This work is aimed at investigating technical possibilities to provide information on environmental
parameters that can be used for risk management.
The World food Program (WFP) is the United Nations Agency which is involved in risk
management for fighting hunger in least-developed and low-income countries, where victims of
natural and manmade disasters, refugees, displaced people and the hungry poor suffer from severe
food shortages.
Risk management includes three different phases (pre-disaster, response and post disaster) to be
managed through different activities and actions. Pre disaster activities are meant to develop and
deliver risk assessment, establish prevention actions and prepare the operative structures for
managing an eventual emergency or disaster. In response and post disaster phase actions planned in
the pre-disaster phase are executed focusing on saving lives and secondly, on social economic
recovery.
In order to optimally manage its operations in the response and post disaster phases, WFP needs
to know, in order to estimate the impact an event will have on future food security as soon as possible,
the areas affected by the natural disaster, the number of affected people, and the effects that the event
can cause to vegetation. For this, providing easy-to-consult thematic maps about the affected areas and
population, with adequate spatial resolution, time frequency and regular updating can result
determining. Satellite remote sensed data have increasingly been used in the last decades in order to
provide updated information about land surface with an acceptable time frequency. Furthermore,
satellite images can be managed by automatic procedures in order to extract synthetic information
about the ground condition in a very short time and can be easily shared in the web.
The work of thesis, focused on the analysis and processing of satellite data, was carried out in
cooperation with the association ITHACA (Information Technology for Humanitarian Assistance,
Cooperation and Action), a center of research which works in cooperation with the WFP in order to
provide IT products and tools for the management of food emergencies caused by natural disasters.
These products should be able to facilitate the forecasting of the effects of catastrophic events, the
estimation of the extension and location of the areas hit by the event, of the affected population and
thereby the planning of interventions on the area that could be affected by food insecurity. The
requested features of the instruments are:
• Regular updating
• Spatial resolution suitable for a synoptic analysis
• Low cost
• Easy consultation
Ithaca is developing different activities to provide georeferenced thematic data to WFP users, such
a spatial data infrastructure for storing, querying and manipulating large amounts of global geographic
information, and for sharing it between a large and differentiated community; a system of early
warning for floods, a drought monitoring tool, procedures for rapid mapping in the response phase in
a case of natural disaster, web GIS tools to distribute and share georeferenced information, that can be
consulted only by means of a web browser.
The work of thesis is aimed at providing applications for the automatic production of base
georeferenced thematic data, by using free global satellite data, which have characteristics suitable for
analysis at a regional scale. In particular the main themes of the applications are water bodies and
vegetation phenology. The first application aims at providing procedures for the automatic extraction
of water bodies and will lead to the creation and update of an historical archive, which can be analyzed
in order to catch the seasonality of water bodies and delineate scenarios of historical flooded areas.
The automatic extraction of phenological parameters from satellite data will allow to integrate the
existing drought monitoring system with information on vegetation seasonality and to provide further
information for the evaluation of food insecurity in the post disaster phase.
In the thesis are described the activities carried on for the development of procedures for the
automatic processing of free satellite data in order to produce customized layers according to the
exigencies in format and distribution of the final users.
The main activities, which focused on the development of an automated procedure for the
extraction of flooded areas, include the research of an algorithm for the classification of water bodies
from satellite data, an important theme in the field of management of the emergencies due to flood
events. Two main technologies are generally used: active sensors (radar) and passive sensors (optical
data). Advantages for active sensors include the ability to obtain measurements anytime, regardless of
the time of day or season, while passive sensors can only be used in the daytime cloud free conditions.
Even if with radar technologies is possible to get information on the ground in all weather conditions,
it is not possible to use radar data to obtain a continuous archive of flooded areas, because of the lack
of a predetermined frequency in the acquisition of the images. For this reason the choice of the dataset
went in favor of MODIS (Moderate Resolution Imaging Spectroradiometer), optical data with a daily
frequency, a spatial resolution of 250 meters and an historical archive of 10 years. The presence of
cloud coverage prevents from the acquisition of the earth surface, and the shadows due to clouds can
be wrongly classified as water bodies because of the spectral response very similar to the one of water.
After an analysis of the state of the art of the algorithms of automated classification of water bodies in
images derived from optical sensors, the author developed an algorithm that allows to classify the data
of reflectivity and to temporally composite them in order to obtain flooded areas scenarios for each
event. This procedure was tested in the Bangladesh areas, providing encouraging classification
accuracies.
For the vegetation theme, the main activities performed, here described, include the review of the
existing methodologies for phenological studies and the automation of the data flow between inputs
and outputs with the use of different global free satellite datasets. In literature, many studies
demonstrated the utility of the NDVI (Normalized Difference Vegetation Index) indices for the
monitoring of vegetation dynamics, in the study of cultivations, and for the survey of the vegetation
water stress. The author developed a procedure for creating layers of phenological parameters which
integrates the TIMESAT software, produced by Lars Eklundh and Per Jönsson, for processing NDVI
indices derived from different satellite sensors: MODIS (Moderate Resolution Imaging
Spectroradiometer), AVHRR (Advanced Very High Resolution Radiometer) AND SPOT (Système Pour
l'Observation de la Terre) VEGETATION. The automated procedure starts from data downloading, calls
in a batch mode the software and provides customized layers of phenological parameters such as the
starting of the season or length of the season and many others