution: 

30.00

Space-based Information: 

Arial Imagery,AVHRR, Digital Elevation,Declassified data, Digital Line Graphs,Digital Maps, GEOGLAM, Global Fidutials, Global Forest Observation Initiatives,Global Land Survey,JECAM Stes, HCMM, LIDAR, Land Cover,Vegetation Monitoring,NASA LPDAAC Collection

Requirements: 

<p>Operating System: Windows XP, Windows Vista, Windows 7, Windows Server 2000, Windows Server 2003, Windows Server 2008, MAC, UNIX, LINUX</p>

Restrictions / Citation of the dataset: 

EO-1 Sensor Web (NASA)

Data Type: 

satdata

Costs: 

free
English

Spatial Coverage: 

Global

Temporal Coverage: 

arch

Data accessibility: 

exportdata

File types: 

GeoTIFF
HDF4

Disaster Cycle Phase: 

drm
rr

Spatial Resolution: 

10.00

Satellites and Sensors: 

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