Evaluating GIS-DM procedures
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The document examines GIS decision-making procedures in addressing land use challenges in Bandung, Java, focusing on two case studies: locating a sanitary landfill and land use allocation. It emphasizes the sensitivity of decision outcomes to the criteria weights and the necessity for public participation to enhance decision quality. The findings highlight the conflict between economic growth needs and environmental considerations due to increasing population density.
Evaluating GIS-DM procedures
- 1. Evaluating GIS Decision Making Procedures Case Study : Land Use Problems in The Bandung Area, Java : Agung Wahyudi : Prof Marc Van Meirvenne : ir. Liesbet Cockx by promoter co-promoter INTERUNIVERSITY PROGRAMME IN PHYSICAL LAND RESOURCES
- 2. Introduction Decision Making (DM) process of evaluating choices among alternatives Spatial decision making deals with location problems Conventional approach only based on experience and audacious feeling GIS solving spatial problems Current GIS still has limitation; lack of preferences from decision makers GIS in support with decision tools improvement AIM to evaluate GIS-DM procedures Two case studies in spatial decision problems Single Objective Multiple Criteria : To find suitable location for sanitary landfill Multiple Objectives Multiple Criteria : Land use allocation for agricultural, industrial and residential areas
- 3. Study Area Location: Java island, West Java Province Area : 127,830 ha (8 times Ghent’s area) Population : 1,436,777 in 2005 (6 times Ghent’s pop) Labor proportion: industrial sector (27, 21%) agricultural sector (26,48%) Population density : 1,007 /km 2 Population growth rate : 2.89% Saguling Lake Leuwigajah Sanitary Landfill 24 ha
- 4. Single Objective Multiple Criteria | Sanitary Landfill Methane explosion in 2005 Leuwigajah sanitary landfill was closed New site need to be allocated It needs requirements from regulations Not-In-My-Backyard (NIMBY) syndrome generate opposition Single Objective Multiple Criteria Single Objective Multiple Criteria before after 1 km 1/3 km
- 5. Single Objective Multiple Criteria | Sanitary Landfill Analytic Hierarchy Process (AHP) by Saaty (1990) Deriving the weight important issue Difficult to quantify and weigh Pairwise comparison matrix appropriate methods Step I sum of the values in each column Step II divide each element by its column sum Step III compute the average 1/9 1/7 1/5 1/3 1 3 5 7 9 Criteria 2 Criteria 1 extremely equal moderate strong very strong Scale of Importance’s Intensity in Analytic Hierarchy Process Deriving Criterion Weight
- 6. Single Objective Multiple Criteria | Sanitary Landfill Pairwise Comparison Matrix from Analytic Hierarchy Process (AHP) 1. Equal compromise scenario equal preference basic scenario rain intensity = soil type = geology = recharge = slope = road = center of waste = land use = built up Four different priorities were introduced to accommodate the different perceptions 2. Government low cost for constructing and daily operation land use > built up > center of waste > road > recharge area = slope = soil type = geology = rain intensity 3. Citizen Not-In-My-Backyard ( NIMBY) syndrome built up > recharge area > land use > soil type = rain intensity = geology = slope = center of waste = road 4. Environment minimize the impact conserve the soil soil type > geology > slope > rain intensity > recharge area > center of waste = land use = built up = road
- 7. Single Objective Multiple Criteria | Sanitary Landfill Results of suitable location for sanitary landfill Equal Priority Government Priority Citizen Priority Environment Priority more suitable less suitable “ the results were sensitive to a change in criterion weight”
- 8. Multiple Objective Multiple Criteria | Land Use Allocation Multiple Objectives Multiple Criteria Industries are needed to boost economic growth Agriculture is threatened by industries Population growth rate 2.89% It demands new land for housing Residential took 2.4% of total area in 1983 and 8.2% in 2003 “ Trade-offs must be made to ensure proper land use allocation” landscape residential agricultural industrial Multiple Objective Multiple Criteria
- 9. Multiple Objective Multiple Criteria | Land Use Allocation Pairwise Comparison Matrix from Analytic Hierarchy Process (AHP) Objective 2 Industry textile water for washing location road > water > power lines > slope > land use Objective 3 Residential amenities close to facilities proximity to the city center > road > power lines = water = land use = slope Objective1 Agriculture fertile soil & availability of water paddy rice water availability > soil type > percentage of slope > land use classes
- 10. Multiple Objective Multiple Criteria | Land Use Allocation “ there are areas where more than one objective is suitable” Multi Objective Land Allocation (MOLA) Module from IDRISI To solve conflicting areas Suitability map for Agricultural areas Suitability map for Industrial areas Suitability map for Residential areas less suitable more suitable rank images minimum area requirement objective weights
- 11. Multiple Objective Multiple Criteria | Land Use Allocation Shortage of agricultural areas 33,326 ha or only 66% completed APPROACH 1: Varying the growth rate while keeping objective weight equal Population growth of 5% should be avoided to ensure sufficient land
- 12. Multiple Objective Multiple Criteria | Land Use Allocation APPROACH 2: Varying the objective weight while constant growth rate of 3% NO significant change
- 13. Conclusions Single Objective Multiple Criteria: locating a sanitary landfill is very sensitive to the weights Multiple Objective Multiple Criteria: A population growth of 5% will lead to land use problems, Population growth should be controlled Varying the objective weights did not significantly change the land allocation General GIS-DM procedures was able to quantify the preference of the decision makers But: Improvement could be made by participation from the public opinion The quality depends on the quality of the input data layers
- 14. Closing Thank you For your attention
Editor's Notes
- #3: The best way to evaluate the procedures is by using them to solve spatial decision problems. There are two cases which will solved by the procedures, single objective, and multiple objectives ; it is an attempt to know not only the objectives but also where the location of the objective is
- #4: The best way to evaluate the procedures is by using them to solve spatial decision problems. There are two cases which will solved by the procedures, single objective, and multiple objectives ; it is an attempt to know not only the objectives but also where the location of the objective is
- #5: The objectives complies with single objective, while it needs various multiple criteria to pursue the objective
- #6: The weight is sensitive to preference. In this step, DM is pushed to gives their preference, to quantify their preference, the pair wise comparison matrix was used. We also introduce four different priorities representing different decision makers.
- #7: The weight is sensitive to preference. In this step, DM is pushed to gives their preference, to quantify their preference, the pair wise comparison matrix was used. We also introduce four different priorities representing different decision makers.
- #8: Give the idea that changing the criteria weight gave impact on the result
- #9: Intro to multiple criteria.