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Every year, there are almost 50,000 forest fires in Europe (127/day), which have burned an area equal to more than 450,000 ha. An effective management of forest fires is therefore fundamental in order to reduce the number of the fires and, especially, the related burned areas, preserving the environment and saving human lives. However, some problems still exist in the structure of information and in the harmonization of data and fire management procedures among different European countries. Pursuing the same interoperability aims, the European Union has invested in the development of the INSPIRE Directive (Infrastructure for Spatial Information in Europe) to support environmental policies. Furthermore, the EU (European Union) is currently working on developing ad hoc infrastructures for the safe management of forests and fires. Moving from this premises and following an analysis of the state of the art of information systems for forest fire-fighting, in the light of the end-user requirements, the paper presents the INSPIRE—compliant design of a geographical information system, implemented using open-source platforms.
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An INSPIRE-compliant open-source GIS for fire-fighting
Nives Grasso
Andrea Maria Lingua
Maria Angela Musci
Francesca Noardo
Marco Piras
Received: 10 July 2017 / Accepted: 6 October 2017 / Published online: 17 October 2017
ÓSpringer Science+Business Media B.V. 2017
Abstract Every year, there are almost 50,000 forest fires in Europe (127/day), which have
burned an area equal to more than 450,000 ha. An effective management of forest fires is
therefore fundamental in order to reduce the number of the fires and, especially, the related
burned areas, preserving the environment and saving human lives. However, some prob-
lems still exist in the structure of information and in the harmonization of data and fire
management procedures among different European countries. Pursuing the same interop-
erability aims, the European Union has invested in the development of the INSPIRE
Directive (Infrastructure for Spatial Information in Europe) to support environmental
policies. Furthermore, the EU (European Union) is currently working on developing ad hoc
infrastructures for the safe management of forests and fires. Moving from this premises and
following an analysis of the state of the art of information systems for forest fire-fighting,
in the light of the end-user requirements, the paper presents the INSPIRE—compliant
design of a geographical information system, implemented using open-source platforms.
Keywords Forest fire-fighting Decision support system Emergency
management INSPIRE data model GIS
1 Introduction
As a consequence of the global climate change and the interaction among several natural
and technological hazards, the number of natural disasters, including forest fires, is
increasing. They usually cause life losses and property and environmental damages (IPCC
2014). A recently published international document, the Sendai Framework for Disaster
Risk Reduction 2015–2030 (Sendai Framework 2015), identifies, considering the open
&Maria Angela Musci
Dipartimento di Ingegneria Dell’ambiente, Del Territorio E Delle Infrastrutture (DIATI),
Politecnico di Torino, Duca degli Abruzzi 24, 10129 Turin, Italy
Nat Hazards (2018) 90:623–637
problems, two critical issues: the standardization of the risk and danger factors information
and the necessity to optimize the employed capital in emergencies.
In the list of main natural and man-made disasters, the forest fires take up an important
role, for the seriousness of damages, and the consequent costs (Guha-Sapir et al. 2015).
This phenomenon is widely spread in Europe. The total European burned area only in the
year 2012 (most recent available official data) is 519,424 ha (European Commission—
Joint Research Centre 2012).
In order to be more effective, forest fires require both active and passive fighting
activity. In particular, the management of fire emergencies is organized in three steps
(Fig. 1).
Management, monitoring of fire risk areas and fire-fighting actions are very complex
operations, especially when dealing with ‘‘mega fires’’ (Pyne 2007). Some critical issues
have to be solved for effectively perform these activities by means of automatic and
integrated tools (Chuvieco and Salas 1996).
During each step, the operators must collect and analyse a lot of data, having various
nature (dynamic data, historic series, geometric or thematic data, and so on) (Chuvieco
et al. 2010). Private and public institutions produce and provide data in different and,
sometimes, proprietary formats (Zlatanova et al. 2010). This produces difficulties in the
information retrieval process, and the rapid and efficient interpretation and usage of the
data. It is therefore necessary to harmonize the involved data. For example, the national (or
even sub-national) digital maps are often structured following local specifications and are
shared through independent procedures, which vary in each case.
Finally, the coordination and collaboration among the various operators taking part in
the emergency intervention are essential: official forces (land, marine and air), volunteer
corps, resources coming from neighbouring countries, providing help, and so on. However,
a current difficulty is the coordination process, because it is ruled by different procedures
in each country.
These issues have to be taken into action for effectively realizing a unified European
supporting system for fire-fighting, possibly sharing and optimizing resources.
The foremost tasks to be realized are as follows: an early warning system and a support
for a risk management integrated approach, which allow controlling all the fire-fighting
steps (Fig. 1).
Considering these aspects, this study proposes a method to design and implement a
standard-based Geographic Information System (GIS) increasing the interoperability of
involved data, and producing an effective information for fire-fighting, allowing the pos-
sibility of an automatic and real-time data validation and integration. A possible good
solution could be the use of the European Directive INSPIRE (Information for spatial
information in Europe) (INSPIRE Directive 2007), which has the aim of transboundary
Fig. 1 Steps of the fire-fighting operations
624 Nat Hazards (2018) 90:623–637
cartographic data harmonization and management for environmental protection and
common policies. Nevertheless, the data model proposed by INSPIRE is a complete and
international standard-compliant (e.g. with the ISO/TC211 standards) model, suitable to
represent cartographic entities even outside Europe. For its completeness and application
independence, it could be considered as an ontology.
In the implementation of the system, open-source software products were preferred,
because, firstly, they are recommended by programs such as ‘‘Interoperable Delivery of
European eGovernment Services to public Administrations, Business and Citizens’’, at
European level (European Commission 2004) or Digital Administration Code in Italy.
Secondly, open-source software were selected for their well-known features such as
cheapness, portability and customization potentiality.
Finally, a further contribution of this study is the introduction of automated processes
such as triggers and specific queries, which allow the system to be quickly consulted also
exploiting real-time data. Moreover, through similar processes, the system can fill-in
automatically, and in real time, some tables useful for the management of the resources in
fire-fighting activity (e.g. firefighters teams during emergencies).
2 The state of the art: GISs dealing with fires
Currently, in Europe, there are already several GIS platforms providing decision support
for fires issues. However, each system emphasizes only some specific functionality for the
stages of the fire management. In recent years, some examples of tailored forest fire
decision support systems based on GIS technology have been developed and used in
different regions, for example, France, Italy, Spain and the Alpine areas of Europe.
However, they do not implement the whole process, but only a part, or some parts of it.
In particular, GIS EMERCARTO (made by TRAGSA) (
focused in the command and control of operations, as well as in the management and
allocation of fire-fighting resources and support in the decision-making process in real
time. Another GIS tool was developed by (Moreno et al. 2012), in which a dedicated
simulation was realized for a rapid organization of human resources and their equipment.
The capabilities of this tool allow the analysis of the impact of different fire-fighting
strategies considering different simulated scenarios of active operations on the field. In
Italy, the system called SIRIO was developed by (Losso et al. 2012). This system was
tested in Sanremo (Imperia Province, Italy) for monitoring the fire risk areas and giving an
early warning message (e-mail or text message) in real time, when the algorithms detect a
high risk of fire. Nowadays, the European Forest Fire Information System (European
Commission JRC 2000), INSPIRE-compliant, is one of the few GIS applications, aiming at
the retrieval of the data from the whole process of fire-fighting. EFFIS GIS acquires, at this
moment, only the data (e.g. Risk index, hotspots and size of fire) involved in the fire risk
forecasting, and the fires occurred in Europe, using and integrating these historic data to
support decisions. Another case of a fully integrated and interoperable system for fire-
fighting management is the result of ArcFUEL
project (Bonazountas et al. 2012), which
adopts Global Technology standards at all operational layers (e.g. INSPIRE, OGC and
XML/GML). The aim would be providing and producing updated fuel maps to be used in
forest fire management operations and geoplatforms as ArcFIRE
(Mitsopoulos et al.
2014). However, despite these attempts, the use of standards is not so widespread: data
Nat Hazards (2018) 90:623–637 625
content and format are often not uniform, consistent, complete and compatible with the
available technologies.
Following a careful analysis of the existing tools, it is possible to notice that an inte-
grated central system is missing. Moreover, it should be underlined that the metadata of the
observed maps are almost never available, and it is impossible to determine the quality,
accuracy, last updating and further useful information about the data.
3 The design of a standard-compliant spatial data model for fire-fighting
The well-known rules for database modelling, as defined by the ANSI/X3/SPARC standard
(Laurini and Thompson 1992), were followed for designing the GIS.
An effective GIS has to consider all the phases of fire-fighting: prevention, prepared-
ness, fire response and recovery (Fig. 2; Neal 1997).
For fire prevention and preparedness aims, GIS should be used for risk analysis and for
supporting preventive activities and decisions. Considering these aspects, it is important to
integrate various data (e.g. past fires, fuel models and weather) and to simulate some
scenarios (Pausas and Ferna
˜oz 2012) also useful for forecasting activities (Vi-
valda et al. 2017a).
During emergencies, the GIS should be able to help in real-time mission planning,
activities management for fire-fighting, and rescue operations. Being designed as a decision
support system, it should also collect and provide information about network infrastructure,
buildings, number of people in danger, available water supplies and further useful data
involved in the analysis.
For the recovery phase, the system is a useful platform, where to store data of the
mission and update the fire registry. These functionalities are very important for fire
damage assessment and reconstruction planning.
The GIS proposed is composed of three main categories of objects: the competent
authorities and actors in the fire-fighting process (command); the land, intended as objects
that are both to be protected and to be considered in the fire-fighting operations, for various
Fig. 2 Schema of the life cycle stages in forest fire management
626 Nat Hazards (2018) 90:623–637
reasons (infrastructures where to move, water supply resources and so on); and a more
dynamic component describing the events (fire and hotspot) (Fig. 3).
The command entities are represented following the proposal of the project of having a
unique control centre (the command centre), which coordinates the human resources and
the performing operations. This would be a simplification of the actual state of things, since
the fire-fighting at present involves, for example in Italy, public and private authorities with
the hierarchical order in Fig. 4. Therefore, the proposal of a single command centre for the
coordination of activities and data processing is needed to optimize the management, the
data distribution, updating and use in emergency situations.
The command centre handles all the data from the local operations centres and is able to
direct both the teams moving in the air and the ones acting on the ground. The proposed
structure consists in a national unified command centre, that manages the forest moni-
toring, the fire emergencies and all the equipment for fire-fighting. It coordinates local
operating centres, which are responsible for the local resources management, and the
updating of the fires registry and the mission report. Finally, the operating teams handle
fire-fighting operations in the field (Fig. 5).
The INSPIRE data model provides fundamentals for completely defining the infor-
mation layers closely related to the land description (e.g. cadastral parcels, building,
exposed element and spot elevation), the event development (for instance, event registry
and event time) and the meteorological data (e.g. meteorological data and stations) (Burgan
et al. 1998; Han et al. 1992).
As previously mentioned, in Europe, a systematic fire model is missing, therefore an
approximation on the fuel models was realized, to improve our capacity of fire forecasting
and, consequentially, of fire-fighting management. It introduces some vegetation param-
eters (relative moisture, time lag and combustion heat) that are essential for modelling the
forest fire behaviour (Ager et al. 2011).
In the model, both static and dynamic entities, which are collected and produced during
the event (e.g. operating team locator or resources available), are included. These latter
entities allow the real-time data to be handled and the information to be uninterruptedly
updated. The tables are updated in the system through an SQL script, simulating the data
Fig. 3 The three objects categories for the external model development
Nat Hazards (2018) 90:623–637 627
provided by external data sources. A considered option for a real-time acquisition and
communication of the data could be the use of JSON files and protocols provided by the
external sources and employed sensors (Sriparasa 2013).
4 The standard data model extension and automatic schema generation:
the Model Driven Architecture (MDA) approach
To respond to requirements of interoperability and demands of integration among existing
systems and the developed system, the Model Driven Architecture (MDA) approach was
developed by OMG (Object Management Group) in 2001. MDA is enabled to development
through existing specification such as UML and XMI (Cephas Consulting Corp 2006).
Indeed, the Model Driven Architecture (MDA) approach allows the automatic trans-
formation from an UML diagram to a conceptual data schema script (Lisboa-Filho et al.
2013). More specifically, it allows to translate an object-oriented UML model (Platform
Independent Model, PIM) into an object-relational database model in PostgreSQL/PostGIS
(Platform Specific Model, PSM).
Enterprise Architect (hereafter EA) by Sparx Systems is the Computer Aided Software
Engineering (CASE) tool used to support the GeoDB implementation by means of this
approach. This software product is able to automate the construction of a suitable UML
(Unified Modelling Language) diagram, permitting the reuse and extension of the already
available schemas, to effectively design the database and exchange it through applications.
Thus, to generate an INSPIRE-compliant UML class diagram with interoperable data
formats, the INSPIRE UML profile and the INSPIRE repository are imported in EA. The
INSPIRE UML profile is an XML file containing the definition of each element present in
the UML diagram, essential to interpret its meaning by humans or machines (Kutzner and
Donaubauer 2012).
Using the INSPIRE Repository, INSPIRE classes (e.g. Metereological Data, Event-
Time, CadastralParcels, etc.), highlighted in the conceptual model (Fig. 5), were extracted
and imported into a new model. In order to extend the standard with some tailored features
for fire-fighting management, the procedure stated by the OGC as the best practice for
Fig. 4 Involved subject in fire event stages
628 Nat Hazards (2018) 90:623–637
extending the Open Geospatial Consortium (OGC) data model CityGML was used (Van
den Brink et al. 2012).
The physical structure of the DB was realized in a semi-automatic way, according to the
steps shown in Fig. 6.
The UML Class Model was converted in an XSD (XML Schema Definition) file through
the specific Enterprise Architect tool. It is suitable for being used as GML application
schema. Then, the XSD was imported and validated with Altova XMLSpy software (or
Fig. 5 UML conceptual model including the INSPIRE-compliant entities and their extension for fire-
fighting applications
Fig. 6 Procedure of implementation. The underlined passage (in grey) is the only manual step
Nat Hazards (2018) 90:623–637 629
equivalent open-source ones, such as XPad). During the validation process, the main
problem was the recognition of some data types. Indeed, the semantics, in XML format, are
different from INSPIRE. For example, the notation of text data type in XML schema is
xs:string, while in INSPIRE application schema, the same data type is defined by Char-
acterString. The only solution, in this case, was the manual editing.
Besides validating the XML application schema, which structures XML data, a tool,
integrated in the Altova XMLSpy software, converts the XML schema in an SQL script
with a set of Data Definition Langauge (DDL) commands. This is a mandatory procedure
in order to generate a relational model-compliant DB in a common SQL-based DBMS
The XML editor (in this case, Altova XMLSpy) automatically generates an Structured
Query Language (SQL) script that can be exported and used to automatically build the
structure of a conceptual model-compliant SQL database in a DBMS software.
5 GIS realization and filling-in in open-source software
As specified in the introduction, open-source software tools were preferred. In addition to
the above motivations, open-source software offers a major interoperability (since they can
easily employ open formats). Furthermore, they permit the access to the code and to the
connected libraries for the customization of some tools.
DBMS PosgreSQL, with its spatial extension PostGIS and the graphical interface
PgAdmin III, was used to manage the system (PostgreSQL 2016). Moreover, a connection
with Q-GIS was realized, with purpose to see the data.
PgAdmin III and SQL language allow the implementation of triggers and other func-
tions useful for data querying and analysing, and the realization of views for users and
different uses, and, the semi-automatic filling-in of the data.
To fill the database, the main difficulty is linked to the integration between national and
regional data structures and the data structure suggested by INSPIRE and used to create the
proposed GIS. Indeed, the provided data are often released as single shapefiles, and they
are not organized in a systematic database.
6 Test site and available data
In order to test the functionality of the proposed GIS, the data of Sardinia (Italy) are used.
In particular, the area of the Park of Sulcis, in the south-west of Sardinia, is considered.
For this specific area, several data were collected, as information about forests, fuel
models, hydrographical sources, roads and technological networks, command centre,
operating centres, teams, meteorological data, hotspots and alarms. Other data (e.g. event)
were not referred to real cases of forest fires, but they were hypothesized for testing the
Each data set was therefore converted according to the designed database structure.
630 Nat Hazards (2018) 90:623–637
7 A specific TRIGGER function for early warning
In order to allow a real-time monitoring, a trigger system was developed and included in
the platform. The triggers are ad hoc procedures for the automatic manipulation (insertion,
modification and deletion) of the information related to an event (Perry 1990). In this
study, a dedicated trigger devoted to initiate the sending of a first operation team on the
field when receiving the alarm is proposed (Fig. 7).
The trigger was built in SQL code. Analysing the single phases (Fig. 8): the event starts
due to an alarm (1). The alarm is given when the command centre is contacted, and some
data are communicated and inserted into the system, among which the fire location
(geographic coordinates) (Fig. 9); the system requires some variables to be defined as a
reference for performing the following steps (2). The database selects the Command Centre
in charge based on the field ‘‘country’’ where the alarm is given (3). Through the com-
putation of minimum (linear) distance (‘‘min distance’’ function), developed based on
coordinates of the alarm, the nearest Operating Centre is selected (4). The Operating
Centre sends the first Operating Team in field (TIF0) (5).
In order to exploit the advantages of such a GIS, different queries can be performed
where the goal was the automatic calculation of the number of fire-fighters to be sent on the
field. The variables considered by the automatic query are as follows: the class of fire, the
teams that are already in the field and the availability of further fire-fighters in the nearest
operating centres. A further parameter to be considered for calculating the number of
needed fire-fighters is the extension of the fire. This can be assessed also in real time
through some recently proposed methods (Vivalda et al. 2017b). At present, it is an
automatic but independent task; however, future work could permit to fill-in the needed
variables in the here proposed query with the fire extension forecasting results. Moreover, a
network of physical sensors communicating with the built GIS could give real data about
the development and extension of the fire.
Another interesting issue to be considered for determining the number of needed fire-
fighters would be the presence on the territory of some additional risks or elements that
could intensify or influencing the fire development (e.g. gas stations, nuclear plants and
However, since the objective of this study was the development of an expeditious
procedure and tools for fire management considering the whole Europe, these aspects,
dealing with a major detail in the analysis, will be further developed in future researches.
Fig. 7 Flow chart for developing alarm trigger
Nat Hazards (2018) 90:623–637 631
The query is composed by two iterative processes (the two loops), which finish only
when the number of men in the field is sufficient to fight the developing fire (and this last
one is no more increasing) (Fig. 10).
When the trigger in Fig. 7creates a new team (TIF0) after the alarm, a new event in
EventRegistry is inserted and the HotSpot coordinates are registered.
This query is used when a new update on EventTime table arrives to the Command
Centre. Generally, rises of Rate of Spread (ROS) and intensity of fire in EventTime
table produce a new request of fire-fighters (Andrews and Rothermel 1982). When the ROS
is constant or decreases the loop stops. To simplify the process, in this case, only the ROS
was considered. Therefore, the query takes into account the ROS of the Event and selects a
proper value of ‘‘class of Fire’’. The fires are classified considering the control problems on
Fig. 8 Alarm trigger SQL code
632 Nat Hazards (2018) 90:623–637
each kind of fire (Cesti 2002). As a consequence, it is possible to define the number of the
needed fire-fighters (NF).
Once the query is performed, the first loop updates the class of fire and checks if the
number of fire-fighters on the field (TIFt) is sufficient, compared with the needed fire-
fighters (NF). If the result is negative, the second loop starts, verifying if the fire-fighters
availability, in the nearest Operating Centres, allows to cover the request of support, and so
on considering the Operating Centres in order of their (linear) distance from the fire. The
loop stops when the request of support is totally covered. The query, in this way, updates
Operating Centre Resources and allows to know who is on field, how many men, and
when, they are involved in the fire management. The time saved by means of such tool is
very precious in an emergency case.
8 Conclusion
In the paper, a standard-compliant and integrated GIS was proposed, as the core part of a
more complex system for ‘‘big fire prevention and management’’, an SDI able to support
prevention, preparedness, emergency response and recovery phases of the fire-fighting
process. It can support early warning systems, the integrated management of historic data
and dynamic information, which is a critical challenge, especially when considering the
intensification of fire phenomena, because of the climate changes, and when it comes to the
so-called mega-fire. It is aimed at filling the existing gap in the fire-fighting process, in the
integration of a very heterogeneous information (multiplicity of procedures, used data
formats, used data sources and so on). The cartographic and territorial data very often do
not comply with shared standards, so they suffer from a limited interoperability. This study
proposes a solution by means of the interoperability technologies, developed in a ‘‘smart’
Fig. 9 Trigger in Q-GIS (the numbers refer to the trigger steps in Fig. 7, and the output of them is
underlined in the green squares): (1) input of the alarm position in the system, (4) selection of nearest
operating Centre based on ‘‘min distance’’ function, (5) creation of new operating team (TIF
). The TIF
position would be surveyed and mapped during the operations through navigation sensors communicating to
the system. The numbers refer to the SQL code described in Fig. 8
Nat Hazards (2018) 90:623–637 633
A great advantage of the proposed system is the use of the available reference standards
for structuring the data and the metadata referring both to the cartographic side (land shape,
land coverage and use, network and infrastructures, etc.) and to some thematic environ-
mental or monitoring data. This makes the system completely compatible and
importable by states having INSPIRE-compliant digital maps, as should be in the near
future, for states having adopted the INSPIRE Directive (the whole Europe). Being the
INSPIRE data model structured in form of a very general and application-independent
ontology, it could be probably exported to further regions with effective results.
Fig. 10 Schema of the query workflow. The SQL code of the query is shared at the link http://areeweb.
634 Nat Hazards (2018) 90:623–637
Furthermore, the inclusion of dynamic data, historic data registry and similar information
can be an effective support to advanced analysis, to be performed directly in the GIS
Another contribution of the presented study is the effort to improve the automaticity in
the conversion of the (in this case extended) conceptual model into the internal model. In
this way, during the transformation from an object-oriented UML class diagram to the
object-relational PostgreSQL/PostGIS database, the data formats and semantics defined by
INSPIRE are preserved. A modelling phase in Enterprise Architect was employed for
defining the extension, which is already affirmed practice in the community. On the other
hand, while the use of an MDA approach is probably affirmed in the informatics field, for
geomatics and cartography management goals, it has to be refined and tested. Although
being an essential part of the generation of the now unavoidably standard-compliant
geodatabases, an optimized procedure implementing is not fully integrated in the software
Finally, an innovation of the system is linked to the specific application field. The more
critical limit is the lack of integrated and harmonized procedures, solutions and data for
common analysis and optimized management of the entire command chain in interventions
for fire-fighting. In the functioning of the GIS, a solution was hypothesized considering a
unique control centre holding the task of coordination and management, and distributing
responsibilities and mission instructions to decentred bases, able to act. A more definitive
solution should be obviously proposed by the entities directly involved in the fire-fighting
application field.
A great part of the system was based on the open-source system, but some tools are only
available under shareware software, which still limits sometimes the full understanding of
some processing.
In future work, the proposed platform should be tested in collaboration with the actual
operators intervening in the fire-fighting. Moreover, the implementation of automatic
procedures should be improved. A fundamental part of such automatic procedures should
regard the fire alarm, which could be given by automatic physical sensors positioned in
especially vulnerable areas (as evaluated by experts). In this way, an effective sensor
network architecture, following the Internet of Thing paradigm, could be exploited and
integrated in the proposed tool (Gubbi et al. 2013; Arco et al. 2016). A fundamental
development will be the publication of such system as webGIS or as part of a more
complex SDI.
Acknowledgements The study was realized on the themes treated in the European project AF3 (Advanced
Forest Fire Fighting— The authors would like to thank the CVVFF of Cagliari for their
availability and data sharing. Furthermore, they thank Dr. Raffaella Marzano from University of Torino for
her help about fuel model and forest type and Dr. Cesti for his availability.
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... Cartographic data harmonization (Grasso et al. 2018) IS standardization (Granell and Ostermann 2016;Steinhäusler, Friedrich Hällström et al. 2018; Information from unstructured data (Chaniotakis et al. 2017;Weiler et al. 2017) Creation of canonical bodies of knowledge (Granell and Ostermann 2016) Creating data-driven firefighting support (Song et al. 2017) Another EU-wide initiative is SAYSO. SAYSO has been initiated in mid of 2017 and should be completed in 2019. ...
... TrendsINSPIRE(Grasso et al. 2018), Digital plan(Weidinger et al. 2018), OpenFireMap, Fireboard SAYSO(Steinhäusler, Friedrich Hällström et al. 2018;, Firebrary(Spaling et al. 2018), on-site IS(Weidinger et al. 2018) Twitter model(Chaniotakis et al. 2017), twitcident, event detection(Weiler et al. 2017) Firebrary(Spaling et al. 2018) Econometric model(Song et al. 2017) ...
... Challenges and Trends of Data Management in FirefightingINSPIRE(Grasso et al. 2018), Digital plan(Weidinger et al. 2018), OpenFireMap, Fireboard IS standardization(Granell and Ostermann 2016;Steinhäusler, Friedrich Hällström et al. 2018; ...
Conference Paper
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For successful firefighting, information is key. In this work, a general overview of the current challenges and trends of data management for firefighting in Germany and the Netherlands are examined. This was accomplished by conducting a literature review to find out the current state-of-the-art in research. The results of the literature review are then compared with expert sentiments and gaps between research and practice are revealed. Through the review, six challenge categories are identified: cartographic data harmonization, IS standardization, information gathering from unstructured data, canonical bodies of knowledge, and data-driven firefighting support. The challenges and trends are discussed in the context of Germany and the Netherlands and significant differences are presented. Lastly, the gaps between research and practice are thoroughly analyzed and potentials for future work revealed.
... GRASSO ET AL. additionally propose a method to design and implement a GIS that fulfills the standards of INSPIRE. The proposed GIS comprises the three major object categories command, land and event which are represented in an INSPIRE-compliant UML model ( Grasso et al. 2018 p. 629). ...
... Cartographic data harmonization (Grasso et al. 2018)IS standardization (Granell and Ostermann 2016;Steinhäusler, Friedrich Hällström et al. 2018;Information from unstructured data (Chaniotakis et al. 2017;Weiler et al. 2017)Creation of canonical bodies of knowledge (Granell and Ostermann 2016)Creating data-driven firefighting support (Song et al. 2017) ...
Conference Paper
For successful firefighting, information is key. In this work, a general overview of the current challenges and trends of data management for firefighting in Germany and the Netherlands are examined. This was accomplished by conducting a literature review to find out the current state-of-the-art in research. The results of the literature review are then compared with expert sentiments and gaps between research and practice are revealed. Through the review, six challenge categories are identified: cartographic data harmonization, IS standardization, information gathering from unstructured data, canonical bodies of knowledge, and data-driven firefighting support. The challenges and trends are discussed in the context of Germany and the Netherlands and significant differences are presented. Lastly, the gaps between research and practice are thoroughly analyzed and potentials for future work revealed.
... Relevant related objects, factors and phenomena can be represented: the position of the heritage in the city or landscape, related transport network and accessibility, relation to other buildings or spaces and so on, including the connection to potential risk factors. Other studies successfully apply in its place GIS technologies to the risk prevention and management field (Grasso et al., 2018;Chen et al., 2001;Assilzadeh et al., 2010) as well as to heritage representation (x 1.1). However, there is a gap in the current research about the representation of risk and hazard parameters of cultural heritage (CH) and built environment in a complete and interoperable spatial database. ...
... Relevant related objects, factors and phenomena can be represented: the position of the heritage in the city or landscape, related transport network and accessibility, relation to other buildings or spaces and so on, including the connection to potential risk factors. Other studies successfully apply in its place GIS technologies to the risk prevention and management field (Grasso et al., 2018;Chen et al., 2001;Assilzadeh et al., 2010) as well as to heritage representation (x 1.1). However, there is a gap in the current research about the representation of risk and hazard parameters of cultural heritage (CH) and built environment in a complete and interoperable spatial database. ...
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Purpose The study, within the Increasing Resilience of Cultural Heritage (ResCult) project, aims to support civil protection to prevent, lessen and mitigate disasters impacts on cultural heritage using a unique standardised-3D geographical information system (GIS), including both heritage and risk and hazard information. Design/methodology/approach A top-down approach, starting from existing standards (an INSPIRE extension integrated with other parts from the standardised and shared structure), was completed with a bottom-up integration according to current requirements for disaster prevention procedures and risk analyses. The results were validated and tested in case studies (differentiated concerning the hazard and type of protected heritage) and refined during user forums. Findings Besides the ensuing reusable database structure, the filling with case studies data underlined the tough challenges and allowed proposing a sample of workflows and possible guidelines. The interfaces are provided to use the obtained knowledge base. Originality/value The increasing number of natural disasters could severely damage the cultural heritage, causing permanent damage to movable and immovable assets and tangible and intangible heritage. The study provides an original tool properly relating the (spatial) information regarding cultural heritage and the risk factors in a unique archive as a standard-based European tool to cope with these frequent losses, preventing risk.
... On the other hand regression analysis that gives good results even for smaller datasets is one of the most widely used statistical processes for estimating the relationships among variables influencing fire. GIS, along with exploratory data analysis, simulation, and interpolation, provides more insights into the causes of fire events (Grasso et al. 2018). (Zhang et al. 2018) presented a global linear regression model to unveil information about spatial variations in urban fire occurrences using road density as a factor. ...
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The article aims to analyze the various causes and relationships of fire with the urban pattern. Various spatial analytics and geostatistical techniques are applied to reveal spatiotemporal variations in the datasets. The novel machine learning framework models important variables identified by random forest technique as predictors to develop GWR models. The framework is applied to establish the relationship between fire vulnerability and urban patterns for two periods (day and night) for the southern region of Mumbai city. We found that the urban pattern has a strong relationship with fire vulnerability, especially during the day time. High R-square values of 0.9086 and 0.7448 are achieved for the day and night periods, respectively. Further, significant differences in the influence of the predictors is observed during the periods. As cities are becoming more prone to fire, this study has the potential to help decision-makers with proactive measures over time and space.
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Wildland fires have been a rising problem on the worldwide level, generating ecological and economic losses. Specifically, between wildland fire types, uncontrolled fires are critical due to the potential damage to the ecosystem and their effects on the soil, and, in the last decade, different technologies have been applied to fight them. Selecting a specific technology and Decision Support Systems (DSS) is fundamental, since the results and validity of this could drastically oscillate according to the different environmental and geographic factors of the terrain to be studied. Given the above, a systematic mapping was realized, with the purpose of recognizing the most-used DSS and context where they have been applied. One hundred and eighty-three studies were found that used different types of DSS to solve problems of detection, prediction, prevention, monitoring, simulation, administration, and access to routes. The concepts key to the type of solution are related to the use or development of systems or Information and Communication Technologies (ICT) in the computer science area. Although the use of BA and Big Data has increased in recent years, there are still many challenges to face, such as staff training, the friendly environment of DSS, and real-time decision-making.
This paper describes an exploration process aligned with the core domain of Service Science inside a critical sector of Society, aiming at developing City in a sustainable, responsible, inclusive way. The paper focuses on defining the Public Safety as a Service concept in an inclusive and responsible value co-creation urban design vision for liveable cities. It explains how service intelligence can act on immaterial artefacts to transform data into information to generate value co-creation processes whose outcomes are applied to the evolution of knowledge in public safety services. Public safety is approached within a service ecosystem perspective, following the global targets of the Sendai Framework for Disaster Risk Reduction as an application perspective. Managerial implication are approached from two perspectives: establishment of governance principles with the help of Elinor Ostrom’s works, and a Viable Systems Approach on the response to disasters operating rules.
Technical Report
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Executive Summary In 2015, 376 natural triggered disasters were registered. After the lowest number since the beginning of the century in 2014 (330), this increase could be a sign of a reversal in the trend to decline in the annual number of disasters since 2005, even if the 2015 number remains below its average annual for the period 2005-2014 (380). Last year natural disasters made still 22,765 deaths, a number largely below the annual average for years 2005-2014 (76,416), and made 110.3 million victims worldwide, also below the 2005-2014 annual average (199.2 million) (see Figure 1). Like the other indicators, with estimates placing economic damages at US$ 70.3 billion, natural disasters costs were, in 2015, significantly below their decennial average of US $ 159.7 billion. The increase in the number of reported natural disasters in 2015, was mostly due to a higher number of climatological disasters: 45 compared with the 2005-2014 annual average of 32, an increase of 41%. The number of meteorological disasters (127) was 2% above its decadal average (125) while, inversely, the number of hydrological disasters (175) and of geophysical disasters (29) were, both, 9% below their 2005-2014 annual average of, respectively, 192 and 32. As each year since 2005, the number of hydrological disasters still took by far the largest share in natural disaster occurrence in 2015 (46.5%, for a mean proportion of 50.6% for the period 2005-2014), followed by meteorological disasters (33.8% versus a decadal mean proportion of 32.7%), while climatological disasters (12% versus an annual mean proportion of 8.3%) overpassed geophysical disasters (7.7% for a 2005-2014 mean proportion of 8.4%) Over the last decade, China, the United States, India, the Philippines and Indonesia constitute together the top 5 countries that are most frequently hit by natural disasters. In 2015, with 36 natural disasters reported, China experienced its third highest number of natural disasters of the last decade, 20% above its 2005-2014 annual average of 30. The country was affected by a variety of disasters types, including 17 storms, 13 floods and landslides, 5 earthquakes and one drought. The number of natural disasters in the United States (28) was as high as in 2013, and 33% above its decadal annual average of 21. With 21 disasters, its third highest number since 2005, India is 24% below its 2005-2014 annual average of 27. Inversely, with respectively 15 and 10 natural disasters, the Philippines and Indonesia knew their 4th and 2nd lowest numbers since 2005, below their respective annual average of 18 and 14. In 2015, the number of people killed by disasters (22,765) was the lowest since 2005, way below the 2005-2014 annual average of 76,416 deaths which, however, takes into account two years with more than 200,000 people reported killed, each time mostly attributable to major catastrophes: the cyclone Nargis in Myanmar in 2008 (138,366 deaths) and the earthquake in Haiti in 2010 (225,570 deaths). But even after exclusion of these disasters, the number of deaths in 2015 remains below a recomputed 2005-2014 annual average of 40,022 deaths. At a more detailed level, it appears that, in 2015, earthquakes and tsunamis killed the most people (9,526) however far below a 2005-2014 annual average of 42,381. Extreme temperatures made 7,418 deaths, the second highest number since 2005 but far below the peak of 2010 (57,064). Inversely, the number of deaths from floods (3,449) and storms (1,260) were, both, the lowest since 2005, far below their 2005-2014 annual averages (5,933 and 17,769, respectively). Amongst the top 10 countries in terms of disaster mortality in 2015, six countries are classified as low-income or lower-middle income economies (see World Bank income classification), and accounted for 67.6% of global reported disaster mortality. Four disasters killed more than 1,000 people in 2015: the Gorkha earthquake in Nepal of April (8,831 deaths) and three heat waves in France between June and August (3,275 deaths), in India in May (2,248 deaths) and in Pakistan in June (1,229 deaths). The number of victims in 2015 (110.3 million) was the second lowest since the decade, far below its 2005-2014 annual average (196.3 million). It must be noted that the four years with the lowest number of victims since 2005 are the four last years, 2012 to 2015, far below the 200 million victims reported between 2007 and 2011. This decrease is mainly explained by the lower human impact of floods, whose number of victims (36.1 million) was the second lowest since 2005, 58.4% below its 2005-2014 annual average (86.9 million) and of storms with a number of victims (10.4 million) 70.2% below its decade’s average (34.9 million). The number of victims of climatological disasters (54.3 million) was near its 2005-2014 average (56.7 million). Geophysical disasters made 8.1 million victims, a number lightly below the 8.6 million annual average, but however the second highest since 2005, after the very high peak of 2008 (47.7 million). Nine countries of the top ten countries in terms of number of victims were low or lower-middle income countries, accounting for 69.9% of the victims of 2015. The natural events that accounted for more than 10 million victims were two droughts in DPR Korea in June and July (18 million victims) and in Ethiopia, from September (10.2 million) and floods in India in July and August (13.7 million). Twenty other disasters (10 droughts, 5 floods, 4 storms and one earthquake) had severe human impacts ranging from 1 to 9 million victims. The estimated economic losses from natural disasters in 2015 (US$ 70.3 billion) was the third lowest since 2005 and 56 % below the annual 2005-2014 damages average (US$ 159.8 billion). The lowering in the amount of damages come from geophysical (US$ 6.7 billion; -86.0% compared to the 2005-2014 average), meteorological disasters (US$ 33.4 billion; -51.7% compared to the 2005-2014 average) and hydrological disasters (US$ 21.3 billion; -38% compared to the 2005- 2014 average). Damages from earthquakes were the second lowest since 2005, and represent 8.7% of all disaster costs. Those from storms and floods were, both at their third lowest since 2005, contributing, respectively, to 47.4 and 30.3% of all disaster costs. These three disaster types are at the origin of almost all these costs. On their side, damages from climatological disasters (US$ 8.9 billion) were, in 2015, very near their 2005-2015 annual average (US$ 8.8 billion), however if in this disaster category, damages from droughts and from wildfires were, both, the fourth lowest since 2005, costs of droughts (US$ 5.8 billion) were slightly below their decadal average (US$ 6.4 billion) while those from wildfires (US$ 3.1 billion) were 27.9% above their 2005- 2014 annual average. In the top ten countries for economic damages, six were high or upper-middle income countries which accounted for 70.7% of the total economic losses while the share of the four low and lowermiddle income countries in this total was of 17.6%. The costliest natural disaster in 2015 was the Gorkha earthquake, in Nepal, which cost US$ 5.7billion to the country, while typhoon Mujigae impacted China for a total of US$ 4.2 billion economic losses. Twenty-one other disasters (9 storms, 7 floods, 3 droughts and 2 wildfires) accounted for damages ranging from US$ 1 to 3 billion. The total costs of these 23 disasters represent 61.2% of all reported damages in 2015. Looking at the distribution of disasters across continents, it appears that Asia was most often hit (44.4%), followed by the Americas (25.5%), Africa (16.5%), Europe (7.2%) and Oceania (6.4%). This regional distribution of disaster occurrence is, in 2015, not very different from the profile observed between 2005 and 2014. However, the share of Europe in the distribution is half its 2005-2014 mean proportion, while the share of Oceania is, in 2015, twice its average. Asia accounted in 2015 for 62.7% of worldwide reported disaster victims (against 80.6% for the 2005-2014 decade’s average), while Africa accounted for 28.0% (against 13.1% on average for the 2005-2014 period) and the Americas for 7.0% (against 5.8% on average for 2005-2014). Oceania accounted for 2.2% of all natural disasters victims (against 0.1% for 2005-2014 average) and Europe for only 0.21% (against 0.35% according to the 2005-2014 average). With 49.1% of worldwide natural disaster reported costs, Asia suffered the most damages in 2015, followed by the Americas (36.7%) and Europe (6.8%). A share of 5.1% of global disaster damages was reported for Oceania and of 2.4% for Africa. In spite of some differences in the proportions, the ranking of the continents according to their contribution to the total reported damages is similar from the one observed over the last decade, where Asia had the most damages, followed by the Americas and Europe. However, when compared to its 2005-2014 average, the amount of damages in Africa was significantly above its 2005-2014 annual average of 0.34%. EM-DAT’s global approach to the compilation of disaster data continuously provides us with valuable information and trends on the occurrence of natural disasters and their impacts on society. However, the development of guidelines and tools for the creation of national and subnational disaster databases; for the compilation of standardized, interoperable disaster occurrence and impact data remain priorities for the strengthening of tools helping to benchmark and orientate effective disaster risk reduction programs.
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Air quality is a factor of primary importance for the quality of life. The increase of the pollutants percentage in the air can cause serious problems to the human and environmental health. For this reason it is essential to monitor its values to prevent the consequences of an excessive concentration, to reduce the pollution production or to avoid the contact with major pollutant concentration through the available tools. Some recently developed tools for the monitoring and sharing of the data in an effective system permit to manage the information in a smart way, in order to improve the knowledge of the problem and, consequently, to take preventing measures in favour of the urban air quality and human health. In this paper, the authors describe an innovative solution that implements geomatics sensors (GNSS) and pollutant measurement sensors to develop a low cost sensor for the acquisition of pollutants dynamic data using a mobile platform based on bicycles. The acquired data can be analysed to evaluate the local distribution of pollutant density and shared through web platforms that use standard protocols for an effective smart use.
Domain engineering is a set of activities intended to develop, maintain, and manage the creation and evolution of an area of knowledge suitable for processing by a range of software systems. It is of considerable practical significance, as it provides methods and techniques that help reduce time-to-market, development costs, and project risks on one hand, and helps improve system quality and performance on a consistent basis on the other. In this book, the editors present a collection of invited chapters from various fields related to domain engineering. The individual chapters present state-of-the-art research and are organized in three parts. The first part focuses on results that deal with domain engineering in software product lines. The second part describes how domain-specific languages are used to support the construction and deployment of domains. Finally, the third part presents contributions dealing with domain engineering within the field of conceptual modeling. All chapters utilize a similar terminology, which will help readers to understand and relate to the chapters content. The book will be especially rewarding for researchers and students of software engineering methodologies in general and of domain engineering and its related fields in particular, as it contains the most comprehensive and up-to-date information on this topic.
The use of disaster phases (e.g., preparedness, response, recovery, and mitigation) has assisted both disaster researchers and managers. Disaster researchers have used disaster phases to systematize and codify research results. Disaster managers have drawn upon disaster periods to organize their own activities. Yet, many problems exist with the current use of disaster periods. In summary, I find that the current uses of disaster periods lack conceptual clarity for improving scientific and practical use. As a result, I suggest ways the field can recast the use of disaster phases to improve the theoretical and applied dimensions of the field.
After many years of research in the field of conceptual modeling of geographic databases for Geographic Information Systems, experts have produced many different alternatives of conceptual data models from extensions of the Entity- Relationship model or of Unified Modeling Language (UML). However, the lack of consensus on which is the most suitable one for modeling applications in the geographical domain, brings up a number of problems for field advancement, mainly problems of interoperability of database design and CASE tools. The Model Driven Architecture (MDA) approach allows the development of systems from an abstract view until the corresponding implementation code that can be automatized by means of models transformation. A UML Profile is an extension mechanism of UML which allows a structured and precise extension of its constructors, being a good solution to standardize domain-specific modeling, as it uses the entire UML infrastructure. This chapter describes the use of MDA approach in the design of databases in geographical domain; using a UML Profile called GeoProfile aligned with international standards of ISO 191xx series. The chapter also shows that with the automatic transformation of models it is possible to achieve the generation of scripts for spatial databases from a conceptual data schema in a high level of abstraction.
Conference Paper
ArcFIRE™ is a state-of-the-technology Integrated Wildland and Forest Fire Management Geoplatform under constant technology evolution since 1990, progressed at high-tech institutions of international competence, but also withdrawing on US Forest Service modelling technologies. The Geoplatform captures the vital dynamics demanded by Planers and Decision Makers engaged in the Forest Fire Life Cycle. ArcFIRE™ has been used in numerous operational tactics in France, Greece, Italy, Spain, Portugal and other countries. It is worth noting that practically all forest fire management activities require a good assessment of vegetation cover in the management area in the form of a fuel map. It is widely recognized that the availability of updated and accurate fuel cover maps is one of the limitations for fire prevention plans, fire spread simulation and for recovery plans. ArcFUEL™ is a LIFE+ Project that involves six European Partners with the objective of producing updated fuel maps to be used in forest fire management operations and geoplatforms as ArcFIRE™. This paper outlines the: (i) usage of ArcFIRE™ as an Integrated Wildland and Forest Fire Management Geoplatform for the four phases of the Forest Fire Management Cycle: Awareness (Preparedness/Prevention), Emergency, Impacts and Dissemination, (ii) technology used for its development, (iii) architecture implemented, (iv) methodology of production fuel cover maps based on satellite data and field validation to fulfil the needs of local, regional or national users. Modelling, Monitoring and Management of
Rate of spread, heat per unit area, flame length, and fireline intensity are plotted on a fire behavior chart. Spread component, energy release component, and burning index are plotted on a National Fire Danger Rating System chart. -from Authors