Decision Support System of Agricultural Craps and Application of Geagraphic Information System for Site Suitability Classification

THESIS

DECISION SUPPORT SYSTEM OF AGRICULTURAL CROPS

AND

APPLICATION OF GEOGRAPHIC INFORMATION

SYSTEM FOR SITE SUITABILITY CLASSIFICATION

(STUDYAREA

-

JAMBI PROWNCE, Ih'DONESL4)

By:

MIE

MIE

AUNG

P

-

36500006/

MIT

GRADUATE PROGRAM

BOGOR AGRICULTURAL UNIIERSITY

Abstract

Assessing the suitability of an area for Ag,rkcultural craps requirt: a considerable

effort in terms of information collection that presents both opportunities and limitations

to decision-makers. A DSS was dcveluped fur specified crops based an 9 criteria of climatic requirements (average annual precipitation and annual mean temperature) and

the quality arid characteristics of land (slope, drainage, soil texture, soil depth, sail CEC,

sail base saturation, and sail

pH).

The Jmbi Province is the case study area. The main objective of this study was to develop a land suitability decision support: system and to determine the suitability classes for selected crops in study area. The methodology was

concerned to producing polygons included climatic and sail factors; scaring of each

factor coincide with requirements of each crop; grading for the suitability classes based an the total, score and classification of each classes based on thc current land available status. In the system, the user needs to select the most appropriate mnge of each factor (coincide with his soil environment) in the given combo boxes, then at the end of selection it would give the result that is Highly Suitable ($1) when the grade

($1

is equal

to I ar Moderarely Suitable (52) when 1 < S

<

= 2 or Marginally Suitable (33) when 2<

S

<= 3 or Not Suitable (54) when 3c S <= 4. In Jambi, about 47 % of total m a is not

available to change its landuse classes; the rest 53 % is moderately and marginally

suitable far each crop. Only about 0.1 % was found as not suitable for any crop. The

resulted suitability sites will be infamed to the

user

via application AgriDSS software

and WebPages. The next step shauld involve an on-site investigation, Factors such as

water supply, other climatic factors, agronomic practices, or economics that influence the

&cisions of whether land shauld or should not be used for crop production

are

not considered in this assessment.

DECLARATION LETTER

I, Me Mie Aung, hereby declare that the thesis title:

Decision

Support

System

Of

Agricultural Crops

And

Application of Geographic Infbrmation

System

for

Site

Suitability Classification

contains correct results from my own work, and that it have not been published ever before.

All data sources and infarmation used factual and clear methods in

h

s

project, and has

k n examined far its hctudness,

THESIS

DECISION SUPPORT SYSTEM

OF AGRICULTURAL CROPS

AND

APPLICATION OF GEOGRAPHIC INFORMATION

SYSTEM FOR SITE SUITABILITY CLASSIFICATION

(STUDY AREA

-

JAMB1 PROVINCE, INDONESIA)

By:

M E

MIE

AUNG

P

-

365000061

MIT

A Thesis Submitted to the

Graduate School of Bogor Agricultural University, indonwia

In

Fulfiflment of the Requirements for the Degree of Master of Science in

Infarmatiu~ Technology far Na t urn1

Resouras

Management

GRADUATE

PROGRAM

BOGUR AGRICULTURAL UNIVERSITY

Research Title : Decision Support System of Agricultural Craps and Application of Geagraphic Information System for Site SuitahiPty Classification

Student Name : Mie Mie Aung

Studeat ID :

P

-

36500006

Study Program : Master of Sdence in Information Technology far Natural Resources Management

This thesis

is approved

by

the

Advisory

Board:

Dr* Ir* Handoka

Supervisor

Mr. ldung ~ h d i y s n t o

Cu-supervisor

Chaiman of the Study Program

ge-s-SC

Dr. Ir. Handoko

r the Graduate Program

AUTOBIOGRAPHY

The author, Ms. Mie Me Aung, was born an March 7, 1973 in Taunggyi, Shan

State, Myanma. She is the eldest daughter OF

U

Sitt Aung and Daw Khin Than Nwe. As

her educational background, she was studied her basic education in No,4 Basic Education

Nigh School, Taunggyi. In 1990, she was passed her high school

in

No.16 Basic

Mucation High School, Mandalay. She was allowed to study in Yezin Agricultural

University (YAU) in 1993, then she was graduated her Bachelor of Agricultural Science in $996. In 2 W , she was selected as a state scholar to study her master

of

Information Technology for Natural Resources Management in Bogor, Indonesia.

As her employment background, she was worked as

sm assistant: supervisor in

My anmar A d c u l twal Service, Thike-kyi Township, Yangon once after graduated. After

that, she was moved to Yezin Agricultural University in September 1997. Start from that time onward, she is working as a demonstrator in Department of Agricultural Botany, YAU until now.

She has k e n experienced with a Workshop an Production and Utilization of

Mycorrhiza that was opened in Center of Agrrculturd Research Institute,

Yezin,

Myanmar

in 1997; a Training on Hybrid Rice Production, Center of Agricultural

Research Institute, Yezin, Myanmar in f 998; a Training on Maintenance of Cut Flowers, Mngladone Orchid Garden, Mngladone Township, Yangon Division, Myanmar in 1999. In 2001, she was performed as a Lecturer Assistant in Training on Remote

Sensing and GIS Technology for Environmental, System Analysis and Management

@SAM) hat was opened in BTIC, Bogor, Indonesia; as an Assistant in Workshop on Coastal Management and Small fsXand Inventory Using Remote Sensing Satellite System,

BTIC,

Bogor, Indonesia. Moreaver, she got a chance to attend an International Seminar and Exhibition an Information Technology for Sustainable Management of Naturd Resources, which was celebrated in SEAMJZO-BIQTROP, Bagor, Indonesia.

In 2002, she was attended some trainings that were hosted

by

the SEAMEO- SEAMQLEC, Jakarta, Indonesia, They we Hands-an Training in the Production of Web

and CD Based Interactive Multimedia Learning Progs:ms for Online Access, Training on the Utilization of Internet far Instruction and Training Purposes, Regional Training Workshop on Web Based Course Development Using WeKT. She was dso joined with

a Seminar on Towards a More Effective Management of Open and Distance Learning; System held in SEAMEO-SEAMOLEC, Jakarta, Indonesia,

This thesis was come out after two-year study in MIT program. Finally, she

qualified for s S E M O - S E A R C A scholarship fur the MSc in

l

T

for Natural Resources

Management p r o p m e hosted by the Bogor AgriculturaI University (fPf3) and based at

Acknowledgement

In the Name of the Most Mercifil God, we begin. 0 Ever-

Living, 0 Eternul One, by Your mercy I seek Your help, Q Allah, I seek refige with You from distress, grieJ: ittcrrpucify, kuziness, miserliness, cowardice, the burden of debt and from being overpowered by men,

It has been almost two years for my mastering in Infomation Technology for

Natural Resources Management, but

X

have at Xeast reached the finish line. I assure that 1 would not be able to get ithe goal of my study here unlcss you were there, It is

impossible fur me to acknowledge all of you individually here, but my sincere

appreciation is nuEd for dl who grrat1y contributed to improvement of the research.

Start from very beginning, my appreciation gms out to my country, Union of

Myanmar, for allowing me to study the Master degree in abroad as a state scholar.

ConsquentXy, I am greatly indebted to all responsible persons from the scholarship

organization SEAMEO-SEARCA for heir financial assistance for overall expenses

during the wble study period in MIT study program under Bogor Agricultural

University, Indonesia,

Firstly, I would Iike to express my genuine &ank to supervisor Dr. Hmduko,

MIT study program Cuurdinator, for his insightful suggestions, comments, and

constructive critique. Not only his worthwhile guidance on this research but also his

tips on thinking of life in positive ways have made me discharge from all stresses

throughout the development the research. Research under his supervision has k n a

rewarding experience.

Furthemure I would like to tbank my co-supervisor Mr, Idung Risdiyanto, lccturer in Bogor Agricultural University, who aided me greatIy with his insightful

explanations and literatures he supplied me. I have got much more experience on

madeling using visual basic programming language via him for airnost half of this

master study period.

My appreciation gues out to entire resmrch group at BTIC, especially to

AGRISOR, WAIDO, and LUCC organizations, not only for supporting necessary

spatial and nun spatial data of study site Jmbi but also far heir compassionate hands

thrwughout my research period. They never blamed for my harassment by going in and

Mr.

Ir.

Y, G. Armando (M,S), Lxctarer from Agricultural Faculty, J m b i University, far their willingly checking and verfying my data that

X

have been used in this research.

I am thankfully acknowledged a11 staffs horn MIT study programs, fw intimately concerning and treating me like a relative throughout my study period. Everybody has been kind enough for letting me to be here cheerfully, making me stronger and stronger spiritually, and all t h e monument events wauld always be on my mind.

Within the same campus, SEAME0 BIQTROP head office is not forgettable.

AX1 chase generous staffs from tkac headquarters are always h i n g ready to give a

helping barid to MlT students. The only library was a special place where I have hen

most but I am sure that I would not be there without glory of Librarian and other staffs.

A pretty woman who we address I i k Ibu Xn&a was really like a mother and has given

me strength; you are deferential with the ability of salving problems well an the s p t , Moreover, I wauld like to express my profound gratitude to the external

examiner

Dr.

Ir. Muhamad Ardiansyd, Lecturer, Dept. of Soil Science, Faculty of Agriculture, Bagor Agricultural University, who made my thesis acceptable with a lot

of valuable discussions and comments on the find presentation day.

I wish to thank my friends, and fellow students Mr. Ismail bin Hj. Hashin from

Malaysia, Mr. Puvdol l h y d e e from Thailand and Mr. Josemari

B,

Gonzales from Philippines fur their dedicating many hours listening to overall affairs within two years.

Their interaction has helped mc clear my cbougbts and is highly vdued. All MIT students fram junior batch were also k here with me b ask my progress, to give me a

helping hand with a cute smile, to allow me keep on full courage so haw I can stay

without thanking all of you. Moreaver, I would like to appreciate all friends who were concerned all a b u t me physically in person and emotionally via letters by post and also

via online while I studying in Indonesia. Among &em, Naung Naung is the most

understandable and adorable, and I have considered you as my best friend forever.

Finally, but not least,

X

wish to express my gratitude to my parents and family fur their invariable love and invaluable encouragement throughout &e whole life. Whoever says who is the best, nobody is comparable and substitutable with you. 'f

found strength through the support and rriissurances of my parents,

U

Sitt Aung and

Daw Khin Than New, and my sister Ni Ni Aung. I feel very auspicious to have such a

strong, suppurtive and loving family. Unfortunately 1 have got a great chance to

[image:118.605.88.538.141.710.2]

TABLE,

OF CONTENTS

Page No

. .

LIST OF TABLES

...

xn

... LIST OF F I G U W

...,...

...

xm

LIST OF APPENDICES ...4...,...a...a....

...

xiv

...

....

.

1

.

1

.

Background

...

., ,.,

..,....

,,, 1

1.2. Objectives

...

6

2

.

LITERATURE REVIEW

...

7

2.1

.

Decision Support System

...

,...

...

7

2.1.1. Software Development Cycle

...

,.

...

. . 8

2.2. Simulation

.

.

.

.

.

.

.

Modeling

.

.

.

.

.

.

.

.

...,....

.

.

.

.

.

.

.

.

.

.

,,

.

.

.

9

2.3. Geographical Information Systcrns

...

..,

...

10

2.4. The Structure of F A 0 Framework Classification

...

,

.,

...

13

2.5

.

Basic Requirements for Agricultural Crops

...

.,

...

I 4

2.5.1. Climatic Requirements

...,,...

.

14 2.5.1.1. hpartance of Rainfall

...

14

2.5.1.2. Importance of Temperature

...

14 2.5.2. Landscape and Soi t Requirements

...

,

...

15

2.5.2.1. Importance of Topowaphy

...

15

2.5.2.2. hpartance of Wetness..

... ..,

...

16 2.5.2.3. Importance of Physical Soil Characteristics

...

17

2.5.2.4. hporrance of Sail Fertility Characteristics

...

.,

...

18

...

3.1 Materials 26

3.1 .1

.

Time and Location

...

26

...

3.1.2. Necessary Data

2 7

...

3.1.3. Sources of Data 27

3.1.4. Required application hadware and software

...

28

...

3.2 Methods or Methadology 28

...

3.2.1. Schemes af Research 28

...

3.2.2. Method of Suitability Analysis

.

.

.

.

...

29

...

3.2.3. Data Reparation 32

3.2.3.1. Preparation of Rainfall polygons

...

3 2

3.2.3.2. Preparation of Temperature polygons

...

34

...

3.2.3.3. Reparation of Slope polygons 34

3.2.3.4. Reparation of Drainage polygons

...

.

.

...

.

.

...

3 5 3.2.3.5. Preparation of Sail Texture polygons

...

35

...

3.2.3.6. Reparation of Soil Depth polygons 36

3.2.3.7. Preparation of Soil CEC polygons

...

35

...

3.2.3.8. Preparation of Soil Base Saturation polygons 37

...

3.2.3.9. Preparation of Soil

pW

polygons 37

3.2.4. Method of Scoring in the Attribute with all criteria

...

38 4

.

KESULTS AND DISCUSSION

...

39

. .

...

4.1. General Descnpbon 39

4.2. Classification of Land Suitability for Selected Crops

...

39

...

4.2.1

.

Scoring for Rainfall Factor.. 40

...

4.2.2. Scoring for Temperature Factor 41

...

4.2.3. Scoring

fur

S l o p Factor 41

...

4.2.4. Scaring for Drainage

Factor

. 4 i

...

4 - 2 5 Scaring for Soil. Depth Factor 41

...

4.2.6. Scaring for Sail Texture Factor 42

...

...

4.3.8. Scahg for Sol1

Base

Saturation Factor 42

...

4.2.9. Scoring for Soil

pH

Factor 42

...

4.2.10. Suitability Analysis based on Total Scores 43

.

...,...

4.2.1 1 Suitability Classification based on Recent Land Classes 44 4.3. Suitability

Classes

for each selected crop

...

49

...

4.4. Graphical User Interface for

Land

Sui~dbility C1assificatio n. 47

4.4.1. GUI fur Weather Model Farm

...

48

4.4.2. GUI for Suitability Decision fur Spcificd Crop Farm

...

50

...

4.4.3. GUI

for

Map Display Form 52

4.5

.

Building Website for the DSS af Agricultural Crops

...

55

5

.

CONCLUSIONS AND RECOMMENDATION

...

56

...

5.1. Conclusion

...

., 56

5.2. Recommendation

...

57

LIST OF TABLES

Table 2.1. Equivalences between percentage gradient and degree of slope angle

...

16

Table 2.2. The approximate base saturation for the soils of a given soil

pH

...a-

19 Table 3.1. Lists of Hardware and Software

...

.

.

...

28 Table 3.2. Structure af the Suitability Classification

...

30

Tinble 3.3. Relations between Suitability grades and classes

...

30

...

Table 4.1. Suitability Grading Method 4 3

Table 4.2. The sample =suit table from weather model (Daily)

...

50

Figure 2.1. Primary Components of Evalutianruy Development of DSS with

Iterative Prototyping of Specification and Design

...

9 Figure 2.2. Major Data Sources for GIs

...

11

...

Figure 2.3. GI3 for Decision Support 12

...

Figure 3.1. Map of the Study Site 26

Figure 3.2. Research Flow Diagram

...

2 9 Figure 3.3. Flowchart of Suitable Sitc Selection Mcthad

...

31

...

Figure 3.4. Isoh yets in Jambi Province 33

Figure

3.5.

Average Annual Temperature in Jambi Province.

...

3 4 Figure 3.6. Slope percentage in Jarnbi Province

...

34

Figure 3.7. Drainage Properties in Jambi Province

...

35

...

...

Figure 3.8. Soil Texture in Jambi Pravince ., 36

Figure 3.9. Sail Depth in Jmbi Province

...

...,...

,.,,

...

36

Figure 3.10

.

Soil CEC Constituents in Jambi Province

...

,..

...

37

Figure 3.1 f

.

Soil base Saturation Percentage in Jmbi Province

...

37

Figure 3.12. Soil

pH

in J m b i Province

...

...,,...

...

38 Figure 4.1. Suitability grading procedure in ArcView GIs Software

...

43

Figure 4.2. Land Suitability Classes for

Rubber

...

44

Figure 4.3. Recent Land utilization status in Jmbi Province

...,..

.

45

Figure 4.4. Recent Land classes and suitability information for Rubber

...,,...

46 Figure 4 5 Flowchar! for the Main farm of DSS for Agricultural Crops

...

47 Figure 4.6. GUZ for Main Farm

...

...,,... ...

48

Figure 4.7. flowchart for the Weather Model Form

...

49

Figure 4.8. GUI for weather mo&l before and after running the program

...

49

Figure 4.9. Flowchart. far the Suitability Decision for Specified Crops Form

...

51

Figure 4.10. GUZ for Suitability Decision for Specified Crops Form

...

52

Figure 4.11. flowchart for Map Display Form

...

53

Figure 4.12. Jambi Map Display Form ... 53

Figure 4.13. Map Display of Suitability Classes for Cassava

...

54

LIST

OF APPENDICES

APPENDIX - 1 CROP REQUIREMENT TABLE

...,,.. .

...

1 of Appendix

X

APPENDIX - 2 MAPS AND ATIXlBUTE TABLES

OF

LAND

CLASSES AND SfJffABlLZTY PERCENTAGE FOR

EACH CROP

.

...,..

.,,

..,,..

,,..,

. . . .

.

1 of Appendix 2

APPENDIX

-

3 SCRPT FOR MAIN FORM

...,..,,..,.., ,...,.,,..,...

1 of Appendix 3 APPENDIX - 4 SCRlPT FOR WEATHER MODEL FORM

... ... ...

1 of Appendix 4

APPENDIX

-

5 SCRIPT' FOR S'tJTTABILRY DECISION FUR

SPECIFIED CROPS FORM

...,,..,...

,

...,.

.,.

. .

1 of Appendix 5

APPENDIX - 6 SCRIPT FOR MAP DISPLAY FORM

..,...,..,..,..

,.. 1 of Appendix 6 APPENDIX

-

7 AVENUE SCRIPTS

...

1 of Appendix 7

APPENDIX

-

3 CURRENT PLANTATION IN JAMB1

..,

.. . .

. . .

. . .

. . .

. . ..

1 of Appendix 8

APPENDIX

-

9 SAMPLE ATTRBUTE TABLE

OF

SUITABILITY

Preface

The Earth has

been

created for many special purposes. Among those purposes, it is being the main source to give foods fur plants from which the world people are getting foods

far

their Xife. With the increasing realization of the importance of agriculture as a

necessary source for our living, there is a growing enthusiasm m n g us to lean it

deeply, In view of this, a Decision Support System P S S ) was developed based on the bac kgroilnd h o w Xedgc and references on integration with Information Technology. A

system is necessarily needed to simplify in order to be useful for many people at the same

time with stumpy consumption of time and energy. A11 basic necessary criteria were.

referred from the F A 0 land evaluation methods and crop requirements guide

book

from

ITC Ghent. This study investigated the suitability site far some tropical and subtmpical

crops on a global basis by mudding, and Jambi Province was selected as case study ma by using GIs,

The objectives of this research are:

-

1,

To

develop a land suitability system of selected agricultural craps

based

an the F A 0 land evaluation methods and crop requirements guidebook of ITC Ghent, 2, To determine the land suitability classes for each selected crop based on the

spatial, data of crap requirement criteria in thc case study m a by using GIS.

3. To develop a computerized Decision Support System (DSS) comprising of suitability site spatial information, the weafier model and a graphic user interface (GUI) shell to assist policy makers, planners and researchers who involve in planning and promoting various cammercirtl flora production at the provincial level.

There are three major tasks: (1) developing a DSS of selected agricultural crops

based

an crop requirement factors by using Visual Basic Programming Software, ( 2 ) practicing the suitable site selection based on maps of those criteria for each crap in GIS

environment for case study area, and (3) incepting the resulted suitability information of study area in the DSS in order for the user to learn via the system software package. The crap requirement factors and their necessary range in each suitablli ty level were collected

and

prepared as input data far the system. The scares were calculated by giving 1 to 4 for Highly suitctlrle (S 1) ta Not suitable (S4) level respectively far each factor. The final score was averaged fram the total scare and assigned as

S

1 when the find scare was

equal to 1; as S2 when the scare was greater than f and less than or equal to 2; as 53 when the scare was greater tkan 2 and kss than or equal to 3; and as S4 when the score was greater than 3 and less than or equal to 4.

In GIS environment, the climatic factors wcre gemrated from the weather model and shape files for temperature and rainfall were prepared by using Arcview GIs

software. Other soil factors shape files were prepared separately based an the mailable

same file and attribute by using Geoprocessing wizard in Arcview. Scoring was dune for

each crop by using Map Query and Map Calculator on the needs. Firstly, the result was

given in polygons with their suitability levels. It was then analyzed by using recent land

classes and availability status map so that the final suitability classes could

be

resulted.

According to the result

for

each crop, it was concluded that the study area is suitable for a

particular crop at Moderafely srci3able (S2) and Marginally srcikble (S3) level in most case. Suitability percentage is different. far S2 and 53 of a specified crop, Same crops have higher percentage of S2 than that of S3, fax example - estate crops Iike rubber,

cocanut and ail palm are mare suitable than other horticultural crops like onion, cabbage, and carrot in Jmbi.

The resulted suitability infomation maps and some database a b u t study area

were prepared in Graphic User Interfaces by using ESRI MapObjects Tool and MSflexgrid Tool in VB programs. The weather model form, DSS form and Map display

form were linked in rhe main form and it was created as an application software package then it can be run in every computer after installing it, The users are informed by the

system that their particular lucatians are falling in which suitable level in growing a

certain kind of crop. Moreover, the users can learn and download the requirement factors and brief descriptions for each crop, the result suitability infarmation and other

database of case study area through Internet. The web pages wem uploaded to the BXUTROP sewer by using WS-FTP Pro Version 6.60 Software and the site address is

1.1 Background

For agricultural processes, conservation production systems must be implemented to ensure the long-term sustainability of thc soil resource, and in rum the sustainability of agriculture, Producers need sound advice and accurate information on all aspects of their

farm aperations in order to make appropriate conservation farming decisions while also

maintaining the economic viability of their operations, To deal with the many complex issues and numerous alternatives available, thcy need access to available information as well as access to multiple experts, When we we going to deal with information twtmmlagy field and agriculture field, we must know the background knowledge of agriculture well so that we can be able to inkgatc those basic cognizances with infomatian technology atmosphere canvenien tl y.

The Decision Support System (DSS) is playing an important role in decision-

making, The target is to choose the best decision with the lowest risk also based on the knowledge of evaluation of public policy by using the logical, mathematical and

phenomenological models. It is important to understand well about the nature of decision- making

such

as decision structure, saurcc of information, accuracy of information and scope of decision. A decision support system is a computer program that combines

information, knowledge, and human expertise, and interacts with the user to provide

support for decision-making (Bentham, 1992).

DSS is also an approach to development, application and analysis that leverages the community's complementary talents and resources in order to set new standards fur quality of science and reliability of application of agicuXtura1 models. The resulting comprehensive system f u m s the foundation that the community, including governments,

&pa, topology, soil type, sail water content, evaporation rates, climate data etc., as well as

multi- criteria, optimization, habitat analysis, plant growth, andlor yield prediction models

into one system.

The concept of a DSS has evolved aver the last 10 years. As other camputer-based

tools have developed, the potential for integrating a widc range of information sources has

become obvious. These include simulation models, expert systems, databases, graphically-

oriented systems such as gcagraphic information systems (GIS), remote sensing, remote networks, and so on, n u s , the term DSS now encompasses systems that range from tools that assist with a well-defined problem area to those which are open-ended in their application, from programs that are pure expert systems or sirnulatian models to those which combine many approaches, from systems which q u i r e a computer and trained users to those which stimulate interactions between mangers at a sacid level. All have the common god of improving decision making and providing users with the means to assess alternative outcomes against each other objectively and comprehensively than could be done previously.

Decision makers must intepte information an climate, soils, vegetation, animals,

economics, and politics in making their decisions, and they must do this across a

heterogeneous environment. At each level, these factors fall into a hierarchical order, dependent on scde in time and space. Wcisions should aim at, sustainable land use, which

means optimizing productivity within the constraint of avoiding land degradation. h d

degradation, or desertificatian, can be defined as the lass of potential productivity, where the measure of productivity must be related to the goals of land use. Degradation can

occur at dl Ievels of the production system by altering the ability of the land to respond to climate, changing soil characteristics through hoof impact or erosion, altering vegetation

composition through inappropriare timing, even degrading the economic viability of an enterprise through the use af undesirable gcnetic stack or ill-advised financial decisions.

En determining

what issues are important to decision makers, it is also important to recognize that theoretical and real priorities may also differ for each of these levels of use,

sustainable viability of management systems, in practice, policy decisions inevitably need to

bc

able to take account af political constraints, Similarly, individual managers may

espouse long-tern sustainability as a preferred goal but still have to c o p with meeting

debts, sending tire

kids

to school, or just wanting a particular lifestyle, Wany of these factors are imponderables that cannot be handled directly by a DSS, but the recognition of their existence can help with appropriate dcsign approaches, interface design, and with

training and implementation.

Finally, there is a hierarchy of scales far decisions, especially for palicy makers

where decisions range from regional though state to national and even trading block or

global levels. h a simpler sense, individual managers too may be concerned abut a single enterprise or may

bc:

part of a larger multi-enterprise or rnultilocation concern. In general, as the scale gets larger, extrinsic constraints change into management must consider. As

the unit becomes larger, these factors become more controllabk. A DSS that is appropriate to one scale of decision-making may be very inappropriate to another, since DSS is concerned with efficient model links between input and outputs and should, therefare, abstain unnecessary details that require greater data collection and efforts in validation, The DSS projat must identify the different perceptions, priorities, and

problems correctly and target them appropriate1 y.

Models are, a widely used instrument in science when complex problems and

complex systems are under investigation. It is impossible to solve a quantitative model,

which represents a system with many variables in equations, by using normal algebra or calculus; managed systems are too complicated fur that We therefore make use of

sirnulation, meaning that we will create a set of equations to represent the system and tfim

allow the equations to run forward in simulated time to attempt to mirror the behavior of

the real. system as it runs furward in real time, In principle, one could nun the equations fuwrnrd by pencil and paper calcuf ation; in practice, a computer and specialized software

Land suitability is the appropriateness of a given type of land for a specified use. The land may be considered in its present condition or aftcr improvements. The process of

land suitability classification is the appraisal and grouping of specific areas of land in

terms of their suitabiiity for defined uses, First, the structure of the suitability

classification should

be

described and then followed by an account of the range of

interpretative classifications recognized: qualitative, quantitative and of current or potential suitability, A specified crop can be cultivated with respect to each kind of land use that appears to bc relevant for the m a .

It is necessary to forecast the benefits to farmers and the national econumy and whether these will

be

sustained without damage to the environment. Essentially a

classification of potential suitability is required which takes account of future interactions

between sails, water, craps and econamic, social

and

political conditions.

Some

factors chat affect land suitability are permanent and others are changeable at a cost. Typical examples of pmment features are temperature, sail texture, depth to bedrock and macro- topa~aphy. Changeable characteristics that may be altered deliberately or inadvertently typically may include vegetation, salinity, depth of groundwater, and same social and economic conditions (e.g. land tenure, accessibility).

Land

suitability must therefare

be

assessed and classified with respect to specifled kinds af land use.

It is evident that an interdisciplinary approach is required, because no one

discipline can cover all aspects of land suitability evaluation. Land evaluation can

be

carried out: using general. economic considerations to establish a context for sclectcting

appropriate crops and management, and to establish the criteria for boundaries between

suitable and unsuitable land. To make a quantitative evaluation at project or farm level, however, requires formal analysis in financial and economic terms. h d evaluation is an

iterative process leading to successive refinements and the need for surveys and investigations that are appropriate in scale and intensity during the different stages from recamaissance to detailed project planning, and thereafter in successive phases of project implementation.

Simulation is a kind of modeling which is useful for wide range of problems and

very good data, or very little data. It has important implications for disciplines such as swial anthropology that are basically non-experimental, providing a means of exploring

problems which could never be observed to order. Simulation is not a panacea for all of

our problems, but it can be an important tool fur the social researcher aware of its

limitations.

Agricultural management can be a daunting task because so many factors must

be

taken into account. Agricultural decision making involves understanding not only the immediate impact of human activity an the various crops, issues regarding soil conservation, climatic condition, economic costs, current and pending regulations, fairness, and a host of others. In principle, all of these interrelated factors have a bearing on any decision related to the agriculture and its environment. A good design should avoid

lucking the project into a rigid solution with little flexibility or adaptability in case problems occur later an or changes in the enviranmcnt &mand changes in project pcrfamance or effectiveness,

Geographic Information System is any manual or computer based set of procedure

used to store and manipulate geographically referenced data. As

GIs

is a computer-based

system, we need four sets of capabilities that arc inputs, data management, manipulation

and analysis, and output to handle geareferenced data. It is also st powerful tool for handling spatid data. Generally, a GIS project can be organized into a series of logical

steps, each of which builds upon the previous one, Many GXS projects need to follow a similar sequence. However many considerations influence the design and implementation of a specific project. Before stating the project, it is impartant to determine the objectives of the project. We need to consider what the problem is to be solved, how it: is salved,

what the final products are, how these products might frequently be generated, and so on. These issues affect the scope of the project and its implementation.

ArcView is a powerful deskap geographic information system (GES) made by

Environmental Systems Research Institute, Inc. (ERSf). With Arcview, any data that: is linked to geographic locations can

be

loaded and displayed it graphically as maps, charts,

questions or to meet certain criteria, and the information can be analyzed statistically as

well as spatially. Then the results can be shown as quality graphic presentations to print

out or display on the screen.

1.2 Objectives

1 . To develop a land suitability system of selected agricultural crops based on the F A 0 land evaluation methods and crop requirements guidebook of ITC Ghent. 2. To determine the land suitability classes for each selected crop based on the

spatid data of crop requirement criteria in the case study area by using GIs.

3. To develop a computerized Decision Support System (DSS) comprising of suitability site spatial information, the weather model and a graphic user interface (GUI) shell to assist palicy makers, planners and researchers who involve in planning and promoting various carnrnercial flora production at the

provincial

2.

LITERATURE lREVIEW

2.1 Decision Support System (DSS)

DSS is a process of choosing mong alternative courses of action for the purpose

of achieving a god that consists of the following components: Data Management

Subsystem, Model Management Subsystem, Dialog Management Subsystem, and Knowledge Management Subsystem. Because of the interaction among the multitude of factors affecting a complex decision, it is essential to identify the important ones and to

determine the degree to which they affect each other before a clear decision can be made.

Based on the issue of how to structure a complex situation, identify lits criteria and other factors whether intangblc or concrete, it can be measured the interactions among

them

in

a simple way, and can also

be

synthesized all the information to obtain priorities. The priorities can then be used in a hnefitlcast setting to devdap portfolios of activities, one af the major concerns of corporations, government and other organizations with different

goals and purposes, (Turban, 1988).

A DSS does not necessarily attempt to model the derails of the human interaction

with the biological and economic system, but rather to model the inputs, the outputs, and parameters that are likely to affect which alternative is implemented (Gillad and

Monypenny, 1988). Computer-bssed DSS aim to

be

flexible, with integrated software for

accessing, retrieving, and generating reparts

on

database information, as welt as king

able to accommodate simulation and decision models for conducting further analyses

including alternative testing, sensitivity analysis, and automated goal seeking (Belew,

1985; Covington et al., 1988). A true DSS has the added flexibility af allowing users to define new relationships mong decision variables (Caaney, 1986) so that users have the freedom to analyze decisions in a manner not anticipated by system designers; however,

many DSS do not cumntly p m i t this capability.

DSS are a valuable mechanism for organizing infurmation in a way that allows

and perception son the planning process (Stuth et al., 1990). DSS thus have a special

capability to aid problem solving in selection af suitability area fur agricultural crops.

In

such selection, it encompasses a particularly wide range of issues appropriate to DSS solutions, thus making them a focal point when discussing uses of DSS. In this thesis, the

practical application of these points will be illustrate by showing haw different types of

systems can be linked in DSS to handle very complex questions.

Improved political decision making and better on-thc-ground maxxagemcnt can

only result from more objective, consistent, and timely information about: the issues

involved, DSS aim to integrate very different types af information into a cumman framework; they seek to provide assistance in the context of the special features of

individual decisions rather than generating generalizations, and, above all, the development of DSS focuses an understanding which decisions we important to different

users. Infomation must be organized to

be

of value, whether at the individual or policy

Ievel of decision-making. With the advent of computer technology and the exponential expansion of infarmation about: natural resource management, DSS has helped provide a logical framework fur this organization (Stafford Smith and Faran, 1988, 1990; Stuth et al,, l99Q). DSS also assist managers in dealing with complex planning problems and in selecting appropriate technology. DSS in natural resources are similar to rhose in other

businesses in that they are designed fox a specific problcm ma, they incarporate

specified planning horizons, and they guide decision-makers through a process of logical planning and assessment of alternatives (Taylor and Taylor, 1987).

2-1.2 Software devdopment cycle

Eason f 1988) recommended an evslutianary devebprnent of

DSS

with iterative

prototyping of specification and design (Figure 2.1). The guidjng principle is the creation

of opportunities for learning from practical experience before major design decisions are

taken. This procedure minimizes the need for major commitments to technical developments in the early stages of development while allowing the users considerable opportunity to see and test what, could be provided, thus allowing them to arrive at a

[image:134.608.82.541.80.327.2]

Figure 2,1 Primary components of evolutionury h e l o p m e a t of decision support systems

{DSS) with ifem five prototyping of specificabba and design (Adapted from Eason, 1988)

Design

Team

2.2 Simulation Modeling

Specify Broad Detailed Evaluation and User Support,

Requirements Specifications Iteration Review and

1

I J Iteration

The core of many DSS will always

be

good simulation model, varying from

simple spreadsheet-style aids to complex mpresentations of system function where the data and the understanding exist. To maintain credibility with the more complex

hydrological, plant growth, and other environmental models, developers will need to pay

greater attention to controlling model campXexity far the sake of users and their input data needs while maintaining the quality and integrity of results. A more explicit hierarchical

approach to developing simple application models for specific areas

fram

more complex

and

generalized research models may

be

one necessity. Good model validation and verification will certainly be another. The first step in model building is to state clearly the specific objectives of the modeling effort. Once the modeler has a clear understanding

of the problem and objectives to be accomplished, other important design questions can

be

addressed, such as what types of dava are available, what kinds of inputs will

be

required, what kinds of output will be required to meet the objectives, and what the intended use of the model will be. The answers to these questions will guide rhe modeler's approach to meeting the objectives (Gillard ef ak, 1988)

Technical

Development

v

~rorotype ~ l a t &tern Operational Evolutionary

Development Design and Systems Design Development 1 Impleqentatian

and

hplqnmtation I

System

A

and Feedbac tck

Operati nal Use Widening Use

Use

Simulation can & defined in either a broad or narrow sense, In the narrow sense simulation is a model where we are attempting to describe thc behavior of a system by

incrementally and interactionally applying a number of models against some starting

situation. In the broader sense, ir is any kind of computer model within which some

structure is being modified along one or mare dimensions.

In

the usual case one dimension is time, but this is neither sufficient nor necessary for a simulation; it is the

modeling

of any complex system where observation of change, or an incremental

process, is central. Traditionally simulation has been a technique used for quantitative

analysis. As with computing techniques in general this is due to the historical development of computing and constraints on our knowledge of haw to represent. models

and infomation af a qualitative and symbolic farm. Designing a simulation involves

translating the essential aspects of preexisting models into a fom chat can be

implemented an a computer so that monitor the interaction of the models can be monitored. Simulations usually require programming of some sort since any computing

language has a limited set of resources available for representing dara, information,

relationships and transformations that can be applied. As a specific problem comes along with a researcher, it i s important that the design devclup according to the needs of the

research, and not from the needs of the computer. So it is better to make the simplifications and compromises at the later stages rather than the earlier :roes of the

design. In this way the requirements can

be

considered in det'ail, and can better judge how

to solve the more mundane problems uf implementation. (Fischer, 1996).

2.3 Geographical infarmstian Systems (GIs)

Geographic Information System (GIs) is a computer-based system used to stare

and manipulate geographic information, 'It is designed fafor callectian, storage, md analysis of objects and phenomena where geographic location is arr important: characteristic or critical to the analysis (Aranaff, 1991).

G S

is defined as an information system that is used to input, store, retrieve, manipulate, analyze and output

geographically referenced data or geaspatial data, in order to support decision making for planning and management of land use, natural resources, environment, transportation, urban facilities, and other administrative records. A computer system for GIS consists of

analysis, modeling and display of geospatid data, The sources of geaspatial data axr: digitized maps, aerial photographs, satellite images, statistical tables and other related

documents (Figure I ) (Murai, 1996).

Analog M a p

Figure 2.2 Major data sourcesfor GI5 (source: Murai, 1996)

Geographic infamation can be represented with geometric infarmatian such as location, shape and discribubon, and attribute infomation such as characteristics and nature, Vectors and raster farms are the major representation models for geometric information. Most objects on a map can

be

represented as a combination of a point (or node), edge (or arc) and area (or polygon), which are vex tor farms. A point is represented by geographic coordinates. An edge is r e p ~ s n t e d by a series af line segments with a

start point and an end point. A polygon is defined as rhe sequential edges of a boundary. The inter-relationship between points, edges, and weas is called a topo1ogicaI

relationship. In the raster form, the object space is divided into a group of regularly spaced grids (pixels) to which the attributes are assigned. The raster form is basically identical to the data format of remote sensing data (JARS, 1993).

GIS can be a very important tool in decision making for sustainable development, because GIs can provide decision makers with useful infomation by m a n s of analysis

and assessment of spatial database as shown in Figure 2. Decision-making including policymaking, planning and management can be interactively implemented taking into consideration human driving farces through public consensus. Driving forces include population growth, health and wealth, technology, politics, economics etc. by which

human society will set up targets arid gods on how to improve thc quality of life.

models for different purpose like the flow of water, crop growth, soil erosion, nutrient

and pesticide leaching. GI$ helps in integriating geographical, drnta on various aspects such

as soil, crop, weather and field history along with simulation models. Another aspect of

CrIS support to precision adculture is the engineering component, in which the research

findings are translated into operational systems for use at

farm level.

GIS can support this

engineering activity by providing a good platform far starage of base data, simple modeling, presentation of results, development of a user iinterhce, and, in combination

with a W S , controlling the navigation of farm.

On

the basis of GIs, a decision support

system can be developed for operationalisation of precision farming at f m level (Bregt,

-

Lrrdu-tion

- C o n ~ c t i o n

-

E n e w

uus Public Awarmaa

Cr

-

r n d use c h i g e

- C h g c of Life Style

-

h n d Degradation

-

Pollution

-

Climate change [image:137.607.211.443.301.578.2]

Remote Sensing

Figure 2.3 GIS for Decision Support {Source: Murai, 1996)

Many farm information systems (EIS) are available, which use simple programmes to create a fann level database. One example of such FIS is LURfS (Local. Resources Information System) consists of several rnudules, which enable the data import; generation af raster filcs by different gridding mcthods; the storage of raster infomatian in a database; the generation of digital am-resource maps; the creation of

2.4 The structure of the

F A 0

framework classification

T h e F A 0 Framework indicates that: it is necessary to evaluate land and not just soils. The suitability of soils for irrigated crops is useful information but it is inadequate

for

making

decisions about land use development. Therefore all relevant land

characteristics including soils, climate, topogmph y, water resources, vegetation etc. and

also socia-economic conditions and infrastructure need to

be

considered. According to the FAO, four categories, namely Orders, Classes, Subclasses and Units are recognized in

the FA0 Framework classification (FAO, 1985):

1, Land Suitability Orders reflect

kinds

of suitability (i.e, Suitable and Not Suitable);

Suitable land is land an which sustained use of the kind under consideration is expected to yield benefits that justify the inputs and development: casts, without unacceptable risk of damage to land resources. Not Suitable indicates that: the land has qualities that appear to preclude sustained use of the kind under cansi&ratian.

2. Land Suitability Classes reflect degrees of suitability within Orders (i.e. S1, 52,

53, N 1 and N2);

a. Class $1, Highly Suitable:

Land

has no significant limitations to sustained

application of a given use, It may include minor limitations that will not

reduce productivity, benefits or costs b l o w the lower boundary set for the

class.

b. Class 52, Moderately Suitable: Land has limitations that in aggregate are

moderately severe far sustained application of a given use. The limitations

may weducc physical productivity, benefits or costs camgarcd with S1 land to a lower limit set far thc class.

c.

Class

$3, Marginally Suitable: Land has limitations which in aggregate are

severe for sustained application of a given use and will so reduce physical

productivity, benefits or casts that the expenditure will only be marginally justified.

d. Class.

NX,

Marginally Not Suitable: h d is marginally not suitable and has limitations that may

be

surmountable in time but which cannot

be

corrected with the existing knowledge or under present social conditions

e, Class

NZ,

PermanenB y Not Suitable: Land is permanently nut suitable for the given use usually because of physical limitations,

Classij5cation of Currerat and Potential Suitability: A classification of current suitability

refers to the suitability for a defined use of land in its present condition, without majar improvements. A potential suitability classification refers to the suitability, for a defined use, of land units in their condition at sam