The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B4. Beijing 2008
operations. To facilitate and support the coordination of
logistics capabilities among co-operating humanitarian agencies,
as well as to complement and support the global and field
logistics clusters, is another major objective while planning an
on-field action. It is done through the provision of Logistics
Information Management, mapping, customs, commodity
tracking tools and services. Inside the UN organization, that
duty is responsibility of the United Nations Joint Logistics
Centre (UNJLC). The UNJLC is a UN Common Service; it is a
facility activated when intensified field-based inter-agency
logistics information is required. Once mobilised, the UNJLC
seeks the widest possible participation among all humanitarian
logistics actors (UN and NGO alike).
During relief operations preliminary phases, short term analyses
on the effects of a single event are critical for preparing detailed
intervention plans and budget estimates. The use of remote
sensing techniques, to perform accurate and timely assessments,
combined with updated, reliable and easily accessible reference
base datasets are a key factor for the success of emergency
operations, helping to answer key questions as how much food
aid is needed and how to deliver it to the hungry population.
Short-term emergency response capacities, long-term risk
reduction, development and environmental protection activities
are sector where a Spatial Data Infrastructure (SDI) may
strongly improve efficiency.
The term Spatial Data Infrastructure (SDI) is often used to
denote the relevant base collection of technologies, policies and
institutional arrangements that facilitate the availability of and
access to spatial data. A spatial data infrastructure provides a
basis for spatial data discovery, evaluation, download and
application for users and providers within all levels of
government, the commercial sector, the non-profit sector,
academia and the general public. Spatial data infrastructures
facilitate access to geographically-related information using a
minimum set of standard practices, protocols, and specifications.
Spatial data infrastructures are commonly delivered
electronically via internet.
The production and use of geospatial information within the
United Nations has been accomplished historically by its
component organizations in accordance with their individual
needs and expertise. This has resulted in multiple efforts,
reduced opportunities for sharing and reuse of data, and an
unnecessary cost burden for the United Nations as a whole.
The ITHACA {Information Technology for Humanitarian
Assistance Cooperation and Action) association is supporting
UN WFP in developing and implementing an SDI as solution
for several issues, related to distributed management and
exploitation of spatial data, among them:
• inconsistent data in terms of content and format;
• existence of “invisible” data, not computerized or hidden in
local computers;
• confidentiality and sensitivity of certain data and
information;
• difficulties in implementing data/systems integration;
• poor application of standards;
• lack of extensive and reliable metadata catalogues;
• lack of streamlining of spatial analysis in decision making;
• unproductive competitive practices.
2. SDI ARCHITECTURE
2.1 Needs assessment
As a result of needs assessment round tables with WFP users,
an architecture granting a solid back end and a flexible,
interoperable and customized front end has been considered the
best solution for managing data in a distributed environment.
Back end component is accessed by high level users, in charge
of database management and of performing complex data
analysis procedures. Front end applications are mainly
dedicated to analysis, processing of project specific geodata and
exploratory aspects; simple editing capabilities should be also
included.
Technical constraint related to low performance internet
connection required to develop solutions for disconnected data
management using database replica and guided procedures for
data reconciliation.
Re-use and re-organization of currently managed dataset have
been a priority in the data modelling phase, together with direct
access to open geographic sources (SRTM data, archive satellite
images, etc.) without any need for data pre-processing.
Finally, the development of suitable data management rules and
map templates allows to create a “lowest common
denominator” for geographic analysis and mapping, in support
to decision making during emergencies.
2.2 System architecture
A two-levels architecture is proposed and implemented, to fulfil
two major requirements:
• to increase performances by splitting the production and
publication environments;
• to study new features in order to implement a progressive
porting of the geodatabase from a commercial to a non
commercial Database Management System.
Production/Editing environment: back end component
accessed by high level users, in charge of database management
and of performing complex data analysis procedures. The
necessity of having ready-to-use and operative functionalities
for ongoing activities and missions, granting high levels of data
security and reliability, is the main factor suggesting the
implementation of a commercial products based platform (
Table 1).
Component
Description
Version
Type
Operating
System
Ubuntu
(linux)
7.10 (32bit)
Open Source
DBMS
Oracle 10 G
10.2.0.1.0
Commercial
Gateway
Software
ESRI
ArcSDE
9.2
Commercial
GIS Client
ESRI ArcGIS
9.2
Commercial
Table 1 - Production/Editing environment architecture
Data security issue is granted by the applicability of several
different approaches, such as:
• authentication, one-factor or two-factor;
• authorization;
• privileges;
• data encryption;
• Data Integrity algorithms;