School of Remote Sensing Suranaree University of Technology Nakhon Ratchasima, 30000 Thailand

1. 12th International Conference on Digital Information ManagementKyushu University, Fukuoka, Japan12-14 September 2017 Arif Wicaksono, SunyaSarapirome* Emails : *a.bijaksono@gmail.com, *sunyas@g.sut.ac.th Urban park area feasibility analysis using fuzzy aggregation of multi-spatial criteria and multi-expert weights School of Remote Sensing SuranareeUniversity of Technology Nakhon Ratchasima, 30000 Thailand

2. Presentation Outline • Introduction • Research Objectives • Study area • Research framework • Criteria preparation • Criteria aggregation • Method : Spatial fuzzy DEMATEL • Method : Experts’ Importance Weighting • Method : Weighted Linear Combination (WLC) • Results and comparison • Discussion and conclusion

3. 1. Introduction • As the world enters 21st centuries, there is growing concern to provide more green open space for human kind (Mela, 2014). • GUOS as one of urban infrastructure provides service for citizens like oxygen, social place to interact and clean air (Laing, Miller, Davies, and Scott, 2006). • GriyaKatulampa urban park , East Bogor sub-district (Source: private collection)

4. 1. Introduction Suitable urban park location approach based on geographical analysis

5. 1. Introduction In Indonesia, public urban park is urban park of which its procurement and maintenance becomes the responsibility of Municipality or Regency Government Nowadays, as every municipality and regency in Indonesia has to preserve 20 % of its area to be public urban park, in some municipalities this could be a problem since sufficient land for this need has to compete with the requirement of other urban facilities. Therefore, selecting appropriate technique for urban park location is ultimate challenge, particularly in sense how efficient this method can deliver suitable urban park areas and locations to meet the requirement of criteria and agree with existing land use. • WarungJambu Market near Ciliwung River (Source: private collection)

6. 1. Introduction

7. 2. Research objectives 2.1 To implement fuzzy DEMATEL on GIS raster-based criteria and incorporate with existing land use to acquire feasible areas and locations for urban park. 2.2 To compare feasible park areas and locations resulted from employing weights of different groups of experts and their combinations.

8. 3. Study area Population:1,407,922 (2015)

9. 4. Research framework Input Criteria: • urban park policy demand (C1) • accessibility (C2) • population density (C3) • distance to school (C4) • distance to water (C5) • distance to electric power line (C6).

10. 5. Criteria preparation : urban park policy demand and population density The population of that year can be predicted from population data in 2015 using equation, operating on every village. where Gnis population of year 2031, Go is the initial population, N is natural population growth rate of the city, M is the influx of people from outside, and n is the planning period of the year. • Urban park policy demand can be computed by: y = 0.2x1 - (x2+x3) • where y is urban park policy demand (km2), x1 is village area (km2), x2 is urban park area for every village in the master plan (km2), and x3 is actual park area in each village (km2).

11. 5. Criteria preparation: fuzzy membership function for distant related riteria Decreasing sigmoidal Increasing sigmoidal

12. 5. Criteria preparation

13. 5. Criteria preparation

14. 6. Criteria aggregation: Spatial fuzzy DEMATEL 6 7 1 5 8 2 4 9 3

15. 6. Criteria aggregation: Experts’ Importance Weighting For every expert group, final importance weight can be obtained by using Equation: Normalized experts’ importance weight can be derived from Equation:

16. 6. Criteria aggregation: Weighted linear combination • In this article, weighted linear combination WLC is used to aggregate : • Fuzzy DEMATEL weights with six GIS layers; • Experts’ importance weights with maps generated from three different expert groups (academics, government, professionals). • Equation used for WLC: • V(Ai)= the overall value of the i-th alternative; • Wk= weight of k-th criteria; • v(aik)= the value of the i-thalternative with respect to the k-thattribute measured by means of the value function; • Source: Malczewski & Rinner (2015)

17. 7. Results : criterion weights from fuzzy dematel and experts’ importance weights

18. 7. Results : Urban park feasibility map based on fuzzy DEMATEL Professional group of experts Academics group of experts Government group of experts

19. 7. Results : Urban park feasibility map based on fuzzy DEMATEL By combining group of experts, new locations of urban park can be discovered instead of using combined all weights Combined all weights Combined group of experts

20. 7. Results : Comparison matrix of similarity and mismatch areas resulting from employing different sets of weights Similarity ratio = intersecting cells ÷ union cells • A = Combined all weights, B = Combined group of experts, C = academics group of experts, D = professional group of experts, E = government group of experts

21. 7. Results : Causal and Effect Relationship Diagrams • (A) academics, • (B) government, • (C) professional, • (D) combined all weights

22. 8. Discussions • Considering provided areas from only high and very high suitable classes, combined group weights provides the biggest feasible areas of 19.26 sq km, while combined all weight offers smallest areas.

23. 8. Discussions • Surprisingly, the result of feasibility analysis using combined group weights offers 19.26 sq km of high and very high suitable classes for new park area, which is 16.25 % of Bogor Municipality area. • According to Bogor Municipality master plan 2031 only around 4.5 % of the municipality area is planned to be additional urban park area. This result gives more chance to decision maker to develop public urban park more legitimately. • In term of area extent, the result shows that about 93 % of villages can comply with the regulation if 5 % of administrative area is suggested to be park area. • Experts in government and professional really care about “where should or should not be developed”. • Experts in academics group might think ideally to develop urban park based on “where it should be needed most” that is referred to school location.

24. 8. Conclusions • It can be concluded that feasible areas and locations from different sets of weights and groups of experts are not much different; • It can be interpreted that opinions from all expert groups and their combinations with respect to criteria weights and weights among them were expressed in the same direction and agreement, or almost no conflict in other word; • In terms of feasible location, it can be observed that the most similar results are from combined all weights and government group of experts. The most dissimilar results are from combined all weights and combined group of experts; • For further study, some additional qualification elements of expert such as familiarity to the project area and specific professional training program could be recommended [Li et al,2015].

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