Use of Geospatial information and Satellite derived products
Background
One of the key issues for all actors involved in post disaster need assessment activities is to
obtain timely, relevant, and accurate information regarding geographic location and spatial
extent of areas affected by a natural disaster including preliminary damage estimation to
human and physical assets. This information should be collected immediately after a major
disaster possibly prior the PDNA mission in order to plan and to prioritize the strategic
collection of sectoral information needed for the recovery planning process. The use of
satellite imagery can be a very cost-effective way to collect such information and often, in
the immediate aftermath of a major disaster, represents the only source of synoptic
information available within affected remote and less developed areas.
Satellite imagery provides both geographic location and spatial representation of features and
objects on the Earth’s surface: shape, size, visual appearance and spatial distribution
patterns and, thus, it can be a very effective support tool for conducting preliminary
(satellite based) damage analysis. The selection of suitable satellite images to assess the
impact of natural disasters is generally based upon a number of different technical
parameters, such as satellite characteristics (sensor and platform type), image availability,
area coverage and required map scales, potentially affected recovery sectors, date of
acquisition, number of spectral bands, and spatial resolution.
Spatial resolution of satellite imagery is a critical factor since it directly influences the ability
to discriminate objects and features on the ground: very high resolution satellite imagery is
generally used to perform very accurate damage detection of objects with high spatial details
such as buildings, shelters, bridges, dams, reservoirs, communication network and utilities
lines. Medium and high resolution satellite imagery can be useful to assess damage to
agricultural areas, environment and infrastructures at lower level of details, while low
resolution imagery is commonly used for disaster mapping at regional scale. Satellite imagery
is usually delivered as large volume binary data sets, which require dedicated processing
before they can be used in assessment exercises. Currently, assessments are typically based
on the interactive interpretation of high and very high resolution remotely sensed, optical,
data i.e. : “image analysts inspect pre- and post- disaster imagery to detect potentially
damaged areas or features that can be then categorized into a given thematic class and
graded by damage severity. Due to the typical time pressure in obtaining “rapid”
assessments, the processing time required should be kept at a minimum.
Satellite imagery fits within the category of geospatial data which refers to data that are
geographically referenced to a location on the Earth’s surface. Besides satellite imagery,
commonly used geospatial data during PDNA activities are: aerial and/or geo-coded ground
photos, topographic maps, GPS points, existing GIS datasets, and other disaster related
spatial information from media, local authorities and field assessments. In the aftermath of a
disaster, damage information extracted from satellite imagery can be easily integrated
together with available geospatial data into a Geographic Information System (GIS) which
allows to store, to manipulate and to analyse different spatial datasets and to create mapping
products at different levels of detail. This information is crucial for a proper planning of the
PDNA, but also for the aggregation and consistent presentation of results.
GIS is a powerful analysis and modeling tool which may help actors involved in PDNA activities
to address specific questions including the following:
-
Geographic extent of damaged areas (e.g. how many square kilometers?)
-
Spatial distribution and number of affected villages
-
Estimation of population living within affected areas (e.g. amount of affected
population by administrative units)
-
Status of access routes and logistic facilities
-
Identification of most affected areas (e.g. based on population density, magnitude of
disaster impact and transportation network accessibility, etc.)
-
Spatial distribution and amount of damage to physical assets (e.g. number of damaged
housing and shelters, hospital and school facilities, industry, length of damaged roads,
size of affected agricultural land, etc.)
-
GIS also allows distance and site selection analysis to relocate affected population and
to support the planning and monitoring of reconstruction and rehabilitation measures
and projects
The Tables 1 and 2 below provide an overview of geospatial information in support of PDNA
that can be either extracted from satellite imagery or collected from different sources of
information such as international agencies, local authorities and PDNA field surveys.
Table 1: Reference, baseline, pre-disaster, spatial information relevant for all recovery sectors
Baseline (Common to all sectors)
Administrative
-
Spatial information (Pre-disaster)
Administrative boundaries
P-codes and places names
Population density and distribution
Topography
Land-use and land cover
-
Elevation (DEM)
Slopes (steepness and orientation)
Contour lines
Bathymetry
Coastlines
-
Land-cover including settlements and built-up
areas
Status of vegetation (health and phonology
based on e.g. NDVI)
Hydrographic network
Watersheds and catchments
Weather forecast
Rainfall distribution
Land and water surface temperature
Wind speed and humidity
Storm tracks
Floods
Landslides, mudflows and debris flows
Volcano: lahars, pyroclastic and lava flows
Earthquakes & Tsunamis
Cyclones, Hurricanes and storms
Forest fires
-
Hydrography
Climate/Meteorology
Disaster risk
Table 2: Damage related spatial information grouped by recovery sector
Recovery Sectors
Agriculture
Security
&
Food
Health & WASH
Education
Infr
ast
ruc
tur
e&
lan
duse
Social
Productive
Commerce & Industry
Housing,
Properties
Land
&
-
Damage related spatial Information
Commercial Shops
Markets
Industry
Crops and agricultural land
Irrigation network
Fishery
livestock
Agro-forestry
Health facilities
Wells, boreholes and springs
Water and sanitation facilities
School facilities
-
Housing & shelters including public buildings
CrossCutting
Infrastructure
Environment
-
Transportation network
Telecommunication network
Utility lines
-
Protected natural areas
Wetlands
Forestry/deforestation
Pollution
World heritage sites
Satellite imagery acquisition and mapping products for PDNA
Within the context of the PDNA process, satellite imagery and geospatial information can be
delivered within few days, sometimes few hours after the onset of disaster according to the
geographic extent of affected areas, availability of satellite imagery and geo-spatial data and
level of image processing required. Suitable satellite imagery and mapping products in
support of the PDNA can be grouped into three primary stages of analysis ranging from predisaster and post disaster to medium and longer-term recovery planning and reconstruction
monitoring:
1. Pre-Disaster (Disaster Preparedness)
2. Disaster to Immediate Post-Disaster
3. Medium and longer-term recovery planning and reconstruction
Fig.1
Overview of
information and satellite derived products in support of the PDNA process
(copyright JRC – UNOSAT 2009)
Pre-Disaster (Disaster Preparedness):
Task: Strategic collection of geospatial data over vulnerable and hazard prone regions
Timeframe: before the onset of a disaster
During this stage of analysis, general information regarding the occurrence of natural hazards
should be collected particularly over vulnerable and hazard prone areas. Existing information
such as maps, satellite imagery, and reports can be used to illustrate historical and current
conditions over hazard prone areas. With this information, it will be easier to identify
potentially hazardous conditions and conduct qualitative and quantitative assessments of the
probable impacts of natural hazards over a given area. Gathering all existing hazard-related
information during the preparedness phase provides an inventory of what is available and
enables the decision makers to determine what else will be needed for the subsequent
phases. Hazard related information extracted from satellite imagery can be combined with
other available information such as vulnerability data on population, land-use, buildings and
contents type, infrastructure and economic activities to assess the risk and to create
vulnerability and risk maps over hazard prone areas.
The use of satellite imagery can be very cost-effective and often the only source of
information within remote and less developed areas. Moreover, remote sensing may
contribute to updating cadastral and land-use maps. Cartographic updates are an important
aspect of remote sensing since there are often delays in public administration for maintaining
updated official cartography. Obtaining a sufficient range of thematic and satellite images
during the preparedness phase will save time and it may help to identify appropriate
questions and issues to be addressed at the early stages of need assessment activities by
PDNA expert teams. Satellite data and useful mapping products for disaster preparedness
activities are listed below; the appropriate map scale and/or imagery resolution may vary
according to the type of hazard and the size of the vulnerable and hazard prone regions.
1) Satellite imagery over hazard prone regions (archive of reference, baseline,
satellite data)
2) Hazard related maps showing frequency and extent of past hazard phenomena
3) Reference maps for vulnerability and risk assessments
Disaster to Immediate Post-Disaster:
Task: Situation assessment maps
Timeframe: Immediately after the disaster strikes (prior to PDNA mission)
In the immediate aftermath of a natural disaster, timely and detailed situation assessments
and maps are required to locate and identify affected areas and to perform preliminary
damage assessment analysis to physical assets relevant to recovery sectors. Pending
availability of pre-disaster satellite imagery, and the timely availability of post-disaster
imagery, pre and post disaster satellite imagery are analyzed together with other available
geospatial data and disaster related information from different sources (media reports,
UNOCHA SitReps, local authorities, etc.). In general, the critical elements during rapid
assessment and mapping activities are the availability of essential, reference and postdisaster, datasets, processing times, information extraction times, and the PDNA
requirements.
For a given major
disaster,
the
geographic scale
at which the
analysis can be
carried out is
determined
by
both the spatial
resolution
of
available
preand
postdisaster satellite
data and existing
geospatial
datasets.
The result of this
stage of analysis
is the production of the following mapping products that can be delivered from few hours to
few days after the onset of a disaster:
Fig. 2 Estimated earthquake intensity map
showing the extent & variation of ground shaking
throughout the affected province of South Kivu,
Democratic Republic of Congo (February 2008).
Fig. 3 Location map of Madagascar threatened by
tropical cyclone Gamede (February 2007)
showing the approximate population density and
distribution of the country.

Location maps are generally realized using the most recent pre-disaster satellite
archive ideally less than five
years
old
to
provide
a
geographic
overview
over
potentially affected regions.
Depending of the geographic
extent of the disaster, location
maps are generally produced at
a variable scale ranging from
1:50.000
to
1:1.500.000
showing,
when
available,
baseline information such as
administrative
boundaries,
topography,
major
communication network, major
cities and towns, population
density /distribution and other relevant information layers.
Fig. 5 Disaster overview map of
Ayeyarwady Delta, Myanmar hit by
Cyclone Nargis (May 2008) showing total
population living within flood affected
areas
Disaster maps provide an overall view of affected
areas and are useful planning and coordination
support tools for both humanitarian and need
assessment activities to set priorities for interventions. A detailed inventory of all areas
affected by disasters may require large scale satellite derived mapping products for which
high and very high resolution imagery become necessary. The intent of disaster maps is to
estimate the potential impacts on population and physical
assets relevant to the recovery sectors caused by the disaster
event. Disaster maps are usually produced at a variable scale
ranging from 1:50.000 to 1:1.500.000 depending on the
geographic extent of affected areas as well as on the spatial
resolution of available post-disaster satellite imagery. At this
stage of analysis, It is crucial to collect rapidly existing
spatial datasets over areas of interest such as administrative
boundaries, topography, major transportation network,
major cities and towns population density/distribution,
urban areas, land-use/land-cover maps. These datasets are
usually combined into a GIS together with the extent of
damage extracted from post-disaster satellite imagery. GIS
analysis allows the identification of those areas potentially
damaged and to estimate the number of affected population
Fig. 6 Damage assessment map of a village in Ngapudaw
township, Myanmar hit by Cyclone Nargis (May 2008)
showing spatial distribution of building and damage
statistics (400 buildings likely destroyed or severely
damaged which represents 87% of all village buildings.
and amount of damage to physical assets (e.g. number of villages and size of agricultural
land severely flooded).

Damage Assessment statistics and maps are generally produced few days after the
onset of a major disaster when very-high and high resolution imagery becomes
available over affected regions. Satellite derived damage assessment is often
performed by analysis of pre- and post disaster satellite imagery, especially when
detecting damage to infrastructures such as buildings, road network and other ground
features with high spatial details. To be relevant for PDNA activities, this stage of
satellite derived analysis should cover damage assessment to the following recovery
sectors :
 Productive sector: industry and agriculture focusing on damage to buildings and
agricultural land
 Social sector: health and education focusing on damage to buildings
 Infrastructure and built-up environment including housing
 Cross-cutting: environment
Fig. 7 Damage assessment map of the village of Gonaives, hit by four
hurricanes in 2008, showing the overall affected area (in red) and the
roads flooded or mud-covered (in yellow), 129 km of road were
affected.
summarise damage statistics by sector at an appropriate scale.
The map scale of
these satellite derived
mapping
products
generally
varies
between 1:2.000 and
1:50.000.
The
information
derived
from
GIS
analysis
usually refers to the
spatial distribution of
damaged
ground
features with damage
statistics
by
administrative
unit
and/or
by
sectors
when this information
is available. The maps
should show the spatial
extent of damage, main
affected sectors, and
Recovery planning and reconstruction monitoring
Tasks: Field verification of satellite based damage analysis – Damage statistics aggregated by
recovery sector and administrative – Damage maps - Establishment of a spatial database
infrastructure - Training and capacity building programmes
Timeframe: During and after the PDNA Mission
During the PDNA mission, satellite derived damage analysis conducted in the aftermath of the
disaster can contribute as evidence based information to support and plan the PDNA sectoral
data collection. Field verification with the support of detailed geo-coded photos, videos and
observation and the integration of spatial data and information collected during the PDNA
into a GIS can significantly improve the preliminary and remote damage analysis carried out
prior the PDNA missions. GIS analysis performed during PDNA missions allows the production
of more detailed damage assessments and aggregated statistics as well as maps categorized
by different recovery sectors and administrative units. These damage statistics and maps may
be included into the PDNA report to make more visible and clear the geographic distribution
of damages and losses within affected regions.
In addition, the establishment of a Spatial Database Infrastructure (i.e. data structure and
access procedures) allows a better management of spatial data and information collected
prior and during the PDNA and it will facilitate the handover of data and information to
national and local authorities to support the recovery planning process including monitoring
of reconstruction activities. Spatial databases generated during the PDNA should be accessible
by all the different actors involved in the recovery planning process including national
authorizes and they should integrate:

Data and Information generated during the emergency response phase as well as during
the PDNA,

Detailed satellite based damage assessments/statistics produced by GIS and Remote
Sensing experts including available pre and post disaster satellite imagery

Project proposals, reconstruction plans including the reconstruction projects awarded
A well designed and implemented information management system allows the establishment
of a monitoring mechanism to guarantee transparent, traceable and efficient implementation
of recovery plans. For this reason the provision of training and capacity building to strengthen
local capacities in the use of geo-information technologies should be considered as a critical
component of the entire recovery planning process.
Standards and Data Format
The complexity and diversity of geographic datasets needed to support PDNA activities call
for the formalization of spatial data concepts, data structures, data formats and the use of
appropriate data standards that facilitates spatial data exchange between all actors involved
in the PDNA process.
Amongst other initiatives, The Geographic Information Support Team (GIST), an ad-hoc interagency support group for sharing of geographic information between actors in the
humanitarian relief community, has developed a set of core standards for sharing of
information. These standards, following the SHARE (Structured Humanitarian Assistance
Reporting Exchange) approach, include:

Geographic reference or location information on where data was collected,

Time-stamp indicating when data was collected, and at what frequency new data are
collected, where suitable,

Meta-data (information about the data itself), including information on source of data,
what the data values represent, which standards were used and how the data were
acquired.
One of the main benefits with satellite imagery is that it follows these standards. This makes
satellite data particularly suitable for GIS integration and sharability with other actors
involved within the PDNA process.
In terms of data formats, satellite imagery is normally delivered as raster data, either already
geo-referenced (e.g. in the GeoTIFF format) or with so-called header-files (meta-data)
containing information on the type of sensor, center and corner co-ordinates, acquisition date
and time, satellite orbit parameters, pixel size, processing level and data provider, etc.
Static, pre-rendered map products are commonly delivered in JPEG or PDF formats which
allow easy file download and printing. Increasingly, webGIS functionality supports interactive
composition of maps, e.g. from a collection of web-services that supply relevant geospatial
outputs. Such web-services typically adhere to the Open GIS Consortium’s web map service
(WMS) and web feature service (WFS) standard protocols. GeoRSS, GeoPDF and Google Earth
formats (KML) are OGC standard implementations that allow wide access to geospatial
datasets also to users that are not experienced in the use of GIS and mapping. The use of tile
server protocols (e.g. OGC TMS, or Google Earth SuperOverlays) support the sharing of full
resolution and complete image coverage and their derived analysis results amongst
assessment teams. These novel GIS architectures can be based on inter-connected GIS data
servers, dedicated computing nodes and distributed clients for visualization and analysis. This
is particularly relevant in PDNA contexts, where contributing PDNA entities may hold
particular geospatial data sets (e.g. derived from satellite imagery, or ground observation
collected by field teams) of interest that need to be shared rapidly in a “common operational
picture”.
Legal aspects and limitations
Within the context of the PDNA process, the benefit of using satellite derived products is
more related to the evaluation of damages and losses to physical assets rather than the
identification of human recovery needs. However, timely delivered satellite derived products
such as disaster situation maps may be very useful for all actors involved in the PDNA for the
planning and coordination of field activities. Satellite derived damage analysis constitute an
evidence based information to support field data collection on damages and losses. Despite
the enormous progress of Earth Observation satellite technology and the recent availability of
very high resolution satellite imagery there are still some technical limitations in the use of
satellite imagery for operational activities such as disaster response and post disaster need
assessments where timely and accurate information is needed:

Availability of satellite imagery: in the immediate aftermath of disaster very high
resolution imagery may not be available over affected areas due to the revisit time of
orbiting satellites that may vary from 2 to 8 days. Another important issue is
represented by weather conditions over disaster impacted regions: cloud coverage
may dramatically affect the exploitation of Very high resolution optical imagery to
perform damage analysis. Thus, days of delay might be expected before acquiring
successfully cloud free satellite imagery. Weather conditions are less important if
radar data can be used for disaster impact delineation (e.g. in the case of floods). The
selection and procurement of satellite data may also require 1-2 days.

Another important aspect to consider is that the quantitative estimation of damage to
buildings and other infrastructures when performed with satellite imagery is a
conservative estimate compared to the actual damage assessed from the ground. This
limitation is mainly caused by the overhead viewpoint of very high resolution optical
imagery that does not allow detecting lateral damage and damage to internal
structures of buildings. Moreover, partial damage to infrastructures may not be
accurately assessed due to the spatial resolution of the imagery and also the total
destruction of buildings might be not assessed especially in the case of the pancake
collapse with intact roof.

Copyrights: all purchased satellite imagery acquired by commercial orbiting satellites
comes with varying degrees of copyright restrictions. Raw satellite imagery data
themselves are usually restricted to the organization that bought the image, or
restricted to a group of predefined users. For the overall benefit of the PDNA process,
satellite imagery should be purchased in a multi-license mode which will allow sharing
pre and posting disaster satellite images amongst all actors involved in the PDNA
including national and local authorities. However satellite derived mapping products
(e.g. location maps, disaster overview maps and damage assessment maps) can be
shared freely amongst PDNA actors without any restrictions.

Cost can be another important limiting factor for the operational use of satellite
imagery. It is a general assumption that satellite imagery are expensive data. This is to
a certain extent correct, but it depends on the type of imagery, and to what one
compares the cost. The cost of satellite raw data ranges from zero (low resolution
imagery) to around 20 US$ per SqKm (Very High resolution imagery). However, during
a major disaster, the International Charter on Space and Major Disasters provides to
authorized users free raw satellite data over affected regions from which satellite
derived mapping products can be produced and freely delivered to both humanitarian
and PDNA actors. Despite there are still some technical and cost limitations, the use
satellite imagery in support of emergency response and recovery planning continue to
increase. The growing number of Earth-orbiting satellite systems makes satellite
imagery day by day cheaper and available in an increasing number of archive data
(multi-temporal datasets), scene sizes, spectral resolution, and spatial details.
Regarding the potential legal restrictions that might affect the utilization of satellite imagery
in the context of PDNA framework an important reference is provided by the UN Remote
Sensing Principles (United Nations, 1986) and the Outer Space Treaty (United Nations, 1967).
The UN Remote Sensing Principles constitute a set of statements from the UN to which many
countries subscribe— and provide that space-borne remote sensing activities can in principle
be undertaken without the specific permission of the state where satellite imagery is
acquired. The UN Remote Sensing Principles highlight the fact that remote sensing activities
should (a) be carried out for the benefit and in the interests of all countries, taking into
particular consideration the needs of the developing countries (Principle II) and, (b) include
international co-operation and technical assistance (Principles V and VIII). Furthermore, when
one country acquires data over another, the sensed country should have access to the data on
a non-discriminatory basis and at reasonable cost (Principle XII). If monitoring is performed
from outer space, states can legally collect data but should be willing to make these data
available to the sensed state. Remote sensing technology should be viewed as a tool to
support humanitarian assistance and the overall recovery planning process and not an
instrument for treaty policing. After all, the UN Principles provide that remote sensing
activities should be carried out in the spirit of international cooperation and for the benefit
and in the interests of all countries.
Useful web links and References
For more information regarding technical capabilities of satellite sensors for risk management
application:
http://www.space-risks.com/SpaceData/index.php?id_page=1
To access and download disaster-related mapping products:
http://www.unosat.org
http://www.gdacs.com
http://www.reliefweb.org
http://ocha.unog.ch/virtualosocc/
Guide to Multi-Stakeholder Post Disaster Needs Assessment (PDNA) and the Recovery Framework,
Working Draft, 16 January 2009.
Handbook for Estimating the Socio-economic and Environmental Effects of Disasters. Economic
Commission for Latin America and the Caribbean (ECLAC) 2003.
T.Lillesand, R.Kiefer, Remote Sensing and Image Interpretation, John Wiley & Sons 1994
GMOSS - Global Monitoring for Security and Stability, JRC scientific and technical reports 2007
United Nations, 1986. Principles Relating to Remote Sensing of the Earth from Outer Space.
UN Resolution 41/65, 31 December 1986.
United Nations, 1967. Treaty on Principles Governing the Activities of States in the
Exploration and Use of Outer Space, including the Moon and Other Celestial Bodies. UN
Resolution 2222 (XXI), 27 January 1967.
Bjorgo, E. Using very high spatial resolution multispectral satellite sensor imagery to monitor
refugee camps International Journal of Remote Sensing, Letters, accepted as coverpublication 1999.
Brunner D., G. Lemoine, F.X. Thoorens and L. Bruzzone, 2009, Distributed geospatial data processing
functionality to support collaborative and rapid emergency response, IEEE JSTARS, Vol. 2, No. 1, …
S. Voigt, T. Kemper, T. Riedlinger, R. Kiefl, K. Scholte and H. Mehl (2007): Satellite image
analysis for disaster and crisis management support. IEEE Transactions on Geosciences and
Remote Sensing, 45(6):1520-1529
Pisano, F. and E. Bjorgo, Space Security and Satellite Applications in Humanitarian Aid.
UNIDIR Conference Report, Security in Space – The Next Generation, 2008
Pisano, F. and E. Bjorgo, Moving from technology to its applications: using satellite remote
sensing for disaster prevention and vulnerability reduction, In Real Risk, Tudor Rose, 2006