=Paper=
{{Paper
|id=Vol-1152/paper48
|storemode=property
|title=DSS Applications In Forest Policy and Management: Analysis of Current Trends
|pdfUrl=https://ceur-ws.org/Vol-1152/paper48.pdf
|volume=Vol-1152
|dblpUrl=https://dblp.org/rec/conf/haicta/AthanasiadisA11
}}
==DSS Applications In Forest Policy and Management: Analysis of Current Trends==
https://ceur-ws.org/Vol-1152/paper48.pdf
DSS applications in forest policy and management:
Analysis of current trends
Antonios Athanasiadis1, Andreopoulou Zacharoula1
1
Aristotle University of Thessaloniki, School of Forestry and Natural Environment,
Laboratory of Forest Informatics, Box 247, 54124 Thessaloniki, Greece,
tel. 2310.992714, 2310.992327/fax. 2310.992717,
e-mail: antatha@for.auth.gr, randreop@for.auth.gr
Abstract. Today, not only scientists and researchers, but public services and
governments as well use DSS (Decision Support System) methods to solve
forest policy and management problems in order to meet the multiple needs of
the public and to achieve the greatest possible effectiveness. This paper
presents and analyses the current trends in emerging DSS applications for the
sector of forest policy and management. The research relates to the scientific
journal articles that propose a DSS since 2007 and until the present. The DSS
are registered and classified as to their characteristics, such as their decision
support topic, multiple-aim DSS, country of application, type of software,
database use, GIS, mathematics, online presentation in the Internet etc. Finally
the DSS applications are categorized as to the above characteristics and current
trends are identified and discussed. GIS and Database technology seem to be
the most popular software used by the decision makers, since Europe North
America emphasize most in these kind of DSS applications.
Keywords: Decision Support Systems, forest policy, forest management,
current trends,
1 Introduction
Information Systems researchers and technologists have built and investigated
Decision support systems (DSS) for approximately 40 years. Computerized decision
support systems became practical with the development of minicomputers, timeshare
operating systems and distributed computing. Ferguson and Jones (1969) reported the
first experimental study using a computer aided decision system. The authors have
developed and conducted experiments with a time-sharing computer model. By
modeling the dynamics of a job shop the authors were able both to make use of and
to evaluate academic research in job shop scheduling. The response of over 300
managers and academicians who have participated in the experiments provides
evidence of the practicality of such an approach to multi-dimensional, time-variant
problem solving.
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549
There are many valid definitions regarding DSS. DSS have been initially defined
as “…computer-based support system for the management decision makers who deal
with semi -structured problems” (Keen and Morton 1978). Decisions are courses of
action that are taken to avoid or reduce negative effects, or to take advantage of
opportunities (Mc Leod 1998). It is a content-free expression; that is, it means
different things to different people (Turban and Aronson, 1998) meaning that a
D.S.S. interacts with the user in order to provide decisions. Recently, DSS are
defined broadly as interactive computer-based systems that help people use computer
communications, data, documents, knowledge, and models to solve problems and
make decisions (Power, 2007). In this paper DSS are approached as a tool, available
to managers, for solving complicated environmental problems by aiding in the
decision making process.
The decision maker has to consult many factors and data in order to provide the
best possible solution to a problem. According to Burstein and Holsapple (2008) the
DSS relaxes cognitive, temporal, spatial and economic limits on the decision maker,
since the support furnished by the system allows a decision episode to unfold:
x in more-productive ways (e. g., faster, less expensively, with less effort),
x with greater agility (e. g., alertness to the unexpected, higher ability to
respond),
x innovatively (e. g., with greater insight, creativity, novelty, surprise),
x reputably (e. g., with higher accuracy, ethics, quality, trust), and/or
x with higher satisfaction by decisional stakeholders (e. g., decision
participants, decision sponsors, decision consumers, decision
implementers)
Today a number of academic disciplines provide the substantive foundations for
DSS. Database systems provide tools on managing data; management science has
developed mathematical models for use in building model-driven DSS, whilst some
other important fields related to DSS are human-computer interaction, software
engineering and telecommunications. Further, the Internet and Web have precipitated
the development of the DSS through Information and Communication Technologies
(ICTs) and its applications that act as providers of a great amount of information and
services related to all sectors of science (Andreopoulou, 2006).
Based upon Alter’s (1980) pioneering research we can identify the following three
major characteristics: DSS are designed specifically to facilitate decision processes,
DSS should support rather than automate decision making and DSS should be able to
respond quickly to the changing needs of decision-makers.
In persuing the goal of improving decision-making, many different types of
computerized DSS have been built to help decision teams and individual decision
makers. Power and Sharda (2009) point that some systems provide structured
information directly to managers. Other systems help managers and specialists
analyze situations using various types of quantitative models, some DSS store
550
knowledge and make it available to managers and some systems support decision
making by small or large groups.
1.1 DSS in forest management and policy
Today, Forestry has to resolve a number of issues and to find effective ways to deal
with the ecological and social problems that act, in many ways, as a threat to the
environment and the people. Such issues that forestry is confronting are: forests fires,
land use, wildlife protection, reforestation, wind damages, illness and infection
damages, infringement of the forest law and many others. In general, the major issue
is the protection and conservation of the natural environment in a way that builds an
intercourse between the people and the environment.
In our days, the definition of forest has been changing towards a wider range of
qualitative characteristics and it is defined as an ecosystem that combines
simultaneously various land uses (Helms, 2002). Modern forestry mostly focuses on
environmental sustainability of the ecosystems in relationship to the citizens as a
result of the current change in both urban and rural areas (Andreopoulou, 2007).
Forests and especially urban forests are considered to be the most popular outdoor
recreation environments in Europe underlying the changing role of forestry through
time (Konijnendijk et.al., 2000).
The multiple functions of forests imposes the existence of several tasks that have
to be dealt in parallel and formulate the forest policy aspects such as forest
management, wood production, forest and wild life protection, forest technical
constructions, treatments, reforestations, forest recreation, land-use legal conflicts
administration and economics (Tasoulas et.al., 2011).
Today, not only scientists and researchers, but public services and governments as
well use DSS methods to solve forest policy and management problems in order to
achieve the greatest possible effectiveness. Geographical Information Systems (GIS),
Database technology, Mathematics, Economics, Chemistry, Internet and software
engineering, are only some of the tools used and combined by the researchers with a
view to create a DSS for an individual issue. Moreover, DSS provide an interesting
framework to integrate database management systems with analytical and operational
research models, graphic and tabular reporting capabilities to assist in natural
resources management and policy analysis (Borges et al., 2003; Reynolds et al.,
2005, 2008).
It is appreciated in recent research (Andreopoulou, 2009, 2011) that the use of IT
tools is the only process to meet the extended needs of forests and in parallel, to
protect forest ecosystems. This paper presents an analysis of the current trends in
emerging DSS applications in forest policy and management sector through their
registration and classification. The aim of the presented research project is to inform
about the current trends in DSS regarding these issues, in order to service further
scientific research.
551
2 Methods and material
Aiming to identify the current trends in DSS in the sector of forest management
and policy, an analytical review of the articles of relative scientific journals has been
performed, in order to register them. There has been a research among the web bases
of the most known journals (High Impact factor) that deal with forest policy and
management and DSS applications, detecting related journal articles for the period
2007-2011. As we can see in Figure 1, the findings were registered and classified
using “EndNote X4”, which is reference manager software.
Fig. 1. Endnote Library
The DSS applications were registered and various characteristics have been
studied aiming to be further classified. The characteristics studied are:
-the specific topic that the DSS deals with such as forest fires, land use, ecosystem
protection, forest planning, etc ,
-if they constitute a multiple-purpose DSS or not,
-the country or the area of DSS application,
-the type of software used to develop the DSS,
-the employ of database,
-the use of GIS technology,
-the existence of mathematic analysis, such as linear programming,
-online presentation and exploitation of the DSS in the Internet etc.
The classification as to their characteristics was accomplished with an Ms-excel
sheet (Fig. 2).
Finally the DSS applications are categorized as to the above characteristics and
current trends are identified and discussed.
552
Fig. 2. Registration and classification of the findings in Microsoft Excel
3 Results
This survey concerns published journal articles derived from 9 individual scientific
journals. There were identified and registered 46 emerging DSS applications for the
sector of forest management and policy since 2007.
In a percentage of 43, 5% they constitute a multiple-purpose DSS as they apply to
more than one specific topic of forest management and policy and can be adopted
and support decision making widely.
As it concerns the specific topics that DSS applications deal with, there were
identified 14 different topics. 15% of the findings relate to forest fires, 15% to forest
management in general and 11% to ecosystem protection as it is presented in figure
3.
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WATER RESOURCES 4,35
TREE PLANTING 4,35
FINANCIAL UTILIZATION 6,52
OTHER 8,70
TREE DISEASES 8,70
SUSTAINABLE DEVELOPMENT 8,70
LAND USE 8,70
FOREST PLANNING 8,70
ECOSYSTEM PROTECTION 10,87
FOREST MANAGEMENT 15,22
FOREST FIRES 15,22
0 2 4 6 8 10 12 14 16
Fig. 3. Topics of the DSS applications in the sector of forest management & policy (%)
Regarding the country-area of the DSS application, a geographical allocation
arises in figure 4. As it is obvious the DSS applications identified are mainly targeted
to Europe and America. It is important to underline that 17 out of the 21 journal
articles found in America, came from the USA and Canada and also apply to these
countries. Further, the European DSS applications refer to EU nations except for one,
which applies to Switzerland.
As far as the type of software used to develop the DSS, 18 out of 46 DSS used
Database technology, 25 were based on GIS (Geographical Information System)
applications and only four introduce a web DSS application available in the internet.
Moreover, 37% of the total findings regard to DSS based on a combination of
existing software applications and with the aim of programming languages and other
software engineering, they present a prototype software as a decision making tool.
Researchers are mostly using Visual basic (C++, NET), SPSS and Java script.
Last but not the least, 50% of the DSS applications seems to have processed
mathematical data in order to achieve the desirable result and to present a reliable
outcome.
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9% 2%
AMERICA
46%
EUROPE
ASIA
43% AFRICA
Fig.4. Geographical allocation of the DSS applications
4 Discussion
According to the results of this study, the current trends in the DSS in the sector of
forest management and policy refer to implementation of geographically based data,
through GIS software, which collaborates effectively with database technology. This
kind of combination is considered to be so successive that 43 out of 46 DSS
applications, registered in this survey, are using either GIS or Databases, whilst 12 of
them are using a combination of both. It is also remarkable that this trend applies
almost to the total of topics of DSS that were mentioned above. Particularly
databases were applied in 10 out of the 14 topics recorded in this research, since GIS
was the basic software for 11 DSS topics of the forest management sector.
The DSS applications identified are mainly targeted to Europe -especially to EU
member nations- and the USA and Canada. This fact proclaims the interest that these
countries show to the protection of the environment and their intention to study and
establish new methods of managing forestlands. Northern states of the USA and
mostly Canada maintain enormous forest areas and not only local institutes and
scientists precisely work on these issues, but the governmental policy seems to
encourage this trend.
As far as the European Union, European commission’s effort to establish a
common framework of managing the natural environment, is offering opportunities
and possibilities to Universities and independent scientists to study upon these
sectors of environmental sciences and to recommend computerized systems to aid
critical decision making.
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