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;