Urban growth modelling in Jakarta Metropolitan area: the research proposal
•Transferir como PPTX, PDF•
2 gostaram•1,121 visualizações
Research proposal for urban growth modelling in Jakarta Metropolitan Area, Indonesia.
Recomendados
Recomendados
Mais conteúdo relacionado
Destaque
Destaque (20)
Semelhante a Urban growth modelling in Jakarta Metropolitan area: the research proposal
Semelhante a Urban growth modelling in Jakarta Metropolitan area: the research proposal (20)
Último
Último (20)
Urban growth modelling in Jakarta Metropolitan area: the research proposal
- 1. Case study: Jakarta Metropolitan Area, Indonesia URBAN GROWTH MODELING IN A DEVELOPING COUNTRY AGUNG WAHYUDI S 42817150 Supervisor: Dr. YAN LIU
- 2. OUTLINE • Introduction • Methodologies • Management Agung Wahyudi S42817150 IntroductionMethodologiesManagement
- 4. BACKGROUND • Urban area covers 5% of overall land in the world1. • In 2030, it is expected 80% world population lives in urban areas2. • Occurs largely in developing countries in Asia. • Jakarta, Indonesia, is experiencing rapid urban growth. Agung Wahyudi S42817150 IntroductionMethodologiesManagement Jakarta, 70’s Jakarta, 90’s
- 5. STUDY AREA Agung Wahyudi S42817150 • Covers 7500 km2 • Population: 28 million people (~10% of Indonesian) • Comprises of 3 provincial governments • Jakarta (the capital of Indonesia) as the economic core • Uncertain future of urban growth Landsat,USGS1994.Truecolour IntroductionMethodologiesManagement
- 6. Agung Wahyudi S42817150 Wallpapersfor.me RESEARCH GAP Urban systems Proximity to facilities HUMAN Developed countries Developing countries Geomorphology e.g. slope Transportation system IntroductionMethodologiesManagement
- 7. AIM AND OBJECTIVES (1) Agung Wahyudi S42817150 • AIM: To develop an urban growth model by taking into accounts human behaviour factors, emphasizing their interactions with other actors, and the spatial pattern of urban growth towards aiding policy makers in regulating the growth of urban areas using Jakarta Metropolitan Area (JMA) as case study. IntroductionMethodologiesManagement
- 8. AIM AND OBJECTIVES (2) Agung Wahyudi S42817150 • OBJECTIVES: 1. To review and evaluate the selection of urban growth factors in cellular automata (CA) urban models. 2. To identify the spatio-temporal pattern of urban growths in JMA using Landsat imaging 3. To develop a prototype of ABM featuring three agents in a separated model 4. To evaluate the impact of policies on the urban spatial pattern by simulating three policy scenarios in three types of interrelated agent’s behaviours 5. To disseminate the results of urban ABM to improve the effectiveness of urban decision-making towards a well- coordinated management among municipalities in JMA IntroductionMethodologiesManagement
- 11. OBJECTIVE 1: Agung Wahyudi S42817150 • Select articles from web of knowledge • Extract and record the factors in CA urban models • Analyse the time (year) and geographic location IntroductionMethodologiesManagement To review and evaluate the selection of urban growth factors in cellular automata (CA) urban models. 1st STAGE Search on “Cellular automata AND urban*” from Web of Knowledge (n=470) 2nd STAGE Check relevance of study – title & abstract (n=165) 3rd STAGE Manual assessment, check introduction and conclusion (n=107)
- 12. OBJECTIVE 1: Agung Wahyudi S42817150 • Suggest key factors influencing urban growth for Objective 3 • Conference paper in CUPUM, The Netherlands, July 2013 IntroductionMethodologiesManagement To review and evaluate the selection of urban growth factors in cellular automata (CA) urban models.
- 14. OBJECTIVE 2: Agung Wahyudi S42817150 • Where the changes happen? • How fast the changes occur? • What are the main driving factors? • Spatial characteristics of the changes? IntroductionMethodologiesManagement To identify the spatio-temporal pattern of urban growths in JMA using Landsat imaging Jakarta, 70’s Jakarta, 80’s Jakarta, 90’s
- 15. OBJECTIVE 2: Agung Wahyudi S42817150 IntroductionMethodologiesManagement To identify the spatio-temporal pattern of urban growths in JMA using Landsat imaging Landsat Year Resol L1-2 L4 L5 L8 1978 1989 1994 2013 60x60 30x30 30x30 30x30 Pre-analysis Geometric correction Atmospheric calibration Supervised classification NDVI NDBI Band 5 and Band 3 Validation Visual calibration on GCPs Confusion matrix Secondary data Administrative boundary Land use map 2005 Google earth Previous reports on JMA Descriptive analysis Histogram Land use proportion Percentageof changes Spatial analysis Urban cross-section maps Variogram on selected angle
- 16. OBJECTIVE 2: Agung Wahyudi S42817150 IntroductionMethodologiesManagement To identify the spatio-temporal pattern of urban growths in JMA using Landsat imaging Landsat Year Resol L1-2 L4 L5 L8 1978 1989 1994 2013 60x60 30x30 30x30 30x30 Pre-analysis Geometric correction Atmospheric calibration Supervised classification NDVI NDBI Band 5 and Band 3 Validation Visual calibration on GCPs Confusion matrix Secondary data Administrative boundary Land use map 2005 Google earth Previous reports on JMA Descriptive analysis Histogram Land use proportion Percentageof changes Spatial analysis Urban cross-section maps Variogram on selected angle
- 17. OBJECTIVE 2: Agung Wahyudi S42817150 IntroductionMethodologiesManagement To identify the spatio-temporal pattern of urban growths in JMA using Landsat imaging NDVI = NIR−red NIR+red NDBI = Bu − NDVI Bu = NIR−MidIR NIR+MidIR NDVI + - NDBI - Forest Water + Grass Urban TASK 2.A SUPERVISED CLASSIFICATION Source: Jensen (2007)3
- 18. OBJECTIVE 2: Agung Wahyudi S42817150 IntroductionMethodologiesManagement To identify the spatio-temporal pattern of urban growths in JMA using Landsat imaging 2)( 1 )()( )(2 1 )( hN i ii huzuz hN h Semi-variogram(γ) Distance (h) sill Nugget fx range z(ui) z(ui+h) TASK 2.D SPATIAL ANALYSIS
- 20. OBJECTIVE 3: Agung Wahyudi S42817150 IntroductionMethodologiesManagement To develop a prototype of ABM featuring three agents in a separated model • Develop a robust ABM • Which agent? • How to define the agents? • How to represent agents’ behavior into the model?
- 21. OBJECTIVE 3: Agung Wahyudi S42817150 Primary data Expert: academician Practitioner: developer Government: Min.Pub.Work Secondary data Previous JMA reports Urban growth casestudies in JMA and developing countries Cellular Automata (CA) Agents Agents A-A interactionA-E interaction Translate to ABM script verification Conceptual framework feedback Static data layer The environment, represents the space where agents are roaming spatially Dynamic data layer The agent, represents the actors that involve in developing the lands Module 1: The environment Module 2: The Agents Module 3: The A-E interaction IntroductionMethodologiesManagement To develop a prototype of ABM featuring three agents in a separated model
- 22. OBJECTIVE 3: Agung Wahyudi S42817150 Primary data Expert: academician Practitioner: developer Government: Min.Pub.Work Secondary data Previous JMA reports Urban growth casestudies in JMA and developing countries Cellular Automata (CA) Agents Agents A-A interactionA-E interaction Translate to ABM script verification Conceptual framework feedback Static data layer The environment, represents the space where agents are roaming spatially Dynamic data layer The agent, represents the actors that involve in developing the lands Module 1: The environment Module 2: The Agents Module 3: The A-E interaction IntroductionMethodologiesManagement To develop a prototype of ABM featuring three agents in a separated model
- 23. Agung Wahyudi S42817150 IntroductionMethodologiesManagement OBJECTIVE 3: To develop a prototype of ABM featuring three agents in a separated model TASK 3.A DEFINE THE AGENTS Agent Who Which Behaviour Sources Data acquisition Method Developers • Occupy >500 ha land in JMA • Searching land • Price negotiation • House credit impact • Real Estate Indonesia • School of Property • Bandung Inst of Tech • Semi-open interview Residents • Middle-income • 25-40 years of age • Location preferences • Price negotiation • Which developers • Thesis on resident behaviours • Indonesia resident association • Literature review • Triangulation with expert interview Government • Each municipalities in JMA • Indonesia Ministry of Public work, section JMA (DPU ID) • Urban policies • Land allocation in master plan • Master plans of each municipalities • Planning agencies in each municipalities • Experts from DPU ID • Semi-open interview
- 24. Agung Wahyudi S42817150 IntroductionMethodologiesManagement OBJECTIVE 3: To develop a prototype of ABM featuring three agents in a separated model TASK 3.B CONCEPTUAL FRAMEWORK Housing Searching Found land developers Permission granted? National Land Agency yes BUY No Develop Idle Land owner expelled negotiate High income Med income Low house (CSR) Spatial pattern Econm instinct Very high, fast High, fast slow Increasing LandValue Source: Adopted from Firman (2004a)4
- 26. OBJECTIVE 4: Agung Wahyudi S42817150 IntroductionMethodologiesManagement To evaluate the impact of policies on the urban spatial pattern by simulating three policy scenarios in three types of interrelated agent’s behaviours • What-if scenario • To simulate the impact of urban policy on the urban spatial pattern • Foreseen the likely future development of an area
- 27. OBJECTIVE 4: Agung Wahyudi S42817150 NO Interaction No protection on the threatened agriculture lands. Permission on new lands will begiven as much as for industrial, commercial zones, and large housing. Economic acceleration Predicting urban growth using trend from the previous urban land changes (Ch.2). No change on urban regulations. Set as benchmark scenario Business as usual Conservation on existing parks, agricultureareas, and forests. Keep impact on environment as minimum as possible Sustainable env Scenario 1A Scenario 1B Scenario 1C Scenario 2A Scenario 2B Scenario 2C Scenario 3A Scenario 3B Scenario 3C STATIC layer DYNAMIClayer 1 2 3 A CompetitionB CollaborationC IntroductionMethodologiesManagement To evaluate the impact of policies on the urban spatial pattern by simulating three policy scenarios in three types of interrelated agent’s behaviours
- 28. OBJECTIVE 4: Agung Wahyudi S42817150 IntroductionMethodologiesManagement To evaluate the impact of policies on the urban spatial pattern by simulating three policy scenarios in three types of interrelated agent’s behaviours Scenario Scenario ## Scenario ## Scenario ## Map Quantitative analysis Spatial pattern TASK 4.D SIMULATE THE SCENARIOS
- 30. OBJECTIVE 5: Agung Wahyudi S42817150 • What-if-then ? So what? • Gap in urban modelling5 IntroductionMethodologiesManagement To disseminate the results of urban ABM to improve the effectiveness of urban decision-making towards a well-coordinated management among municipalities in JMA
- 31. OBJECTIVE 5: Agung Wahyudi S42817150 • Develop interactive medias: • Simulation results in video format and, • Web-based urban model, e.g. LAND YOUs • Propose a guideline for urban policies • Disseminate the findings IntroductionMethodologiesManagement To disseminate the results of urban ABM to improve the effectiveness of urban decision-making towards a well-coordinated management among municipalities in JMA
- 33. Agung Wahyudi S42817150 Key activities 1st year 2nd year 3rd year Oct Dec Feb Apr Jun Aug Oct Dec Feb Apr Jun Aug Oct Dec Feb Apr Jun Aug 2012 2013 2014 2015 1 Objective 1 1.a To select and filter articles X 1.b To analyse geographic & timeframe X 1.c To summarize the findings X S 2 Objective 2 2.a To select and download the images X X 2.b To classify land cover changes X X 2.c To validate the results X 2.d To quantify spatio-temporal changes X 2.e To explore the spatial pattern X X S 3 Objective 3 3.a FIELDWORK X X 3.b To define the agent & behaviour X 3.c Construct conceptual framework X 3.d Develop a prototype of ABM X X 3.e To verify the model X 3.f To simulate three agents X S 4 Objective 4 4.a To define interrelated behaviour X 4.b To develop computer model X X X 4.c To run model & analyse the results X X 4.d To simulate scenario X X X S 5 Objective 5 5.a To build an interactive media X X X 5.b To propose guideline X 5.c To disseminate the findings X M PhD Milestones M.1 Confirmation X M.2 Mid-candidature review X M.3 Thesis review X M.4 Conferences X IntroductionMethodologiesManagement
- 34. FUNDING SOURCES Agung Wahyudi S42817150 No Item GPEM-UQ UQ-ID GSITA Data acquisition 1. Flight ticket return to Indonesia 1500 2. Administration fees for Indonesia statistical data 200 3. Administration fees for spatial data (road network map etc) 200 4. Local transportation 200 5. Duplication of reports and master plans (DVD) 100 6. Hard drive for data storage and back-up 100 International Conference (either in Australia or Asia) 7 . Registration fees 300 8. Return flight tickets 2000 9. Accommodations and foods 600 International conference (other parts of the world) 10. Registration fees 400 11. Return flight tickets 700 12. Accommodations and foods 300 Thesis publication 13. Proofreading 400 14. Printing 200 Total cost 7300 Optional expenditures 15. Dissemination in Indonesia 3000 16. Skill training Repast Java programming 3000 IntroductionMethodologiesManagement
- 35. EXPECTED RESULTS • Three international peer-reviewed articles: • Submission of “Land covers of JMA, urban growths, and its spatial patterns” to International Journal of Remote Sensing Obj.2 • Submission of “A prototype of ABM for single agent” to Journal of computer urban modelling OR Int Journal of GI Science Obj.3 • Submission of “Urban modelling with multi-scenario and different types of interaction in JMA” to Journal of computer urban modelling OR Int Journal of GI Science Obj.4 • Interactive medias: movie, and web-based urban simulation models Obj.5 • Articles in the newspapers in Indonesia • PhD thesis Agung Wahyudi S42817150 IntroductionMethodologiesManagement
- 36. EXPECTED LIMITATIONS • Data and metadata are lacking ; accessibility, availability, and reliability. • Basic experience in Java for writing the programming code. • Urban model over-fits the reality. • From modelling to reality: practical gap. Agung Wahyudi S42817150 IntroductionMethodologiesManagement
- 37. References 1. Taubenböck, H., Esch, T., Felbier, A., Wiesner, M., Roth, A., Dech, S., 2012, Monitoring urbanization in mega cities from space, Remote Sensing of Environment 117(0):162-176 2. Nations, U., 2004, World population to 2300, New York: United Nations. 3. Jensen, J. R., 2007, Remote sensing of the environment. an earth resource perspective, Prentice Hall series in geographic information science. 4. Firman, T., 2004a, Major issues in Indonesia's urban land development, Land Use Policy 21(4):347-355 5. Ersahin, V. K., 2008, Toward integration of Bayesian Networks with geographic information systems and complex systems theory for urban land use change modelling, Simon Fraser University (Canada), Canada, pp. 293 THANK YOU
Notas do Editor
- In my presentation, there are three sections, The introduction, explain Methodologies , explain Management explain
- 1,23 billion population in 2030 (Seto, UN)
- 1,23 billion population in 2030 (Seto, UN)
- The largest in Indonesia, in terms of population and areas Issue on collaboration municipalities 9 municipalities
- Urban as system , it consists of various think that interlinked and work together so that we can see (for example from remote sensing images) that urban is indeed growth just like single cells in organism. Or shrink..,,,, It is also influenced by another systems for example transportation system, economy systems, institutional systems, socials. So urban system work in a way like a complex system. Most of the research consider the urban system on its physical features, for example researcher urban areas have certain distance to road, or proximity to cbd, or current neighbourhood. But they forget (either force to forget) that it is the human (us) that shape the urban. It is the individual behaviour that shape the behaviour of urban system foe example: if the people in city prefer to walk than riding car, what will be the shape of city?? Bbc http://www.bbc.com/future/story/20131018-walk-to-work-transform-your-city To stress again the theoretical gap, while most of the research in urban modelling concentrates in mirroring the spatial arrangement of urban areas, (they use mathematical equation more like regression analysis to treat their urban cases, they consider homogeneous behaviour and trend ) less attention has been paid to the process underlying the dynamic of the urban itself, where the growth of urban is affected by human preferences do make different, where people with different interest background (socially, economically) will prefer different residential areas, where big developers develop dozens hectare at once, and so on. They situation is just too complex to be modelled in single mathematical equation. Thus we need different approach to model the complex or urban systems. In particular in developing countries where the majority of expected population will life here, and where less attention has been given to these countries Complex system
- What does it means? What human behaviors? Why spatial patterns matters? Because the growths are not random.
- Animated, one obj each click, and haze out after.
- I proposed the methods with the three stages, the description, developing methodology, and problem solving Well, I will explain it further each objective in my next slide, but the points that I want to stress here are Every objective is in accordance with the stages, so the first objective is actually where I will gather the required data and basic analysis on the study areas. These data then use as an important input for the second stage to propose a conceptual framework. The keyword in this stage is “to understand” the mechanism of urban land use changes. This conceptual framework then work as an foundation for building a model (an agent based model). We will then test the model, against the conceptual framework, to ensure if the model work as what we propose in the conceptual framework After the model is set, it will be used to help solving a problem (as a model) it wont be a silver bullet model where it can solve everything, the suitable problem to be solved using the proposed model is the issue with deep uncertainty and too complex to be solved using math equation for example the if the government decided to give authorization to open new urban land use in certain areas, what will happen? In terms of the overall growth of other land uses The forth objective is optional, we will see what can we reach in this stages, and use the model to solve another urban problem cases.
- I proposed the methods with the three stages, the description, developing methodology, and problem solving Well, I will explain it further each objective in my next slide, but the points that I want to stress here are Every objective is in accordance with the stages, so the first objective is actually where I will gather the required data and basic analysis on the study areas. These data then use as an important input for the second stage to propose a conceptual framework. The keyword in this stage is “to understand” the mechanism of urban land use changes. This conceptual framework then work as an foundation for building a model (an agent based model). We will then test the model, against the conceptual framework, to ensure if the model work as what we propose in the conceptual framework After the model is set, it will be used to help solving a problem (as a model) it wont be a silver bullet model where it can solve everything, the suitable problem to be solved using the proposed model is the issue with deep uncertainty and too complex to be solved using math equation for example the if the government decided to give authorization to open new urban land use in certain areas, what will happen? In terms of the overall growth of other land uses The forth objective is optional, we will see what can we reach in this stages, and use the model to solve another urban problem cases.
- I proposed the methods with the three stages, the description, developing methodology, and problem solving Well, I will explain it further each objective in my next slide, but the points that I want to stress here are Every objective is in accordance with the stages, so the first objective is actually where I will gather the required data and basic analysis on the study areas. These data then use as an important input for the second stage to propose a conceptual framework. The keyword in this stage is “to understand” the mechanism of urban land use changes. This conceptual framework then work as an foundation for building a model (an agent based model). We will then test the model, against the conceptual framework, to ensure if the model work as what we propose in the conceptual framework After the model is set, it will be used to help solving a problem (as a model) it wont be a silver bullet model where it can solve everything, the suitable problem to be solved using the proposed model is the issue with deep uncertainty and too complex to be solved using math equation for example the if the government decided to give authorization to open new urban land use in certain areas, what will happen? In terms of the overall growth of other land uses The forth objective is optional, we will see what can we reach in this stages, and use the model to solve another urban problem cases.
- Briefly in the first stage the METHODs Is the routine procedure in interpretation of RS images , so for example here, we have three images, supervised classification to translate the spectrum in the images into land categories residential, industrial, non-built up areas. After we obtain the land use from different years, we could then compare areas in different year to see where are the changes, what is the pace, what is the magnitude (in term of size and extent), the overall direction of change (north, south??, along the road),. At this stage we don’t have the primary data thus the analysis relied upon secondary data, literature, reports.
- Briefly in the first stage the METHODs Is the routine procedure in interpretation of RS images , so for example here, we have three images, supervised classification to translate the spectrum in the images into land categories residential, industrial, non-built up areas. After we obtain the land use from different years, we could then compare areas in different year to see where are the changes, what is the pace, what is the magnitude (in term of size and extent), the overall direction of change (north, south??, along the road),. At this stage we don’t have the primary data thus the analysis relied upon secondary data, literature, reports.
- I proposed the methods with the three stages, the description, developing methodology, and problem solving Well, I will explain it further each objective in my next slide, but the points that I want to stress here are Every objective is in accordance with the stages, so the first objective is actually where I will gather the required data and basic analysis on the study areas. These data then use as an important input for the second stage to propose a conceptual framework. The keyword in this stage is “to understand” the mechanism of urban land use changes. This conceptual framework then work as an foundation for building a model (an agent based model). We will then test the model, against the conceptual framework, to ensure if the model work as what we propose in the conceptual framework After the model is set, it will be used to help solving a problem (as a model) it wont be a silver bullet model where it can solve everything, the suitable problem to be solved using the proposed model is the issue with deep uncertainty and too complex to be solved using math equation for example the if the government decided to give authorization to open new urban land use in certain areas, what will happen? In terms of the overall growth of other land uses The forth objective is optional, we will see what can we reach in this stages, and use the model to solve another urban problem cases.
- In the second stages, it is assumed that we have partial understanding on the urban system, that is the “spatial pattern” of urban dynamic. But absent on the understanding of the “process”. Thus, in the second stage, we propose the field work, it is expected that using the first data from the first stage, we could target expert to build our understanding on how process /human/actors influence the urban systems We then propose the conceptual framework, to clarify who are the dominant agents ? Their behaviours, their interaction with others agents, their reaction towards change in the legal pre-setting systems?? We then build a model an agent based model, just briefly agent based modelling is we think the most suitable model for our case because it can represented the human influences, behaviour, and interaction and suitable for complex system like urban dynamic.
- In the second stages, it is assumed that we have partial understanding on the urban system, that is the “spatial pattern” of urban dynamic. But absent on the understanding of the “process”. Thus, in the second stage, we propose the field work, it is expected that using the first data from the first stage, we could target expert to build our understanding on how process /human/actors influence the urban systems We then propose the conceptual framework, to clarify who are the dominant agents ? Their behaviours, their interaction with others agents, their reaction towards change in the legal pre-setting systems?? We then build a model an agent based model, just briefly agent based modelling is we think the most suitable model for our case because it can represented the human influences, behaviour, and interaction and suitable for complex system like urban dynamic.
- In the second stages, it is assumed that we have partial understanding on the urban system, that is the “spatial pattern” of urban dynamic. But absent on the understanding of the “process”. Thus, in the second stage, we propose the field work, it is expected that using the first data from the first stage, we could target expert to build our understanding on how process /human/actors influence the urban systems We then propose the conceptual framework, to clarify who are the dominant agents ? Their behaviours, their interaction with others agents, their reaction towards change in the legal pre-setting systems?? We then build a model an agent based model, just briefly agent based modelling is we think the most suitable model for our case because it can represented the human influences, behaviour, and interaction and suitable for complex system like urban dynamic.
- In the second stages, it is assumed that we have partial understanding on the urban system, that is the “spatial pattern” of urban dynamic. But absent on the understanding of the “process”. Thus, in the second stage, we propose the field work, it is expected that using the first data from the first stage, we could target expert to build our understanding on how process /human/actors influence the urban systems We then propose the conceptual framework, to clarify who are the dominant agents ? Their behaviours, their interaction with others agents, their reaction towards change in the legal pre-setting systems?? We then build a model an agent based model, just briefly agent based modelling is we think the most suitable model for our case because it can represented the human influences, behaviour, and interaction and suitable for complex system like urban dynamic.
- In the second stages, it is assumed that we have partial understanding on the urban system, that is the “spatial pattern” of urban dynamic. But absent on the understanding of the “process”. Thus, in the second stage, we propose the field work, it is expected that using the first data from the first stage, we could target expert to build our understanding on how process /human/actors influence the urban systems We then propose the conceptual framework, to clarify who are the dominant agents ? Their behaviours, their interaction with others agents, their reaction towards change in the legal pre-setting systems?? We then build a model an agent based model, just briefly agent based modelling is we think the most suitable model for our case because it can represented the human influences, behaviour, and interaction and suitable for complex system like urban dynamic.
- I proposed the methods with the three stages, the description, developing methodology, and problem solving Well, I will explain it further each objective in my next slide, but the points that I want to stress here are Every objective is in accordance with the stages, so the first objective is actually where I will gather the required data and basic analysis on the study areas. These data then use as an important input for the second stage to propose a conceptual framework. The keyword in this stage is “to understand” the mechanism of urban land use changes. This conceptual framework then work as an foundation for building a model (an agent based model). We will then test the model, against the conceptual framework, to ensure if the model work as what we propose in the conceptual framework After the model is set, it will be used to help solving a problem (as a model) it wont be a silver bullet model where it can solve everything, the suitable problem to be solved using the proposed model is the issue with deep uncertainty and too complex to be solved using math equation for example the if the government decided to give authorization to open new urban land use in certain areas, what will happen? In terms of the overall growth of other land uses The forth objective is optional, we will see what can we reach in this stages, and use the model to solve another urban problem cases.
- On the third stage, the problem solving, the objective is to bring the model for solving particular problem in urban planning. Most of the research will tempted to start to estimate the future of the urban growth, this might not be wrong but misleading. In particular urban, it is not weather, where in a strict parameter play together and can be estimated. In urban modelling, the parameters could change over time (for example, the decision to install new residential regulation) or for population growth because the national decision to accept in-migration from war conflicts countries. Warning, model is not to estimate the urban , because only the future will unfold the future of a city, but it is to test certain scenario on the urban growth, what-if-scenario. So we could not say , this model performs perfect for estimating urban growth, but rather, IF the government decided to ,,,,, then this will happen. On the forth objective rather than just WHAT-IF scenario, we need also to WHAT-IF-THEN the solution scenarios, too many models already talk about the problems, but few offers the solutions, whilst this is the most important think and waited for decision makers in particular in developing countries.
- On the third stage, the problem solving, the objective is to bring the model for solving particular problem in urban planning. Most of the research will tempted to start to estimate the future of the urban growth, this might not be wrong but misleading. In particular urban, it is not weather, where in a strict parameter play together and can be estimated. In urban modelling, the parameters could change over time (for example, the decision to install new residential regulation) or for population growth because the national decision to accept in-migration from war conflicts countries. Warning, model is not to estimate the urban , because only the future will unfold the future of a city, but it is to test certain scenario on the urban growth, what-if-scenario. So we could not say , this model performs perfect for estimating urban growth, but rather, IF the government decided to ,,,,, then this will happen. On the forth objective rather than just WHAT-IF scenario, we need also to WHAT-IF-THEN the solution scenarios, too many models already talk about the problems, but few offers the solutions, whilst this is the most important think and waited for decision makers in particular in developing countries.
- On the third stage, the problem solving, the objective is to bring the model for solving particular problem in urban planning. Most of the research will tempted to start to estimate the future of the urban growth, this might not be wrong but misleading. In particular urban, it is not weather, where in a strict parameter play together and can be estimated. In urban modelling, the parameters could change over time (for example, the decision to install new residential regulation) or for population growth because the national decision to accept in-migration from war conflicts countries. Warning, model is not to estimate the urban , because only the future will unfold the future of a city, but it is to test certain scenario on the urban growth, what-if-scenario. So we could not say , this model performs perfect for estimating urban growth, but rather, IF the government decided to ,,,,, then this will happen. On the forth objective rather than just WHAT-IF scenario, we need also to WHAT-IF-THEN the solution scenarios, too many models already talk about the problems, but few offers the solutions, whilst this is the most important think and waited for decision makers in particular in developing countries.
- I proposed the methods with the three stages, the description, developing methodology, and problem solving Well, I will explain it further each objective in my next slide, but the points that I want to stress here are Every objective is in accordance with the stages, so the first objective is actually where I will gather the required data and basic analysis on the study areas. These data then use as an important input for the second stage to propose a conceptual framework. The keyword in this stage is “to understand” the mechanism of urban land use changes. This conceptual framework then work as an foundation for building a model (an agent based model). We will then test the model, against the conceptual framework, to ensure if the model work as what we propose in the conceptual framework After the model is set, it will be used to help solving a problem (as a model) it wont be a silver bullet model where it can solve everything, the suitable problem to be solved using the proposed model is the issue with deep uncertainty and too complex to be solved using math equation for example the if the government decided to give authorization to open new urban land use in certain areas, what will happen? In terms of the overall growth of other land uses The forth objective is optional, we will see what can we reach in this stages, and use the model to solve another urban problem cases.
- On the third stage, the problem solving, the objective is to bring the model for solving particular problem in urban planning. Most of the research will tempted to start to estimate the future of the urban growth, this might not be wrong but misleading. In particular urban, it is not weather, where in a strict parameter play together and can be estimated. In urban modelling, the parameters could change over time (for example, the decision to install new residential regulation) or for population growth because the national decision to accept in-migration from war conflicts countries. Warning, model is not to estimate the urban , because only the future will unfold the future of a city, but it is to test certain scenario on the urban growth, what-if-scenario. So we could not say , this model performs perfect for estimating urban growth, but rather, IF the government decided to ,,,,, then this will happen. On the forth objective rather than just WHAT-IF scenario, we need also to WHAT-IF-THEN the solution scenarios, too many models already talk about the problems, but few offers the solutions, whilst this is the most important think and waited for decision makers in particular in developing countries.
- On the third stage, the problem solving, the objective is to bring the model for solving particular problem in urban planning. Most of the research will tempted to start to estimate the future of the urban growth, this might not be wrong but misleading. In particular urban, it is not weather, where in a strict parameter play together and can be estimated. In urban modelling, the parameters could change over time (for example, the decision to install new residential regulation) or for population growth because the national decision to accept in-migration from war conflicts countries. Warning, model is not to estimate the urban , because only the future will unfold the future of a city, but it is to test certain scenario on the urban growth, what-if-scenario. So we could not say , this model performs perfect for estimating urban growth, but rather, IF the government decided to ,,,,, then this will happen. On the forth objective rather than just WHAT-IF scenario, we need also to WHAT-IF-THEN the solution scenarios, too many models already talk about the problems, but few offers the solutions, whilst this is the most important think and waited for decision makers in particular in developing countries.
- On the third stage, the problem solving, the objective is to bring the model for solving particular problem in urban planning. Most of the research will tempted to start to estimate the future of the urban growth, this might not be wrong but misleading. In particular urban, it is not weather, where in a strict parameter play together and can be estimated. In urban modelling, the parameters could change over time (for example, the decision to install new residential regulation) or for population growth because the national decision to accept in-migration from war conflicts countries. Warning, model is not to estimate the urban , because only the future will unfold the future of a city, but it is to test certain scenario on the urban growth, what-if-scenario. So we could not say , this model performs perfect for estimating urban growth, but rather, IF the government decided to ,,,,, then this will happen. On the forth objective rather than just WHAT-IF scenario, we need also to WHAT-IF-THEN the solution scenarios, too many models already talk about the problems, but few offers the solutions, whilst this is the most important think and waited for decision makers in particular in developing countries.
- There are many limitation than the actual limitation I show here, This research is data driven, in that, the stages, the proposing method, the overall output could be adapted depending on the data that we have. This could leads on partial information, understanding, and eventually leads to wrong conceptual framework, So we have to ensure that the reliability of the data source if of highly credential sources Even before reaching the data, we have to make sure that the data is indeed available and accessible. These are common in developing countries, but in Indonesia, I am expecting the required data is on limited accessibility there should be authorization that I have to obtain to reach the data. General critics about modelling in particular the ABM that it works in the low scale areas where it ignores the general /higher level parameters, we acknowledge the limitation of models (we will not claim that this is the best models, but it might explain the dominant process. We will keep “roughly right than precisely wrong” In the ABM models, we construct a model based on the conceptual framework, the limitation of experience that I have is expected to impede the progress of the research, but perhaps by attending (online) training, it is expected we could alleviate the problems Model is model, simplifying the reality is never an easy task. Oversimplyfing or over fitting reality is of major concern for most critics of the models. Thus, we will make the model with as realistic assumption as we have.