E-praxis: A web-based forest law decision support system for land characterization in Greece

Forest Policy and Economics 103 (2019) 157–166

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E-praxis: A web-based forest law decision support system for land characterization in Greece☆

T

Antonios Athanasiadis , Zacharoula Andreopoulou ⁎

Aristotle University of Thessaloniki, Faculty of Forestry and Natural Environment, Laboratory of Forest Informatics, Box 247, 54124 Thessaloniki, Greece

ARTICLE INFO

ABSTRACT

Keywords: Greek forest law Web-based decision support system Land characterization Forest service Rule-based reasoning

This paper presents “e-praxis”, a Web-based Decision Support System (DSS), to assist the land Characterization Acts (CA) issuing process, performed by the Greek Forest Service (GFS). The issue under investigation is the characterization of specific or wider land areas as sylvan (forest ecosystem in general) or not, based on the applicable legislation and the fundamental principles of Forest Ecology. The proposed DSS is a web application that bases its operation and functionality on a model built for the decoding of the relevant Forest Legislation and utilizes the “Rule-Based Reasoning” technique for the design and implementation of the decision model. Programming languages such as PHP, HTML and JavaScript were employed for the development of the application. The main goal of the DSS is the simplification -and to the possible extent - automation of the process together with the reduction of the required examination time. “E-praxis” also aims to document the decision process based on objective criteria so as to combat bureaucracy and potential corruption. The use of the application by the GFS can save time that can be committed to other significant tasks and strengthen the objectivity in decision making. The proposed DSS could also be exploited as a consultation tool for freelance forestersscholars, be used as a training tool for newly appointed foresters of the GFS and as an educational tool for Forestry and Legal sciences students.

1. Introduction 1.1. Problem statement and aim of the study This paper proposes a new methodology for issuing “Land Characterization Act” (CA) by the Greek Forest Service (GFS). Specifically, a web-based Decision Support System (Web-DSS) has been developed (Bhargava et al., 2007; Jain and Tyagi, 2014) that processes all relevant parameters (legal, environmental, ecological) that affect the query, operating supportively in deciding on the character of an area. The proposed web-DSS by the name “e-praxis”, implements new issue control methods for CAs on the basis of the possibilities offered by Information Technology (IT), in order to a) achieve a significant reduction of the required time to issue a CA b) limit potential omissions in the process and c) organize and classify the existing legislation so as to be easily and directly accessible at each stage of the process, d) reduce the probability of failure of critical parameters (Athanasiadis and Andreopoulou, 2013). The main problem of the Greek Forest Service (GFS) regarding land characterization and especially the CA issuing process is the large number of

applications for land characterization and significant staff shortages in several departments, which result in slowing the CA issuing process and publication (Andreopoulou, 2011). Other important issues are a) the complexity and constant revision of the forest law b) potential subjectivity of the decision-maker and c) negligent or intentional data omission (Rigopoulos and Karachle, 2013). The term “subjectivity” refers to the case where the examiner, either deliberately or by mistake, misinterprets the law or inadequately assesses the available data, with the result that his findings are often called into question. Consequently, objections to decisions and activation of judicial review procedures are followed, which cause a climate of suspicion against the GFS (Papastaurou, 2006; Goupos, 2003). “E-praxis” was chosen to facilitate the work of the decision-makers of the GFS by the use of a simple web application which organizes and automates the CA issuing process. Ultimately, the GFS does not employ such a decision tool, which contains all relevant data and working stages that concern the CA process. The aim of this study is, through the use of the proposed DSS, to contribute to a) upgrading the quality of services offered b) decreasing bureaucracy and c) increasing productivity of GFS staff while saving resources that could be used for other tasks.

This article is part of a special issue entitled. “Models and tools for integrated forest management and forest policy analysis” published at the journal Forest Policy and Economics 103C, 2019. ⁎ Corresponding author. E-mail addresses: [email protected] (A. Athanasiadis), [email protected] (Z. Andreopoulou). ☆

https://doi.org/10.1016/j.forpol.2019.03.002 Received 30 October 2016; Received in revised form 5 March 2019; Accepted 6 March 2019 Available online 18 March 2019 1389-9341/ © 2019 Elsevier B.V. All rights reserved.

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governing land characterization are listed in the following Table 1. The following Table 2 presents each paragraph of art.3 of L.998/ 1979, according to its latest amendment by art.32 of L.4280/2014. This is, along with other special law cases, the conceptual framework and the theoretical basis for designing and implementing the decision framework of the proposed DSS.

1.2. The Greek legislative framework The definition of the character of a land area is a prerequisite for the protection and conservation of natural resources. This operation also defines and establishes the permitted and proper interventions in the natural environment and the land use status of the study area (Chazdon et al., 2016; Lund, 2015; Verburg et al., 2009). The criteria on which it depends on and the procedures followed are determined by the Legal framework of each country in relation to its specific ecological and environmental characteristics (FAO, 2012). The legal standing of the definition of forest ecosystems is of fundamental importance, as are the environmental factors that ultimately determine what is forest and what is not (Helms, 2002; Sasaki and Putz, 2009; Lund, 2014). In Greece, where land registration procedures (National Cadastre) are still ongoing, a complicated as well as time-consuming procedure (Stamou, 2002) of examining of individual cases of land characterization is taking place in areas mainly outside the urban fabric, in which the perspective Forest Map hasn't been constructed yet. The land characterization process is being conducted by the Forest Service, according to the current legislative framework, either ex officio or upon request. The legal document, indicating the characterization of the study area, is the “Land Characterization Act” (CA) and is accompanied by a topographic chart depicting the boundary of the area under examination and a location map of the wider region. The CA document is a prerequisite for the utilization and economic exploitation of a piece of land –if characterized as non-forested–, which usually involves building permit, fence construction, installation of agricultural activity, opening access road, electrification, connection to water supply network etc. On the other hand, if the study area is defined as of environmental importance (e.g. Forest, woodland etc.), the CA document ascribes a specific land type identity to the area and secures its protection, conservation and potential restoration. The concepts of forest and forest ecosystems are generally defined by the forest science and also certified by the Greek Constitution as “the organic whole of wild plants with woody trunk on the required surface ground which, in combination with the coexisting flora and fauna, constitute via their mutual interdependence and interaction, a particular bioecoenosis (biological and ecological unit) and formulate a special natural environment (forest ecosystem). Forestland (Woodland) is treated as a separated concept and identified when the wild woody vegetation, either high or shrubbery, is sparse”. Currently, the Greek forest legislation related to the characterization of land is based on article 3 of L.998/1979 as it stands and amended by article 32 of L.4280/2014. Suffice it to say that, a number of legislative provisions such as Ministerial Decisions (M.D), Presidential Decrees (P.D), State Council Decisions and common with many governmental orders and regulations, compose the respective legislative framework. Inevitably, Forest Policy Planning is inextricably linked to the current legislative framework, whilst it implies a group of strategic plans and measures applied to support forest planning and management (Menzel et al., 2012; Montiel-Molina, 2013). Case law documentation is also an extremely important aspect affecting the issue under investigation (Rozos, 2006). The main legal instruments

1.3. State-of-the-art regarding DSS for land use and land characterization It is obvious that land characterization, through the CA issuing process, is a decision-making process of selecting an action among a set of alternative actions with the objective of achieving a goal. The decision makers studying various multi-affected biological, social and economic factors and using new interactive tools and techniques, try to minimize the margin of error (Turban and Aronson, 1998). These tools are Decision Support Systems (DSS), which are based on the use of a computer and intended to help the administrator to identify and solve problems and make decisions by using communication technologies, facts, data and models (Power, 2007). Nowadays, DSSs are widely used by Institutions, Public Services and Organizations as an advisory means of solving crucial issues of Forest Policy and management (Borges et al., 2003; Stewart et al., 2013). They are regarded as the latest tools of IT that are being utilized for the management of forest ecosystems and normally include standalone applications tailored to the needs and requirements of the specifics of each study area (Tasoulas and Andreopoulou, 2012; Segura et al., 2014). Moreover they suggest innovative methods for solving functional problems of the Forest Services, ensuring objectivity and time saving, taking into account all the crucial factors related to a specific issue (Athanasiadis and Andreopoulou, 2015). The design, implementation and application of operations research models through DSSs can assist greatly in the management of natural resources and the development of strategies for sustainable development (De Meo et al., 2013). Many types of DSSs combine spatial information with thematic databases and deal with routine case studies (Athanasiadis and Andreopoulou, 2011). Spatial Decision Support Systems (SDSS) are widely applicable as they introduce interactive, computer-based systems designed to assist in decision making while solving a semi-structured spatial problem (Zeng et al., 2007). Finally, programming languages, web applications, databases, mathematical and economic models are also utilized to develop DSSs (Lexer and Brooks, 2005; McIntosh et al., 2011). Internationally, there have been many attempts at handling and confronting demanding issues of forest management, land use, environmental protection and administration. Recently, there has been a significant increase in the number of modeling tools available to examine future land-use and land-cover change, most of which are intended for actual planning, decision-making, or policy-making purposes (Sohl and Claggett, 2013). Kirilenko et al. (2007) propose a web-based DSS that provides management advice and appropriate land use measures to forest owners. Church et al. (2000) analyze the development of a DSS based on spatial data analysis, to be exploited by the US Forest

Table 1 The Greek legislative framework of land characterization issue. Legislation

Individual subject

Law 998/1979 Constitution of Greece (2001) Law 3818/2010 Law 4280/2014 Case Law P.D 32/2016 M.D 136255/683, art.67 L.998/1979 & art.39 L.4280/2014 Direction 133,383/6586

Definition of forestry concepts, classification of land types Definition of forestry concepts and protective framework Reconsideration of L.998/1979 Reconsideration of L.998/1979 State Council Decisions (SC), Legal Council Advice (LC) Clarification of Quantitative and qualitative criteria of land characterization Forested farmlands legal status Grasslands and bare lands legal status

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Table 2 Explanatory Table of respective paragraphs of Article 3 of Law 998/1979 as applicable and amended. Paragraph

Illustration

Protection & management status

1 2 3

Forest Forest Land Bare lands (above forest limits), brushwood sites, grasslands, rocky elevations and generally uncovered spaces, enclosed by forests or forest lands Urban Groves and Parks and parts of them which do not bear any forest vegetation Grasslands located in mountainous & hilly regions or generally in rough terrains, that establish natural ecosystems consisting of brushwood, herbaceous or other native vegetation or even forest vegetation that do not exhibit a forest ecosystem The rocky or stony areas of mountainous, hilly regions or generally in rough terrains Area characterized as non-forested (general inclusion) Agriculturally cultivated area (farmland) Areas in the “5α” form, that according to the aerial photographs of 1945 or - if they are not defined 1960, they had an agricultural form (farmland) in the past. Artificial plantations of forest species Saltpans Sandy lands Lowland streams that do not bear any forest vegetation Areas included in urban fabric Irrigation network zones bearing forest vegetation

Protected & managed by the GFS. Falling under the provisions of the Forest Legislation

4 5α 5β 6 6α 6β 6γ 6δ 6ε 6στ 6ζ 6η

Not protected & not managed by the GFS. Falling under the provisions of the Agricultural Legislation

• Understanding and personal experience of Characterization Acts

Service for forest ecosystem management. Hiltunen et al. (2009) present a web DSS application for participatory strategic-level natural resources planning. West and Turner (2013) propose a decision framework for spatial and temporal evaluation of integrated land use. Witlox et al. (2009) exploit decision tables to develop a functional classification theory to land use planning. De la Rosa et al. (2004) develop a land evaluation DSS for agricultural soil protection for the Mediterranean region. In terms of land Characterization most of recent researches refer to methods and decision tools for estimating forest canopy cover in order to classify forest landscapes according to specific features (vegetation, area, latitude, altitude, slope, etc.), mainly utilizing satellite data and Remote Sensing technologies (Townshend et al., 2012; Chrysafis et al., 2017; Ahmed et al., 2015; Webster et al., 2018). A method to identify forested areas from TanDEM-X interferometric data is proposed by Martone et al. (2018). Moran et al. (2018) present a Data-driven classification method of forest structure using LiDAR. Magdon et al. (2014) present an image classification framework implementing the FAO definitions of forest. He (2008) provides classification and characterization of forest landscape models. In Greece, there have been some efforts to address related issues in recent years, mainly on the issue of preventing and tackling forest fires and various other purely management issues (Dimitrakopoulos, 2001; Manos et al., 2010; Ioannou and Lefakis, 2011; Papathanasiou et al., 2005; Kaloudis et al., 2005). Mallinis et al. (2008) propose a method to decrease subjectivity in the characterization of forest areas according to forest legal definitions. Vogiatzis (2008) develops a forest mapping project, in accordance with the current legislation, as a tool for editing forest maps. However, forest administrative and organizational issues of forest law through the use of DSS applications have not received the expected attention (Athanasiadis and Andreopoulou, 2015).

issuing process by the Forestry Service

The proposed DSS simulates the current methodology used by the GFS. For this reason, it is necessary to investigate these conventional methods. However, this effort also attempts to improve and organize the process efficiently, apart from the automation and legal configuration that it aims to provide.

• Physical

and logical planning of the Decision-making Model (Decision Framework)

Decision analysis is the most critical working stage before the development of the DSS. The decision framework is created and the system variables and relationships between them are defined.

• Development of the web application, utilizing the appropriate IT means and web programming tools.

The last section contains all the essential technical details for the development of “e-praxis”. This is an equally important stage because it defines the presentation format of the data and the user interface, which must be concise and easy to use. The structural issue, which the proposed DSS aims to solve, is the identification of forest ecosystem existence in a specific site. This is the basic parameter that one should bear in mind in order to characterize and classify a piece of land according to the 2257/2014 decision of the State Council (SC) of Greece. The examiner must also be aware of the legal arrangements governing the ownership of forests. In total, Forest law delivers the definitions of the fundamental concepts of forest, directly based on the scientific documentation provided by Forestry Science and specifically by forest ecology (SC 5234/1996, SC 32, 33 & 34/2013). In conclusion, the basic factors that must be taken into consideration in order to characterize an area according to the current legal framework and forest ecology (Ntafis, 1986) are listed below:

2. Materials and methods For the realization and development of the DSS, the following tasks are considered essential:

• Canopy cover and land cover percentage of vegetation et al., 2005) • Vegetation and character of contiguous areas

1

• Study and comprehension of the legal framework The basic concepts of forest, as defined by the current legislation on the basis of the fundamental principles of forestry, must be analyzed and clarified, so as to design the basic conceptual framework for the implementation of the proposed DSS.

(Comber

1 It is the basic criterion for the configuration of forest-related environment (Ntafis, 1986).

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Table 3 Special Cases – Research in the GFS Archive. Case

Action taken

Law

Remarks

Certified Forest Map

CA not issued

Already definitively characterized in the corresponding Forest Map

Included in a Region of special protection status

CA issued normally

M.D 97414/754, 199,284/707 Par.2 art. 29 & art.46α of L.4061/2012

Areas included in urban fabric Included in Reforestation Area

CA issued normally CA not issued

Included in other CA Old Settlement areas

CA not issued CA issued normally, Additional proof is required CA issued normally, Additional proof is required

Legal Change of land use

Par.6ζ Art. 3 L.998/1979 Par.3 Art. 117 of the Constitution Art.14 L.998/1979 L.4061/2012 Art.10 L.3208/2003 Legal permit for land clearing

• Vegetation and character of the wider study area • Size of the study area (Required Surface Ground) • Vegetation type and plant species • Interaction with adjacent forest ecosystems - anthropogenic interference • Land use status in the past (1945, 1960, 1998 etc.)

Cessions, legal land clearings and Change of land use permits are not to be considered when the study area is characterized as forest land or reforestations have been ordered. Characterized as “non-forest area” Characterized as (potentially) “Forested area” of the par.4 art. 3 L.998/1979 Already definitively characterized in a previous CA Possibility for the recognition of private Forest Preserving agricultural use. Area cannot be used for another purpose

vegetation to an appreciable extent (high or shrub) b) have the ecological characteristics of a “forest bioecoenosis” and of a particular forest ecosystem in general c) represents an operational management unit that contributes to the ecological balance of a given area's environment, according to the fundamental ecological and forestry principles (Ntafis, 1986). It is considered that these features are covered by the organic unit of a “thicket”, estimated at 700 m2 according to the P.D 32/2016, which is the “Required Surface Ground”. If the examination area is smaller, it may also be classified as forest if it is surrounded by or adjacent to forest areas and exhibits great interdependence and interaction with the natural environment of the region. Significant factors of forest ecology that are counted are: the existence of wildlife and woody vegetation (high or shrub) as part of the ecosystem, the phytosociological zone, soil conditions, geological structure and the position of the site in relation to the surrounding area (Fig. 1). The term “wider region” refers to the nature and vegetation of the wider study area which includes the specific area of examination. The term: “other forms of areas” could be residential, urban, semi-urban or rural areas. Other terms referred to the Decision Trees are illustrated in Table 4. Criterion PR2 is taken into account only if the primary Criterion (PR1) cannot clarify efficiently the adjacency of the study area. Therefore, the area is examined according to the vegetation status of the wider region. The values 15% and 25% of the canopy cover estimation define the separation between forest and forest land according to the PD 32/2016. Depending on the relevant attributes and the available data derived from the preliminary operations such as the research in the GFS archive, site analysis and aerial-photo interpretation, the examiner is gradually guided to the final decision. The decision-making process, through the use of questionnaires, eventually leads to the appropriate characterization of the study area, which is classified according to the respective paragraph of art.3 of L.998/1979 as it stands and amended by art.32 of L.4280/2014. The same examination process is also conducted for the identification of the character of the area in the past.3 The comparative analysis of the two conditions leads to the final classification of the area conditioned by the following assumptions based on the current legislation:

2

The above are the basic variables of the proposed Decision Model. 2.1. Forest service and land characterization The analysis of the current legal framework indicates the complexity and the weaknesses of the CA issue, especially for the GFS staff. Particularly, the examination of a land characterization request, contains collection and processing of data arising from two main preliminary tasks: a) site analysis b) Investigation on the past land use status and vegetation. The collected data may lead the examiner (Forester of the GFS) to the elaboration of the relevant Recommendation report, which is sent to the head of the department for sanction. The CA document becomes officially approved after a twomonth period and on condition that no one involved in the case has raised any objections. It must also be noted that before enacting the preliminary tasks, a data completeness check of the application file and research in the Office archive is mandatory in order to identify any issues and concerns that may affect the case study. These special cases that may arise during an archive research are listed and illustrated in Table 3. 2.2. Decision analysis The “Rule-Based Reasoning” technique (Bonczek et al., 1980; Holsapple and Whinston, 1986; Frye et al., 1995), was employed for the analysis of the decision framework and for the physical design of the decision model. In this way, knowledge is not represented statically, but through a set of rules of the type “if … then …if else …” that indicates directly what should be done or be decided on a particular instance of the problem under consideration (Deng and Wibowo, 2008). Graphical paradigms play an important role in modeling and structuring decision problems, whilst one of the most commonly used graphs is the Decision Tree as a means of Decision Analysis (Nordström et al., 2010). Two decision-making models (Decision Trees) were elaborated, depending on the existence of forest vegetation on the study area (Figs. 1 and 2). The area of examination must have the following general characteristics in order to be classified in a forest land type according to art.3 L.998/1979 as modified by art.32 L.4280/2014: a) contain forest

• Areas of forest form, regardless of their form and use in the past, •

retain their character and are subject to the protective provisions of Forest Law. Areas of forest form in the past, regardless of their present form and use, retain their past character and are subject to the protective

3 1945 is the year of aerial photography of the entire country. Aerial photographs of intervening years could also be considered to establish the temporal character of an area.

2

Refers to the minimum soil surface that may establish forest-related environment 160

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Fig. 1. Decision Model in case of existence of forest vegetation.

•

provisions of Forest Law. In fact, they are declared as “Reforestation Areas” (art.4 L.998/1979, art.117 of the Greek Constitution). Forested former farmlands can recover their former use under

• •

special conditions (M.D 136255/683). Settlement areas retain their ownership status. Private areas (art.10 L.3208/2003) of par.5α & 5β classified in par.6

Fig. 2. Decision Model in case of no forest vegetation. 161

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Both the input data, and those arising from background calculations were stored in: a) text boxes, b) text input areas, c) check boxes, d) radio buttons, and e) drop-down menus. Due to the use of these techniques, data can easily be stored and retrieved via the option-command “Session” of PHP, allowing data access and processing to all stages of system operation. Interaction and interactivity were achieved through Javascript code, which define “what will happen and when” depending on the answers given to the questions and the conditions that we have initially set. In general, for the implementation of the rule basis of the model, which was previously specified during the physical design and the decision analysis, complicated Javascript functions that define the outcome of every choice, were mainly utilized. These functions determine the hiding and showing of the corresponding HTML objects while leading the user to the next stage. The following Javascript code defines values for the variable “message” depending on the canopy cover of the study area, as estimated after a site analysis and photo interpretation by the examiner. Values 1, 2 refer to the corresponding paragraphs of art.3 L.998/1979 and variable “i” to the potential sections of a divided study area. If((document.querySelector('input[name=das_vlastisi_'+i +']:checked').value == 'nai') && (document.getElementById('Vath_sugk_'+i).value == 'dasos')) {message = '1'; document.getElementById('katigories_daswn_'+i). style.display = 'block';} elseif((document.querySelector('input[name=das_vlastisi_'+i+']: checked').value == 'nai') && (document.getElementById ('Vath_sugk_'+i).value == 'das_ektasi'))

Table 4 Explanatory Table of terms in Fig. 1 and 2. AbbreviationTerminology

Meaning

1,2,3 …,6στ, 6η

Corresponding paragraphs of Article 3 of Law 998/ 1979 as it stands Enclosed by Forest Ecosystems Contiguous with Forest Ecosystems Interdependence with adjacent Forest Ecosystems Interaction with adjacent Forest Ecosystems Primary Criterion (Priority 1) Secondary Criterion (Priority 2) Mountainous and hilly regions Areas that meet the following attributes: Altitude < 100 m, Average Slope < 8%, Maximum Slope < 12% The surface area in m2 If the study area is Grassland If the study area is Rocky land

Criterion 1 Criterion 2 Criterion 3 Criterion 4 PR1 PR2 Highlands Lowlands A * **

and are not subject to the protective provisions of Forest Law. 2.3. Development of the DSS e-praxis The design of the user interface of the application was implemented in HTML. In order to ensure the uniformity of the individual web-pages, Cascading Style Sheets (CSS) were utilized. Data entry into the system was performed using HTML forms into a Session of PHP for consecutiveness and connection of the data given and produced in each form.

Fig. 3. Flowchart of web-DSS: “e-praxis”. 162

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{message = '2';document.getElementById('katigories_daswn_'+i). style.display = 'block';} Finally, to check the special cases issues that may occur after the survey in the Service's archive, several logical scenarios were created using PHP code. The following example presents the case of a study area enclosed in a certified forest map, meaning that CA cannot be published. echo (($_SESSION['arxeio']['rows'][$i]['dmap']=='nai')?' area included in a Forest Map excerpt and has been characterized as: '. $_SESSION['arxeio']['rows'][$i]['XP'].'. Eventually < b > CA not issued for this section < /b:”); The same methods were implemented for the comparative evaluation of the character of the study area (present – past condition), so as to reach the final decision.

at this stage of the session refer to these parameters that have been analyzed in chapter 1.2 on the basis of the current legal framework and forest ecology principles (eg. canopy cover, contiguous areas, Required Surface Ground etc.). Since the output is generated automatically, subjectivity is less likely to infiltrate. Having completed the required fields on the last entry screen and submitted the relevant data to the system, a Recommendation report is automatically generated, containing all findings that justify the decision and can be printed or saved in pdf file. The form and content of the documents issued by the system is consistent with the format of the documents published by the local GFS and has been adapted according to the latest Ministerial Decision 118,790/7487. The ability to automatically produce the official documents, provided by “e-praxis”, contributes to faster completion of the process, in contrast to the empirical method, where all documents should be manually filled.

3. Results

4. Discussion

The web-based DSS tool was given the name “e-praxis” (electronic praxis), arising from the Greek word “praxis”, which means “act-action”. It provides decision support capabilities using the interface of a web browser that integrates computation technologies from the user side (Javascript) (Jain and Tyagi, 2014). It belongs to the category of “Rule-Oriented DSSs” (Bonczek et al., 1980) and has the structure of a website with individual web pages (Fig. 3). At this stage of the research, the display language of the decision tool is Greek, since it addresses to the GFS and refers to the Greek national issue of land characterization. The application is also translated into English in order to be accessible to the international audience. The proposed DSS is a simulation of the conventional procedure, followed currently by the GFS, but enriched and refined in a considerable level. The decision model is developed in accordance with the provisions of the forest law and considers all the parameters involved in the impending decision and, as far as possible, quantifies and explores the expected interdependencies and interactions. The “e-praxis” user, once certified by the managing authority of the system, enters his/her username and password and gets access to the home page of the application, which is an informative section on the features and usability of the DSS. Subsequently, operation of the DSS proceeds through with successive screens in which the user is required to make estimates and introduce all the information required. Generally, the structure of the system is based on questionnaires that create a sense of interactivity between the system and the user. Initially, some general information about the study area is required (Application data) followed by a compendious study of the potential special issues that may affect the study area (Archive Research). At this part, the user simply enters the required information about the location and geology of the study area. This structure ensures that there is no omission of any given data to be taken into account. If the archive research of the GFS leads to a recommendation not to issue a CA (Table 3), the system, instead of a Recommendation Report, produces an official Reply Document to the applicant, stating the reasons why the continuation of the process is unnecessary. “e-praxis” also offers the possibility of viewing the study area in backgrounds of recent satellite images via the web application “Google maps”, either by entering the coordinates of the vertices of the polygon area, or uploading a txt file with coordinates couples. In this way, the user can make a rough estimate of the character and vegetation of the wider region (Fig. 4) and give a description to be used in the Recommendation Report. Subsequently, the user is asked to submit his/her assessment of the conditions governing the study area, based on data obtained from onsite inspection and aerial photo interpretation. The questionnaires that are contained in the pages “Site Analysis “and “Photo Interpretation” have been prepared in accordance with the decision Trees presented in Figs. 1 and 2. These two web pages operate as keys that lead to a recommendation for the character of the area. The consecutive input data

4.1. Opportunities and benefits Studying the structure and content of “e-praxis”, some basic advantages can be distinguished. First of all, the interface of the application is relatively simple, without additional functions, special design and operational characteristics, in order to broaden the group of users, since specialized computer handling knowledge is not required for its use. The user's responsibility lies in the proper completion of the questionnaires and relevant data submission, as they are directly guided to the finalization of the proceedings without the feeling of loss of control. The organizational structure of the proposed DSS enables faster completion of the process in contrast to the manual process, saving staff time to execute other important tasks (management, prevention and protection) from the Forest Service staff. Classifying the examination tasks of each individual characterization case to separate work steps and providing partial data entry, the user of “e-praxis” is always conscious of what to do and when. In addition, the relevant legislation is assembled into the problem-processing system and no additional time is required for searching the relevant legislative articles. Another key advantage of the application is the easy adaptation and update of the rule-basis of the decision-making model to possible amendments of the legislation governing the status of characterizations. This is made possible by minor interventions and modifications in the programming code (PHP, Javascript) ensuring the functionality and reliability of the system. All the above suggest that the use of “e-praxis” by the GFS may result in more reliable and documented CAs, minimizing the likelihood of false findings. The proposed DSS can offer great opportunities for upgrading the services offered by the GFS. 4.2. Challenges and potential uses “e-praxis” is addressed primarily to the GFS staff and specifically to the land characterization examiners (foresters). In a second degree however, its use could be extended to the private sector for use by foresters-scholars who are employed as consultants. Also it can be used as an emulator of the actual process, for educational purposes, in the training and education of new employees of the GFS, students of Forestry and Law sciences. Further, it could be an advisory tool for the committees of forest disputes in legal and judicial level. With appropriate technical extensions and updates and especially the integration of dynamic databases, “e-praxis” can be transformed into an accomplished Electronic Service Information Tool that could fully manage the “in-service” CA issuing process. Moreover, a probable interconnection of “e-praxis” with GIS software can correlate all the information relating to a land area with geographic mapping. Finally, direct online connection of the proposed DSS with the governmental 163

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Fig. 4. Geographical display of the study area (screenshot).

portal “Diavgeia” and automatic upload of the CA documents or even constant notification of the applicant about the progression of their application could be a possibility for extension. While other studies regarding land characterization methods seem to employ remote sensing and image processing technologies in order to identify and classify forest land types (Townshend et al., 2012; Ahmed et al., 2015; Webster et al., 2018), “e-praxis” manages this issue from a legal point of view. Specifically, it adopts a land characterization technique based on the codification of the relevant forest legislation and integrates the decision logic into a web application. This approach was chosen because Greece is a special case among other developed countries as it does not yet have integrated forest maps. As a result, land characterizations are directly linked to the current legal regime, which is quite complicated. Hence the need to organize and codify it. Apparently, there are only few similar studies dealing with this issue from a legal aspect. For instance, Magdon et al. (2014) try to match the FAO definitions of forest with an image classification framework, Mallinis et al. (2008) present an object based approach for the implementation of the Greek forest legislation processing satellite images to estimate the canopy cover or a region. Finally, Vogiatzis (2008) analyses and organizes the current legislation related to land characterization issue in Greece and develops an interesting forest mapping project, which could be used for the separation of forest from other forms of land during the elaboration of forest maps.

sustainable forest policy is the clarification of the concept of forest in ecological terms that are certified by the applicable law (Keenan et al., 2015). This is also enhanced by the elaboration and following sanction of the national Cadastre and the relative Forest maps of Greece (Zentelis and Dimopoulou, 2001; Vogiatzis, 2008). Therefore, the exploitation of the Greek public property and the attraction of foreign and local investments depend significantly on a reliable geo-economic environment, which demand the classification of the Greek territory in particular land types. This issue greatly affects any contingent land use change (Borges et al., 2010; Coulston et al., 2013). Moreover, competing pressures to exploit unutilized areas of great interest, forest surrounds, complex issues of tenure, ownership, access and other forest policy issues have hindered any effort of development and economic growth in that sector. Improvement and amplification of the land characterization process are likely to assist in solving the above mentioned problems and put an end to the land status dispute. Apparently, an innovative methodology such us the one introduced by “e-praxis” may face the above challenges by upgrading the land characterization process. This paper proposes an approach to address the issue of land characterizations in Greece, based on exploiting the potential of a webbased DSS. The great challenge of “e-praxis” is to enhance the objectivity in decision making by the Forest Service. Generally, with the adoption of the proposed DSS, the main role of the manager is limited to the accurate data collection and evaluation of the findings and results (Papathanasiou et al., 2005). However “e-praxis” does not refute the empirical approach of the forester towards the issue. Its purpose is to enhance decision-making with factual arguments, ensuring omission

5. Conclusion An indispensable prerequisite for developing and exercising 164

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avoidance of critical data. “E-praxis” also provides appropriate interpretation and implementation of the legislation thanks to its rule-based questionnaires that “forces” the user to explore and consider all aspects related to the issue, unable neither to ignore nor to overestimate any of them. The utilization of the proposed DSS may contribute to the protection of the natural environment, as it aims at eliminating incorrect declassification of woodlands and detection of illegal land use changes. Still, a commonly accepted, impartial and significantly automated land characterization issuing system, can minimize conflicts between citizens and public administration and contribute to the development of trust and confidence. “E-praxis” could also be applied in other countries facing similar issues (Marinchescu et al., 2014; Atmiş et al., 2007) after appropriate interventions and modifications to the structure and legislative basis of the system, according to the legal framework of the country of application. In that case an updated decision model is needed, so that the decision tool can be applied internationally. However, almost all European countries have certified forest maps and cadaster. So “e-praxis” could be applied in developing countries undergoing land characterization and registration processes.

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