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THE USE OF FUZZY SET FUNCTIONS FOR ASSESSING LAND SUITABILITY INDEX AS THE BASIS FOR ENVIRONMENTAL MANAGEMENT

  1. 1. International · ISSN0853-7674 Agricultural ScientificJournal / :)]I I · + . GAKURYOKU Volume XII, 3, 2006 October 2006 1. The use of Fuzzy Set Functions For Assessing Land Suitability Index as the Basis for Environmental Management (Owi Putro Tejo Baskoro and Eduardo P. Paningbatan) .............. ....................... .. ..... 1 2. Mineral composition of Shallots Bulbs (Allium ascalonicum. L) (June Mellawati and T.M. Nakanishi) .. .. ............... ... ......................................... 6 3. Handling of Arenga pinnata (Wurmb.) Merr. Seed to Provide High · Quality Seedling (Muhammad Salim Saleh, Tati Budiarti, H.M.H. Bintoro, E. Murniati and Y. Yamamoto) ................................,........... ..... 9 4. The Influence of Sauropus androgynus (L.) Merr. Leaves on the Body Weight Change and Calcium - Phosphorus Absorption in Lactating Sheep (Agik Suprayogi and Udo ter Meulen) ........................................ 13 5. Morphological and Essential Oil Characterization of The Banda Nutmeg (Myristica fragrans H'outt.) of Moluccas and North Moluccas Ecotypes (llyas Marzuki, M.H. Bintoro Djoefrie, Sandra A. Aziz, Herdhata Agusta, Memen Surahman and H. Ehara) .............. ......... :..... 17 6. The Effect of Green Tea and Ginger on Homogeneous, Acidity, and Protease Activities of Skim and Whole Milks (Tatik Khusniati, Herlina Purwiyanti, Nunuk Widyastuti and Zainal Alim Mas'ud) ................. ..... 22 7. The More Precise Medium Modification and Sterilization Level on In Vitro Propagation of Mushroom (Syammiah, Efendi, and Laura S MeitznerYoder) ................. ...................................................................... . 27 8. .Grazing Tolerance of Normal and Dwarf Elephantgrasses Pasture at the First and Second Years after Establishment (Muhammad Mukhtar and Yasuyuki Ishii) .. ................... .......................... ...... ............ .. .... .... ...... 31 Published by The Association of Indonesian Alumni from Japan (PERSADA)
  2. 2. Chief Editor Prof. Dr. H. M. H. Bintoro Editors Prof. Dr. Yoshinori Yamamoto (Kochi University) Prof. Dr. Hiroshi Ehara (Mie University) Prof. Dr. Kopli Bujang (University Malaysia at Serawak) Prof. Dr. N. Kubota (Okayama University) Reviewers Dr. Suwardi (Soil Science) Dr. Upik Kesumawati Hadi (Veterinary Medicine) Dr. Ari Purbayanto .(Merine Science) Dr. Asep Sudarman (Animal Science) Dr. Lilik Budi Prasetyo (Forestry) Dr. Erizal (Agriculture Engeneering) Dr. Yoni Koesmaryono (Agroclimate) From The Editor The Gakuryoku Agricultural Scientific Journal is published by the Association of Indonesian Alumny from Japan. The articles in th is Journal are the result of Agricultural and life Sciences. This Journal is In­ ternational Journal. In this edition, the articles consist of soil science, mineral composition, seedling quality, tissue culture, and animal science. The editor invite scientists all over the world to . contribute and publish articles in this journal Bogor, October 2006 Editor Address Sekretariat PERSADA Cabang ·Bogor JI. Raya Pajajaran, Kampus IPB Gunung Gede Bogor . Telp. 02S1-3S6833,Fax. 316178, Telp'/Fax. 623410 E-mail: uptbsipb@indo.net.id; editor_gak@yahoo.com
  3. 3. Gakuryoku Volume X II No.3, Th. 2006 THE USE OF FUZZY SET FUNCTIONS FOR ASSESSING LAND SUITABILITY INDEX AS THE BASIS FOR ENVIRONMENTAL MANAGEMENT Dwi Putro Tejo Baskoro 1 and Eduardo P. Paningbatan 2 I Department of Soil Sciences and Land Resources, Faculty of Agriculture - Bogor Agricultural University. Jl Meranti, Kampus IPB Darmaga, Bogor Email: tejo2baskoro@Yahoo.com 2 Department of Soil Sciences UPLB, Philippines ABSTRACT A study is conducted to evaluate the potential use of Geographical Information System (GIS) for land suitability assessment. PC-based GIS softwares are used in analysis, processing and mapping spatial data. This paper presents a spatial modeling procedure for the assessment of land suitability by using Fuzzy Set Functions in Geographical information Systems (GiS) environment. This technique involves the creation of membership maps for every land attribute used as the basis for evaluation criteria adoptedfrom FAG. The study shows that Fuzzy method results in aflexible land-suitability index for identifying and delineating land management units and the suitability of the unit for specific land use. Land suitability map for rice, upland annual crops and coconut derivedfrom Fuzzy method shows that the suitable areafor rice and other annual crops with suitability index 0.5- 1 is about 57 % ofthe study area. The highly suitable areas for the two land use types are especially found in level to gentle slope. Suitable area for coconut covers about 68 % of the study area. Key words: GIS, Fuzzy set/unction, Suitability Index, Environmental management INTRODUCTION A proper land use decisions is of a great impor­ tance to achieve optimum productivity of the land and to ensure environmental sustainability. This re­ quires spatially accurate information of land re­ sources and effective management of the informa­ tion on which such decisions should be based. Land suitability evaluation is one of the effective tools for such purposes [I]. Land evaluation is a tool to predict land perform­ ance, both in terms of the expected benefits from· and constraints to productive land use, as well as the expected environmental degradation due to these uses and can employe as a preliminary to more de­ tailed investigations [2;3]. Therefore, for land to be suitable (for a given purpose) and for the use to be sustainable, it must address the values that are re­ lated to both aspects: degree of suitability and poten­ tial degradation (from long-term perspective) result­ ing from land management practices. Land suitabil­ ity analysis shou Id consider' both aspects of land evaluation, and a GIS may be used to facilitate every stage of the evaluation processes [4]. The paper demonstrates the use of GIS for land evaluation processes. The main purpose is to establish indices of land suitability for cropping land use systems A fuzzy set methodology is employed in the modeling procedures where the classes do not have sharply defined boundaries [5;6]. MATERIALS AND METHOD The area selected for the study include some wa­ tersheds in North-Eastern Laguna covering an area of approximately 90.000 Hectares, located about 60 km, to the east of Manila-the Capital of the Philip­ pines. In the application of fuzzy set functions, soil at­ tributes maps are used as the basis for generating membership function of every land attributes to rep­ resent their suitability rating. Model parameters used for generating the membership function for three selected land use are based on FAO [7]. Once the model parameters have been determined, a member­ ship function for each land attributes is generated. A joint membership function (JMF) of combined land attributes is then determined by using the minimum operation as follows [8]: Result (JMF) = Min ( MFa, MFb, MFc, ....). where Mfa, MFb, MFc are memberships function of land attributes. Memberships functions used for fuzzy member­ ship classification consists of two basic models: symmetric and asymmetric [9]. The symmetric mod­ els consist of two types: one using a single point as the central concept (Type I), while the other em­ ploys a range of ideal points (Type 2). The asym­ metric model uses the lower and upper boundaries of a class. This model also consists of two types: asymmetric left (Type J) and asymmetric right (Type 2). The computation of criterion membership functions is based on the following equation: Type I : MF(xi) = [J/(i + {(ri - b)/e/)] Type2 : MF(xi)= I if(b+eJ) < xi«c - d2) Type 3 : MF(xi)=[J/(J + {(xi-b-ei)/el/)]ifxi < (b + el) Type 4: MF(xi) = [I/(l + {(xi - c + e2)/e2}2)] ifxi > (c - e2) The choice of membership function to suit deci­ sion criterion depends on the trend of performance of a land attribute in creating a favorable condition
  4. 4. Volume XII No.3, Tb. 2006 Gakuryoku for selected land use. Model parameters used include ideal point (b and c) where the MF is set to be 1, zero points (a and d), and e (width of transition zone which is a distance to cross over point-CP, the point representing situation where a land attribute exam­ ined is at the marginal level for a given purpose). Some examples for deriving model parameters are illustrated at Figure 1. In calculation joint membership function, the land attributes are assumed to have equal weight. The idea is that these land properties represent land variables having an equal importance to each other. There is no tradeoff between the land variables. For example, very steep slope of a land area (or block) cannot be compensated for by the excellent quality of soil profile, or vice versa. Results of the minimum operation are Land Suitability Index (LSls), ex­ pressed as continuous values ranging from 0 (very poor or fully not suitable) to 1.0 (excellent or highly suitable). These land suitability indices could then be reclassified to generate land suitability rating map based on the user-defined criteria. RESULT AND DISCUSSION An example of land suitabi Iity index of the study area for annual crops resulted from Fuzzy Approach is given in Figure I. The figure shows that land su itab iIity of the study area for upland annual crops is expressed as continuous values ranging from 0 (fully not suitable) to 1.0 (excellent or highly suitable). This continuous expression provides that the fuzzy approach is more flexible than the traditional approach which usually results in classes with strict border (highly suitable, moderately suitable, marginally suitable and not suitable). The flexibility presented especially in term of the decision to what level of suitability index the suitability rating should be set. As the acceptance level of the suitability index is lowered, the propor­ tion of the total area assigned as the desired suitabil­ ity class increases. This imp lies that if, for example, the suitable area obtained for a give land use is lim­ ited and not sufficient to satisfy the basic minimum area then the land suitability index can be justified to increase suitable area obtained within the acceptable range. Nevertheless, it does not necessarily mean that contiguous regions of 'l given minimum size larger than the area sized used for mapping can be located anywhere. . Assuming that the highly suitable area in fuzzy approach corresponds to 0.8 to 1 land suitability index value, the result also shows that the suitable area obtained from Fuzzy Approach is much larger than that obtained from Trad itional approach (Table 3). In Traditional approach, the intersection only accepted sites that match all the strict requirements. Many sites would be rejected in this manner, espe­ cially if there are many sites having a value of one or more attributes just lower or higher than the class boundary. By accepting sites that are just outside the ideal strict matching, the coverage area that can be judged 2 as highly suitable can be increased substantially without any change in the original class limits ap­ pi ied to the observations. The evaluation of the result obtained by fuzzy approach is also undertaken by using cross compari­ son analysis. An analysis was made by establishing fuzzy membership function (MF) values of land suitability rating obtained from Traditional approach (LST), then comparing these values, based on their corresponding position to MF values of fuzzy ap­ proach outputs. Membership values of LST are gen­ erated as follows: (Category, MF value) = {(I; 0.9), (2; 0.70), (3; 0.50), (4; 0.30), (5; O.I)} There are about 500 points for this validation ex­ ercise, distributed randomly over the study area, using stratified random sampling technique. The root mean square error (RMSE) for the corresponding points is then calcu lated, and the resu Its were pre­ sented in Table 4. Based on spatial comparison analysis, it is found that the variations of land suitability index tend to increase from the area with high suitability classes to medium suitability classes. This is in accordance to land suitability classification study conducted by Burrough et al. [10], who found that the use of Tra­ ditional-based categorical system of land suitability analysis had resulted in the rejection of considerable suitable areas. As the result, the land suitability in­ dex variations of the lower class increase. The fuzzy approach used thus demonstrates its significance for fine discriminations of land qual ity in the area of interest. As has also been demonstrated by Burrough et aI., [10], fuzzy classification approach allows a user to retrieve data and classify them as normal, but includes the advantage of user-defined criteria (with a certain tolerance level) the class limits in the form of the transition zone. Since the information is not thrown away by strict classification early in the analysis, the user can see which attributes contribute most to the final result. It has been demonstrated that fuzzy approach used integrates various land attributes to establish land suitability index for the selected crops. The fuzzy approach utilizes membership function-fuzzy set methodology in the assessment procedures, and the results presented in a continuous pattern. Land suitability index is generated by using actually three basic land variables climate, soils and topography. The three land variables are combined by using minimum function assuming that they have equal importance to avoid tradeoffs between them. Land suitability index produced in this study may serve as a guide to determine what areas can be opened up for agricultural land and what land use management practices is the most appropriate for the areas. It is related to the importance of assessing and identifying the spatial pattern of land suitabil ity of the planned area for selected land use. Nevertheless, the land suitability index resulted from Fuzzy Ap­ proach does not indicate the limiting factor acting in the area for the selected crop as it is in land suitabil­ ity class obtained from conventional approach.
  5. 5. I Sf,: Mana 'I .,,-,,~'i " 121 "00' 1~ r..lJ· Land Suitability Index LAGUNA PROVINCE U...~ /.L...- 114030'I . • Milllil,l , Lft.GUNA DE BAY ,- ' l... ~S' )~/ ,./' ~ ~ . L--_____-, 7") PRO. ICE ~ w San Pablo CI~-~LEG END d!t.nr ,_ Province 80un -~..,....V-- 14°00' Main road B Studl' A rea N A Meters 10000.00 {-1. REPUBLIC OF THE ,rI I PHILIPPINES 'v.~~ LAGUNA PROVINCE ," -~O ,P~S:i ~ "~~ c::It' /" J "!-:; ,/': '1!f~:.''~" • <> !,.,s " ~ Figure I. Land suitability index of the study area for upland annual crops obtained from Fuzzy approach ~~ :;;: ~ c ~ :;;: ~ ~ "= ~ '" ~>-; '" ~ ~;." ~ f'..,,) C) C) C'
  6. 6. Volume XII No. 3, Th. 2006 Gakuryoku MF MF UCP 0 bLCP 1.0 1.0 .~ a 6 0 0 30 60 Drainage rating Soil effective depth (cm) a) MF for soil drainage b) MF for soil depth MF MF b c uCPLCP c UCP 1.0 ..........~ ......;. 1.0 0.5 0.5 . ·· · o o3.0 4.5 6.0 7.0 8.5 10.0 2 15 30 Soil pH Slope Gradient ('!oj c) MF for soil pH d) MF for slope grad ient Figure 2. Membership function of selected land properties: drainage (a ), soil depth (b), soil pH (c), and slope gradient (d) Table 3. Coverage area of land suitability rating for selected crops resulted from Boolean approach and fuzzy approach SUITABILITY RATING COVERAGE AREA Rice Annual crops Coconut Hectares Percent Hectares Percent Hectares Percent Tradilional approach Highly suitable 7751 8.5 65 0.1 7393 8.1 Moderately suitable 23734 26.1 10800 I1.9 15066 16.6 Marginally suitable 19378 2lJ 37444 41.2 38903 42.8 Sub 10lal 50863 55.9 48309 53 .2 61363 67.5 Currently not suitable 16567 18.2 19122 21.0 18343 20.2 Permanently not suitable 21846 24.0 21845 24.0 9569 10.5 Sub lolal 38413 42.2 40967 45.0 27912 30.7 Suilability index from Fuzzy approach 0.9 ­ 1.0 18590 20.5 10340 11.4 16665 18.3 0.8 - 0.9 16516 18.2 7830 8.6 24813 27J 0.7 - 0.8 6053 6.7 16745 18.4 8401 9.2 0.6 - 0.7 5273 5.8 6798 7.5 5575 6.1 0.5 - 0.6 5227 5.8 9357 10.3 6581 7.2 Sub lolal 51658 56.8 51070 56.2 62035 68.3 0.4 - 0.5 3706 4.1 3706 4.1 3361 3.7 OJ - 0.4 3211 3.5 3211 3.5 2845 3.1 0.2 - OJ 3067 3.4 3655 4.0 2361 2.6 0.1 - 0.2 4198 4.6 4198 4.6 8228 9.1 0.0-0.1 23434 25 .8 23434 25.8 10444 11.5 Sub lOlal 37616 41.4 38204 42.0 27240 30.0 Therefore, the combination of land suitability index and land suitability class may be used as a good ba­ sis for identifying and defining land management units, and serves as a spatially-based making parameter in land use planning. decision­ 4
  7. 7. ... Gakuryoku VO/llme XJJ No.3, TIJ. 2006 Table 4. Root mean square error (RMSE) values for land suitability index obtained from Fuzzy approach against land suitability from Boolean Approach BOOLEAN NUMBER AVERAGE RMSE SUITABILITY CLASSES OF POINTS LAND SUITABILITY INDEX Rice I 40 0.937 0.097 2 147 0.873 0.177 3 101 0.698 0.227 4 93 0.3 12 0.149 5 I 15 0.003 0.097 ___O~ve~r~al~I________________________4_9~6_______________0.53~6~_________________~0~.1~6~4_____ . Annual Crops I 2 56 0.911 0.228 3 209 0.724 0.259 4 115 0.354 0.243 5 117 0.003 0.098 Overall 497 0.488 0.224 COCOllut I 40 0.948 0.104 2 79 0~09 0212 3 221 0756 0.280 4 114 0.304 0.137 5 48 0.021 0.107 Overall 502 0.622 0.219 CONCLUSION I. The use of fuzzy approach in land suitability assessment provides more flexibility to identify the suitable area for certain crop, depending on the suitability index value preferred by the user defined as suitable. The method developed shows the significance of the fuzzy approach for refining available land suitability evaluation sys­ tems. Land suitability map for rice, upland an­ nual crops and coconut derived from Fuzzy method shows that suitable area for rice with suitability index 0.5 - 1 is about 57 percent of the study area. Suitable area for upland annual crops covers about 56 percent. The suitable areas for the two land use types are especially found in level to gently slope. Suitable area for coconut covers about 68 percent of the study area. The dominant lim iting factors are slope steepness, erosion hazard and soil pH. 2. The study confirms the capability of remote sensing and GIS to integrate spatial and attribute data and offers a quick and reliable method of natural resources appraisal. The spatial relation­ ship between different geograph ically referenced data can be established by using GIS. In the study, RS has been used to derive land use map and GIS has been used for digitization of base map, digitization and delineation of land re­ source boundary and also for generation of soil erosion and land suitability map. The result pre­ sented shows the potentialities and constraints of the area with regard to its land resources and will be a useful tool for any planning in the study area. REFERENCES (J J FAO. (! 976). A Framework for ,Land Evalua­ tion. Sods Bulletin No. 32, FAO: Rome. (2J Rossiter, D.G ., 1996. A theoretical framework for land evaluation. Geoderma, 72: 165-190. [3] Dent, D. and A. Young. 1981. Soil Survey and Land Evaluation. George Allen & Unwin: Bos­ ~n . . [4] Burrough, P A, 1986. Principles ofgeographi­ cal information systems for land resources as­ sessment. ivlonograohs on soil and resources survey no 12. Oxj~rd University Press Inc., New York. 194 p. [5] Burrough, P.A., P. van Gaans, and R..Hoots­ mans. 1997. Continuous classification in soil survey: Spatial correlation, confusion, and boundaries. Geoderma 77: IJ5 -- 135. [6] Zhu, A. X., B. Hudson, J. Burt, K. Lubich, and D. Simonson. 2001. Soil mapping using GIS, expert knowledge, and fuzzy 'logic. Soil Sci. Soc. Am. J. 65:1463 - 1472 [7J FAO. (1985) Guidelines: Land Evaluation for Irrigated Agriculture. Soi I Bu lIetin No.55, FAO: Rome. [8] Burrough, PA (1989) "Fuzzy mathematical methods for soil survey and land evaluation". Journal of Soil Science, 40:477-492. [9] McBratney, A.B ., and 1.0A ODEH. 1997. Ap­ plication of fuzzy sets in soil science: fuzzy logic, fuzzy measurements and fuzzy decisions. Geoderma, 77:85-! 13 (IOJ Burrough, P.A., R.A. Macmillan, and W. van DeUl·sen. 1992. Fuzzy classification methods for determining land suitnbility from soil profile observation and topography. Journal of Soil Sci­ ence. 43: 93-21 O. 5

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