GIS, in the last decennary, are used intensively as a direction tool in production agribusiness, farm hazard appraisals, agribusiness merchandise procurance – bringing and individuality saving of harvests, in authorities or public degree. Emphasis is given in this survey to reexamine and analyze non merely GIS but besides all factors – standards that are involved in agricultural development of rural countries both under the position of the new EU Common Agricultural Policy ( CAP ) 2007 – 2013 and the local/global demands for fight, sustainable environmental and land direction, economic variegation and quality. The survey focuses on the instance of Arcadia Prefecture that is settled in the Centre of Peloponnese. The terminal merchandise of this survey is the development of a determination support tool for Agricultural Land Management/Planning through the usage of Geographic Information Systems ( GIS ) . This tool adheres to the CAP 2007 – 2013 strategic guidelines.
The developed determination support tool ( Spatial Decision Support System ) that is proposed bases its map on the joint usage on Relational Database Management Systems, Geographic Information Systems and Fuzzy Logic Analysis. Its public-service corporations are tested on the Arcadia Prefecture through the probe of “ hot musca volitanss ” for vineyard cultivations. Consequences revealed that the proposed system turned out to be a strong determination support tool that has many utilizations non merely in the agricultural sector but besides in its surrounding industry.
Keywords
Spatial determination support system, geographical information systems, CAP 2007 – 2013, direction, sustainable agricultural development
Introduction – Demand for the survey
The negative effects and the impacts on societal, economical, environmental and ecological sectors from the intense agriculture techniques and policies all across Europe ( see fig.1 ) , resulted in the evolving of Common Agricultural Policy 2007-2013.
The Grecian agribusiness sector in the event of CAP 2007-2013 and planetary economic alterations, finds itself in a hard state of affairs where it has to bring forth merchandises that are competitory in the planetary and local market and in harmoniousness with the demands of EU statute law and the CAP. The fight has to be maintained, supported and based on the Greek local farming typical characteristics. The complexness and assortment of this effort calls for locally adopted solutions.
This survey attempts to place and analyze the CAP 2007 – 2013 and to set up an “ alternate ” – different solution in determination devising.
Figure 1: Influence Diagram
Scope of the Study & A ; Aims
Scope
The purpose of the research is to analyze the four axes of CAP 2007-2013 that include societal, economical and environmental features/factors and use CAP on Mantinia ( prefecture of Arcadia – Central Peloponese ) with range to make a solution for present and future jobs and chances. As a “ model ” for the application of these, will be the Geographic Information Systems ( GIS ) aided by the usage of Multi-Criteria Decision Making ( MCDM ) package.
Aims
The aims of the research were set to be the followers:
the survey of CAP 2007-2013
the appraisal of conditions and patterns in the rural countries of Greece
the designation of appropriate standards with respects to CAP 2007-2013 and sustainable development
the development of a dependable environment for Sustainable Agricultural Development
the development a robust direction system ( with the usage of GIS ) that will:
integrate and present hereafter facts and factors ( landscape, statute law, socioeconomic characteristics, etc. )
help the determination shapers in expeditiously and efficaciously pull offing – be aftering agricultural land and rural countries
Literature Review
GIS for research in agribusiness
GIS is more than a beneficiary and helping tool in the research within the agricultural sector. GIS is a enormous tool in the designation of suited or non sites and parts and hot musca volitanss within big parts based on legion conditions1, 2.
GIS in research sector is seen by many as the footing of roll uping, managing, analyzing and supervising informations. Researchers agree3 that the ability given by GIS to unite, analyse and eventually give ocular representation of informations refering dirt, clime, societal, economic and other factors of disperse countries and with different weights to each different country ( or even within the same countries ) gives highly high value to its usage and advantages are spread through the whole agricultural supply chain4.
Characteristic agricultural research undertakings undertaken during the last decennaries are given below:
The Kenya Maize Database Project5
Integrated Pest Management on U.S. Fish and Wildlife Service Land6
Site-Specific Weed Management in Growers ‘ William claude dukenfields: Predictions from Hand-Drawn Maps6
The African Country Almanac7
Development of Land Use Change Scenarios for Europe8
A land rating undertaking in Greece utilizing GIS and based on Boolean and fuzzed set methodologies9
GIS and production in agribusiness
The usage of GIS gives to husbandmans and agribusiness professionals7, the ability to pull off their assets and in parallel assist environmental protection. Thus overruns are minimised and the usage of “ natural ” stuffs ( weedkillers, pesticides, H2O, harvests, etc ) is leveraged. This gives the ability to husbandmans and agribusiness professionals to better place themselves non merely within the local market but besides within planetary market. GIS give the ability to gestate how assets and characteristics interact within a part and among them and this gives to husbandmans the ability to leverage productions and operations and later derive non merely in footings of money but besides in footings of environmental protection.
Bellow there are given illustrations of application of GIS within agricultural nutrient and production sector:
Old Style Vineyard Management meets new manner Precision Farming10
Agribusiness Market Information System for little farm determination devising in Hawaii11
Nitrogen Management in Sugar Beet Using Remote Sensing and GIS6
Climate Change and Agriculture Vulnerability12
The FASAL Project – An Accurate Crop Production Forecasting System13
The Proposed Approach – Model
4.1 Plan of action – A new Agricultural scheme
Illustrated in figure 2 below, the procedure of agricultural sector direction calls for three major stairss the stakeholder analysis, the struggle analysis and the direction.
Figure 2: Datas Flow – Conventional representation of the Proposed Agriculture Strategy
Figure 3: Agricultural Management – Criteria Classs
Figure 4: General – conventional representation of rating and trade – offs
As illustrated in figures above, the determination doing procedure that impacts Agricultural Management has to make non merely with forces deducing within the EU ( citizens, local and EU statute law ) but besides outside the EU boundary lines ( GATT, WTO, citizens around the Earth ) and this is were struggles and force per unit areas arise.
True struggle analysis can be achieved with rating of each old ages outputs such as Agriculture Outputs ( harvests, gross revenues, etc ) , Environmental Impacts ( dirt province impairment, H2O decrease – pollution, etc ) and Health Impacts on citizens. All these agribusiness end products and analysis inputs arise possible struggles that influence political relations, land development and usage, etc.
That is where right Management comes away. As illustrated in figure 4, after taking under consideration proposals of husbandmans and other stakeholders that are straight connected to farming activities, economic and environmental parametric quantities and information that is provided from the rating of Agriculture end products, trade offs can be achieved. A assortment of scenarios can be brought up and assist determination shapers in deciding struggles, equilibrating net incomes and losingss and supply feedback and input for following Agricultural Managements Plan.
4.2 CAP & A ; Agricultural Management: An Agile Decision Making Process
The multi-dimensional kineticss of agricultural direction due to the spatial/non-spatial factor unifying in determination devising procedure demands a sustainable type of direction that is “ traveling ” along countries of societal and economical stableness and local and national demands – demands. Having to take under consideration societal, environmental and economical constituents, calls for a new – “ Agile ” direction construction.
The solution proposed by the CAP and the manner that is “ translated ” by the struggle analysis, seeks for a “ Aureate Mean ” – a more nimble attack between environmental objects, societal objects, intensive systems and patterns and economic aims. This new perceptual experience is based on a four – dimensional rural “ regeneration ” :
1st Dimension: Diversification of purposes and schemes harmonizing to local, national and international market demands.
2nd Dimension: Locally based direction systems.
3rd Dimension: Cultivations that put the environment as their first – top precedence. Acts that will back up enterprises based on traditional agriculture methods and merchandises.
4th Dimension: A dynamic reappraisal – coverage strategy based on changeless agricultural activity monitoring.
All the above mentioned dimensions -schemes – patterns can be and are supported by the possible given by the GIS engineering with the aid of adept knowledge14 ( Multi Criteria Decision Making ) .
4.3 GIS & A ; MCDM: A model for Agricultural Management
The combination of GIS and MCDM can be used as a model for turn toing current state of affairs and demands, conveying to come up jobs and other issues under the position of CAP 2007 – 2013 and planetary demands, indicating out solutions and doing trade offs. The integrating of GIS and MCDM under the position of CAP follows the undermentioned way:
Identify, lineation and depict spacial and non-spatial informations features of current and future agricultural state of affairs.
Determine purposes and potencies
Monitor results
Analyse results/impacts – Evaluate
Adopt measures/make trade offs in order to re-calibrate purposes of agribusiness.
The competitory advantage refering the usage of incorporate GIS and MCDM systems in Agriculture derives by the ability given by such an IT System to pull off in an nimble mode all direction issues in Agriculture, issues that each one makes up a different direction class ( Soil Management, Biodiversity Management, Environmental Management, Time Management, etc ) and all of them together consist the Sustainable Agricultural Management.
The dataflow of the proposed integrated GIS-MCDM System for use in agricultural direction is given in figure 5 below. Classs of standards are given in footings of informations and the classs – analysis – use of information is made under the position of CAP 2007-2013.
Figure 5: Dataflow diagram of integrated GIS-MCDM System
Description of the Research & A ; the Research Sample
Evaluation standards associating to Agricultural Development – Management
Evaluation standards with respects to sustainable agricultural development and direction were non merely identified harmonizing to the guidelines of CAP 2007 -2013 but besides with regard to specific issues deducing from the Agricultural and Environmental scientific discipline. For the range of the survey a general standard “ tree ” was developed with 5 group classs of properties – standards ( see fig. 6 ) :
Social – Economic – Managerial standards
Environmental – Cultural standards
Landscape – Geographic standards
Accessibility – Planning & A ; Infrastructure standards
History Of Demand standards
Figure 6: Agricultural standards & A ; AXIS of CAP 2007-2013
For the choice – designation of the standards to be used for both the spacial database development and the instance survey, questionnaires as a method of research were used.
Target Group
The mark group for this undertaking was set to be authorities sections such as the National Statistics Service of Greece, Hellenic Mapping and Cadastral Organisation, scientists of agricultural, environmental and other related subjects, scientific material of ATEI of Piraeus, other professionals in Agricultural sector and husbandmans.
With respects to the sample size, in order to acquire consequences that would reflect a high preciseness degree, it was chosen to accommodate a assurance degree of 95 % with an mistake of A± 5 % for a size of population of about 100.000. It was estimated that the sample size needed for this study would be 383 questionnaires15,16.
For the range of the study 400 questionnaires where prepared ( 250 for the self-administered and the telephone study & A ; 200 for the e-mail study ) . Finally 260 questionnaires where returned ( 190 from self-administered & A ; telephone studies and 60 from electronic mail ) .
Findingss
The statistical processing – analysis of the was undertaken with the usage of SPSS. For the processing17,18 of the collected informations were chosen and used techniques that best suited when sing facets of terminal consequence, classs of the variables used and the measurement graduated tables. The analysis of the questionnaire was undertaken under the undermentioned classs:
Respondents Identity
Social – economical and managerial factors refering agricultural development
Environmental and cultural factors refering agricultural development
Geographical and landscape factors refering agricultural development
Accessibility, planning and substructure factors refering agricultural development
History of demand and agricultural development
Factors – indicants specified by respondents
The many-fold and complicated analysis revealed many countries and factors that seem to impact the agricultural sector and its sustainable development. In Table 1 given below, factors are presented in the signifier of entities along with the per centums that were produced by the questionnaire analysis. Factors are given in the signifier of entities since following range of the research was the development of a database and the parallel usage of it with GIS.
Entity
Questions – Factors ( rates % )
Town
– 5.9 ( 79.6 % ) – 5.10 ( 43.8 % )
Climatology
– 3.10 ( 73.5 % ) – 3.16 ( 81.5 % )
– 3.17 ( 76.5 % )
Population
– 2.10 ( 82.7 % ) – 3.3 ( 62.7 % )
– 2.13 ( 71.2 % ) – 5.9 ( 79.6 % )
– 2.22 ( 73.1 % ) – 5.10 ( 43.8 % )
IRRIGATED AREA
– 3.17 ( 76.5 % ) – 5.5 ( 85.4 % )
County
Not related with specific factor – used for geographical and concluding end product grounds.
PROTECTED AREAS OF NATURA 2000
– 3.9 ( 49.2 % ) – 4.16 ( 89.2 % )
– 3.20 ( 72.3 % ) – 3.21 ( 75.8 % )
Prey
– 3.9 ( 49.2 % ) – 4.16 ( 89.2 % )
– 3.20 ( 72.3 % ) – 3.21 ( 75.8 % )
Land USE ( Corine )
– 3.1 ( 68.1 % ) – 4.7 ( 55.4 % )
– 3. 3 ( 62.7 % ) – 4.12 ( 73.5 % )
– 4.6 ( 86.9 % )
Contour
– 4.15 ( 78.8 % ) – 5.2 ( 74.6 % )
Roads
– 5.2 ( 74.6 % ) – 5.3 ( 85.4 % )
Rivers
– 3.11 ( 69.2 % ) – 3.18 ( 70.8 % )
– 3.20 ( 72.3 % ) – 4.4 ( 77.7 % )
GEOLOGICAL FORMATION
– 3.12 ( 71.2 % )
Lake
– 3.11 ( 69.2 % ) – 3.18 ( 70.8 % )
– 3.20 ( 72.3 % ) – 4.4 ( 77.7 % )
Table 1: Selected Entities
Validation – Case Study
Concluding measure was the application of the proposed Spatial Decision Support System ( joint usage of the ArcGIS, the Geo-Database and the ARCSDM19 ) in cardinal Peloponnesus – Mantinia for the optimal vinery site choice. First the economic sciences behind the choice of vineries were analysed, so information was prepared for usage with GIS, standards were transformed into beds of informations and eventually by utilizing Fuzzy Logic20,21 the fuzzed sets were assigned and the concluding mathematical computations took topographic point in order to bring forth the terminal consequence.
Database Development
In order to pattern the proposed – chosen factors ( see table 1 ) into tabular arraies and later into thematic informations, for GIS usage, the stages undertaken were the conceptual modeling, the logical modeling and the information modeling. Subsequently, after holding collected and analysed the appropriate data/factors from the questionnaires and holding analysed functional inside informations of sustainable agricultural development, the following measure is the Conceptual Design.
– The Conceptual DB Design
Factors and terrain characteristics – objects as analysed and brought to come up by the questionnaire analysis were “ translated ” into thematic beds and this designated their being in the database. The Class Diagram ( fig. 7 ) that follows shows the conceptual informations theoretical account of the used entities – objects.
Figure 7: The conceptual Data Model for Sustainable Agriculture GeoDB development
– The Logical DB Design
At this phase function of entities, dealingss and their properties took topographic point, where Primary Keys and Foreign Keys were identified for each relation, entity and unity restraints were checked, dealingss were validated utilizing the Normalisation technique and the concluding relational scheme was produced.
– The Physical DB Design
Having developed the concluding relational scheme, the following and concluding phase of the database design was the execution of the Database. Tables as described in concluding relational scheme were translated into the entity relationship database with the usage of MS Access. In figure 8 the Entity Relationship Diagram presents the relationships between entities in the database and figure 9 gives the thematic bed informations theoretical account of the geo-database developed through ArcGIS.
Figure 8: MS Access Entity Relationship Diagram
Figure 9: Thematic Layer Data theoretical account used within ArcGIS
Criteria – Evidence bed choice
The standards choice analysis took under consideration the specific demands of vineries with respects to geology, hydrology22, height and other factors. Below are given the standards – grounds beds ( Table 2 ) . In appendix A the selected standards are given along with their standardization. The standardization is given in two columns. The “ scale-calibration ” column gives Numberss burdening the standard in a scope of 0 – 10 and the “ fuzzed sets ” column gives its transition into fuzzed sets as demanded for the Fuzzy Logic Analysis.
No
Criteria – Evidence Layers
1
Convenient Access
2
Distance from Towns & A ; Colonies
3
Distance from Rivers & A ; Lakes
4
Distance from Irrigated Areas
5
Areas with specific Climatologic Characteristics
6
Geological Formation
7
Distance from Quarrying Areas
8
Distance from Protected countries
9
Land Use
10
Terrain Morphology
Table 2: Criteria-Evidence Layers
Establishing MCDM – Fuzzy Logic Organizing
Having decided to utilize the Fuzzy Logic Method, it was selected to use the S-curve equation, since it was considered to be best reacting in the manner that the selected standards are spatially transforming. For the transition of the calibrated standards ( see Appendix A ) into the signifier of equation and the execution of the Fuzzy Logic Analysis the undermentioned equations6 were used:
No
Equation
Word picture
1
I?1 ( I‡ ) = 1 / ( 1+ ( I‡/f2 ) f1 )
Large
2
I?2 ( I‡ ) = 1 / ( 1+ ( I‡/f2 ) -f1 )
Small
f1: the spread of values
f2: the in-between point of the I‡ values
Table 3: Main equations used
With range to take advantage of the legerity given by the S-curve equation, four more types of equations were used, depending on the standard to be converted:
No
Equation
Word picture
1
I? ( I‡ ) = a?s ( I?1 ( I‡ ) )
Slightly Large
2
I? ( I‡ ) = [ I?1 ( I‡ ) ] 2
Very Large
3
I? ( I‡ ) = a?s ( I?2 ( I‡ ) )
Slightly Small
4
I? ( I‡ ) = [ I?2 ( I‡ ) ] 2
Very Small
Table 4: Excess equations used
Having converted, with the usage of the above mentioned rank equations, the standards into Fuzzy Criteria ( Fuzzy Set creative activity ) the following measure is the combination of the standards. The combination had as a range to indicate out the suited countries for vinery cultivations. For the combination of the rank equations, there were used the fuzzed logic mathematical operators Fuzzy And, Fuzzy Algebraic Product and the Gamma Operator as diagrammatically described in figure 10 below.
Figure 10: Fuzzy Groups & A ; Fuzzy Operators
The concluding – optimal site proposals, for the cultivation of quality vineries within Mantinia and the overall Central Pelloponesse are given in figure. The Fuzzy Scaling and the word picture of sites from the least to the most suited are given with different coloring materials shading and are explained on the fable of the map.
Figure 11: Optimum Vineyard Sites
Consequences – Decision
Results & A ; Commenting on the Final End product
The result given in figure11 illustrates Mantinia and the wider country of Central Pelloponesse, with color steps that indicate the suitableness of countries with respects to vineyard cultivation. Areas are assigned to different coloring material depending to a specific factor or a combination of the physical, economical, cultural or environmental factors that contribute negatively or positively rendering the specific countries as useable or non.
The used method is axiomatic that gives great legerity to the research worker non merely because it based on bibliography, existent life cognition and can unite and stand for consequences but besides because all these are based on high degree mathematic equations. This aspect makes the method agile since by giving different scaling harmonizing to specific demands or by fall ining otherwise factors with the fuzzy operators, the concluding consequence is fine-tuned or more orientated towards what is demanded.
Utility of the proposed & A ; used MCDM
The proposed MCDM ( see par. 4 ) , the building of the equal database, the joint usage with GIS and the execution of it on the wider country of Central Peloponnesus ( see par. 7 ) revealed a strong tool for helping, back uping and pass oning. The technique used turned out to be rather accurate, nimble and efficient. Sectors-areas that the proposed tool can help may be:
1 Support-Manage challenges of Agricultural Sector
Future challenges refering sustainable agricultural development, environmental protection, economic system all right tuning and planning of rural/forested countries can be more easy undertaken. The direction and planning chances given by such a tool are a mixture of anticipation, Earth scientific disciplines, dependences, mathematics and object oriented techniques.
2 Assist the Agricultural Sector & A ; the surrounding industry
The proposed MCDM model both supports the agricultural and its surrounding industry. Farmers and investors in agricultural sector can examine-query easy informations ( sing dirt, climatology, H2O, economical parametric quantities, land usage, etc. ) and make up one’s mind on the suitableness of certain countries depending on a assortment of features that may lend to the success of a concern proposal.
On the other manus the MCDM can help the industry environing the agricultural sector non merely because it has the ability to bring forth scenarios and hence contribute to put on the line direction and returns on investings but besides because due to the privileges and cost nest eggs due to the mechanizations given to undertakings and processs and subsequent clip nest eggs, resource direction sweetenings, with coaction of a assortment of stakeholders without the restrictions of clip and distance, that is to state all right melody expeditiously the whole supply concatenation ( storage, transit, bringing, scheduling ) .
All these factors are today what direction stands for and it is what gives a competitory advantage and what produces grosss.
3 Assist Sustainable Decision Making
The capablenesss given by the GIS and the proposed MCDM with respects to accessing and processing of information, gives tremendous support to the determination doing procedure refering agricultural issues.
The proposed MCDM provides an overall model where informations coming from a assortment of beginnings are merged and analysed bring forthing this manner an overall position of specific topics on the agricultural sector refering a assortment of stakeholders, and it can turn into and take the signifier of a assortment of tools such as:
Risk Management and Risk Assessment
Policy Planning ( local or cardinal )
Promote – enhance information ( spacial or non-spatial ) sharing on local or cardinal degree
Project direction and monitoring of Agricultural undertakings, plants, policies or issues
Disaster direction for issues of agribusiness and other refering sectors of economic system
Forecasting tool
Suggestions for future usage & A ; research
The joint usage of GIS and MCDM can be used in a assortment of undertakings on agribusiness on a local or EU degree. Briefly mentioning, for both local and EU degree, these are:
Research on the bing cultivations.
Real clip cultivation and vegetation recording, path of alterations under policies, climatic alterations or natural ( or non ) catastrophes with subsequent production of scenarios on future impacts, disadvantages, dependences and productions.
Construction of an agricultural – environmental database with informations refering agribusiness, economic system and environment ( pesticide utilizations, countries where plagues are used, measures, quality of H2O, air and dirt, etc. ) .
Construction of an agricultural – climatologic database with informations refering agribusiness and climatology.
Research on the joint usage of the above mentioned sectors on an EU degree with deductions for Software, Hardware and Intellectual Capital, with chief range the sustainable direction of agricultural sector.
The end product of the above mentioned issues will be a combination of informations, scientific cognition, practical experience and research “ surrounded-protected ” by natural philosophies, higher degree mathematics ( Multi-criteria Analysis Methods ) bring forthing and positively lending in agricultural, environmental and economical sector, with tools that may:
automatically place cultivation countries.
automatically place agricultural diseases ( or diseases non directly connected to agribusiness ) , issues and deductions that may ensue from negative state of affairss and represent in existent clip effects on the nutrient concatenation and the environment.
automatic appraisal and designation of catastrophes on the agricultural sector from visual aspects of unexpected hoar, ice, inundations, twister or fires, an issue that enhances the effectivity since due to environmental alterations impacts it is non merely a concern of the local degree but besides the cardinal.
Prognosis or modeling of future alterations on land by the combination of all informations available from a great assortment of beginnings.
