SlideShare a Scribd company logo
1 of 17
Cellular automata with non-linear transitio rules for simulating land cover change Katarzyna OSTAPOWICZ [email_address] T he 2009 Annual International Conference of the Royal Geographical Society ,   2 6-28 August 2009 ,  Manchester   Department of GIS, Cartography and Remote Sensing Institute of Geography and Spatial Management Jagiellonian University
Aim  ,[object Object]
Cellular automata: four paradigms ,[object Object],[object Object],[object Object],[object Object],[object Object],Transition rules?
Transition rules: ,[object Object],[object Object],Transition rules?
Artificial neural networks (ANN) ,[object Object],[object Object],x 1 . . x n ∑ f Y w n (x n  w n ) input activation Output w n
Suport vector machines (SVM) ,[object Object],[object Object]
Test area
Land cover: forest/non-forest
Driving forces ,[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Cellular automata model
Workflow Input data Change probabilities Transition rates Natural and antropogenical variable CALIBRATION PART SIMULATION PART ANN/SVM Land cover maps Management plans cross-tabulation Land cover change  simulation
Input data Forest/non-forest: 1987, 2000, 2006 ( source: Landsat images, supervised, hierarchcal approach combining image segmentation, knowledge-based rules and likelihood decision rule ) Elevation and slope  ( source: STRM DEM, spatial resolution 90 m ) Distance to artificial areas  (source: land cover map 2006; distance operation) Migration, NUTS type (urban/rural), distace to urban NUTS  (source: GUS) Ownership: state/private forest  (source: state forest)
Training plots (800, 200 per class) forest aforestation and natural succession non-forest deforestation
Transition rules f(P ij , N i , R ij ) CHANGE PROBABILITIES (P ij )   NEIGHBOURHOOD (N i )   Σ  n i  > 6  (i – land cover type) forest f (elevation, slope, migration, NUTS type,  ownership, distance to artificial areas)  TRANSITION RATES (R ij ) e.g. for forest 0.25% per year TRAINING: forest change between 1987-2000-2006 SCENARIOS: 2006-2056
Maximum accuracy for transsition rules ANN: 75% SVM: 79% 57,06 2050 53,27 2020 55,79 2040 52,16 2010 54,54 2030 50,98 2000 forest cover [%] year forest cover [%] year
CONCLUSSION ,[object Object],[object Object],[object Object]
Thank you :-)

More Related Content

Similar to Cellular automata with non-linear transitio rules for simulating land cover change

seyed armin hashemi
seyed armin hashemiseyed armin hashemi
seyed armin hashemiDheeraj Vasu
 
URBAN AREA PRODUCT SIMULATION FOR THE ENMAP HYPERSPECTRAL SENSOR.ppt
URBAN AREA PRODUCT SIMULATION FOR THE ENMAP HYPERSPECTRAL SENSOR.pptURBAN AREA PRODUCT SIMULATION FOR THE ENMAP HYPERSPECTRAL SENSOR.ppt
URBAN AREA PRODUCT SIMULATION FOR THE ENMAP HYPERSPECTRAL SENSOR.pptgrssieee
 
URBAN AREA PRODUCT SIMULATION FOR THE ENMAP HYPERSPECTRAL SENSOR.ppt
URBAN AREA PRODUCT SIMULATION FOR THE ENMAP HYPERSPECTRAL SENSOR.pptURBAN AREA PRODUCT SIMULATION FOR THE ENMAP HYPERSPECTRAL SENSOR.ppt
URBAN AREA PRODUCT SIMULATION FOR THE ENMAP HYPERSPECTRAL SENSOR.pptgrssieee
 
SIAM-AG21-Topological Persistence Machine of Phase Transition
SIAM-AG21-Topological Persistence Machine of Phase TransitionSIAM-AG21-Topological Persistence Machine of Phase Transition
SIAM-AG21-Topological Persistence Machine of Phase TransitionHa Phuong
 
Regression_Presentation2
Regression_Presentation2Regression_Presentation2
Regression_Presentation2Drake Sprague
 
3_Terrain catergorization for single Pol.ppt
3_Terrain catergorization for single Pol.ppt3_Terrain catergorization for single Pol.ppt
3_Terrain catergorization for single Pol.pptgrssieee
 
Molinier - Feature Selection for Tree Species Identification in Very High res...
Molinier - Feature Selection for Tree Species Identification in Very High res...Molinier - Feature Selection for Tree Species Identification in Very High res...
Molinier - Feature Selection for Tree Species Identification in Very High res...grssieee
 
AT_MB_MM_IGARSS2011.ppt
AT_MB_MM_IGARSS2011.pptAT_MB_MM_IGARSS2011.ppt
AT_MB_MM_IGARSS2011.pptgrssieee
 
MODULE VII_ Remote Sensing_Avantika.pptx
MODULE VII_ Remote Sensing_Avantika.pptxMODULE VII_ Remote Sensing_Avantika.pptx
MODULE VII_ Remote Sensing_Avantika.pptxavantikaadhruj1
 
Using Artificial Neural Networks for Digital Soil Mapping – a comparison of M...
Using Artificial Neural Networks for Digital Soil Mapping – a comparison of M...Using Artificial Neural Networks for Digital Soil Mapping – a comparison of M...
Using Artificial Neural Networks for Digital Soil Mapping – a comparison of M...Ricardo Brasil
 
MODELAÇÃO DO SOLO-PAISAGEM – A IMPORTÂNCIA DA LOCALIZAÇÃO
MODELAÇÃO DO SOLO-PAISAGEM – A IMPORTÂNCIA DA LOCALIZAÇÃOMODELAÇÃO DO SOLO-PAISAGEM – A IMPORTÂNCIA DA LOCALIZAÇÃO
MODELAÇÃO DO SOLO-PAISAGEM – A IMPORTÂNCIA DA LOCALIZAÇÃORicardo Brasil
 
Harmonization of seismic hazard assessment: the SHARE example
Harmonization of seismic hazard assessment: the SHARE exampleHarmonization of seismic hazard assessment: the SHARE example
Harmonization of seismic hazard assessment: the SHARE exampleGlobal Risk Forum GRFDavos
 
Performance Analysis of Adaptive DOA Estimation Algorithms For Mobile Applica...
Performance Analysis of Adaptive DOA Estimation Algorithms For Mobile Applica...Performance Analysis of Adaptive DOA Estimation Algorithms For Mobile Applica...
Performance Analysis of Adaptive DOA Estimation Algorithms For Mobile Applica...IJERA Editor
 
An empirically based path loss model for
An empirically based path loss model forAn empirically based path loss model for
An empirically based path loss model forNguyen Minh Thu
 

Similar to Cellular automata with non-linear transitio rules for simulating land cover change (20)

seyed armin hashemi
seyed armin hashemiseyed armin hashemi
seyed armin hashemi
 
URBAN AREA PRODUCT SIMULATION FOR THE ENMAP HYPERSPECTRAL SENSOR.ppt
URBAN AREA PRODUCT SIMULATION FOR THE ENMAP HYPERSPECTRAL SENSOR.pptURBAN AREA PRODUCT SIMULATION FOR THE ENMAP HYPERSPECTRAL SENSOR.ppt
URBAN AREA PRODUCT SIMULATION FOR THE ENMAP HYPERSPECTRAL SENSOR.ppt
 
URBAN AREA PRODUCT SIMULATION FOR THE ENMAP HYPERSPECTRAL SENSOR.ppt
URBAN AREA PRODUCT SIMULATION FOR THE ENMAP HYPERSPECTRAL SENSOR.pptURBAN AREA PRODUCT SIMULATION FOR THE ENMAP HYPERSPECTRAL SENSOR.ppt
URBAN AREA PRODUCT SIMULATION FOR THE ENMAP HYPERSPECTRAL SENSOR.ppt
 
OGRS2016_ok
OGRS2016_okOGRS2016_ok
OGRS2016_ok
 
SIAM-AG21-Topological Persistence Machine of Phase Transition
SIAM-AG21-Topological Persistence Machine of Phase TransitionSIAM-AG21-Topological Persistence Machine of Phase Transition
SIAM-AG21-Topological Persistence Machine of Phase Transition
 
Regression_Presentation2
Regression_Presentation2Regression_Presentation2
Regression_Presentation2
 
Surface Wave Tomography
Surface Wave TomographySurface Wave Tomography
Surface Wave Tomography
 
Surface Wave Tomography
Surface Wave TomographySurface Wave Tomography
Surface Wave Tomography
 
Geographic information system – an introduction
Geographic information system – an introductionGeographic information system – an introduction
Geographic information system – an introduction
 
American Journal of Biometrics & Biostatistics
American Journal of Biometrics & BiostatisticsAmerican Journal of Biometrics & Biostatistics
American Journal of Biometrics & Biostatistics
 
PSO.ppt
PSO.pptPSO.ppt
PSO.ppt
 
3_Terrain catergorization for single Pol.ppt
3_Terrain catergorization for single Pol.ppt3_Terrain catergorization for single Pol.ppt
3_Terrain catergorization for single Pol.ppt
 
Molinier - Feature Selection for Tree Species Identification in Very High res...
Molinier - Feature Selection for Tree Species Identification in Very High res...Molinier - Feature Selection for Tree Species Identification in Very High res...
Molinier - Feature Selection for Tree Species Identification in Very High res...
 
AT_MB_MM_IGARSS2011.ppt
AT_MB_MM_IGARSS2011.pptAT_MB_MM_IGARSS2011.ppt
AT_MB_MM_IGARSS2011.ppt
 
MODULE VII_ Remote Sensing_Avantika.pptx
MODULE VII_ Remote Sensing_Avantika.pptxMODULE VII_ Remote Sensing_Avantika.pptx
MODULE VII_ Remote Sensing_Avantika.pptx
 
Using Artificial Neural Networks for Digital Soil Mapping – a comparison of M...
Using Artificial Neural Networks for Digital Soil Mapping – a comparison of M...Using Artificial Neural Networks for Digital Soil Mapping – a comparison of M...
Using Artificial Neural Networks for Digital Soil Mapping – a comparison of M...
 
MODELAÇÃO DO SOLO-PAISAGEM – A IMPORTÂNCIA DA LOCALIZAÇÃO
MODELAÇÃO DO SOLO-PAISAGEM – A IMPORTÂNCIA DA LOCALIZAÇÃOMODELAÇÃO DO SOLO-PAISAGEM – A IMPORTÂNCIA DA LOCALIZAÇÃO
MODELAÇÃO DO SOLO-PAISAGEM – A IMPORTÂNCIA DA LOCALIZAÇÃO
 
Harmonization of seismic hazard assessment: the SHARE example
Harmonization of seismic hazard assessment: the SHARE exampleHarmonization of seismic hazard assessment: the SHARE example
Harmonization of seismic hazard assessment: the SHARE example
 
Performance Analysis of Adaptive DOA Estimation Algorithms For Mobile Applica...
Performance Analysis of Adaptive DOA Estimation Algorithms For Mobile Applica...Performance Analysis of Adaptive DOA Estimation Algorithms For Mobile Applica...
Performance Analysis of Adaptive DOA Estimation Algorithms For Mobile Applica...
 
An empirically based path loss model for
An empirically based path loss model forAn empirically based path loss model for
An empirically based path loss model for
 

More from GIScRG

Validation of an agent-based model of shifting agriculture
Validation of an agent-based model of shifting agricultureValidation of an agent-based model of shifting agriculture
Validation of an agent-based model of shifting agricultureGIScRG
 
Modelling the role of neighbourhood support in regional climate change adapta...
Modelling the role of neighbourhood support in regional climate change adapta...Modelling the role of neighbourhood support in regional climate change adapta...
Modelling the role of neighbourhood support in regional climate change adapta...GIScRG
 
Modelling the Nicobar Islands in the aftermath of the 2004 Sumatra tsunami
Modelling the Nicobar Islands in the aftermath of the 2004 Sumatra tsunamiModelling the Nicobar Islands in the aftermath of the 2004 Sumatra tsunami
Modelling the Nicobar Islands in the aftermath of the 2004 Sumatra tsunamiGIScRG
 
Impacts of Network Topology on Tax Evasion in a Complex Artificial Social System
Impacts of Network Topology on Tax Evasion in a Complex Artificial Social SystemImpacts of Network Topology on Tax Evasion in a Complex Artificial Social System
Impacts of Network Topology on Tax Evasion in a Complex Artificial Social SystemGIScRG
 
An agent-based framework for modelling social activities and travel
An agent-based framework for modelling social activities and travelAn agent-based framework for modelling social activities and travel
An agent-based framework for modelling social activities and travelGIScRG
 
Modelling Individual Consumer Behaviour
Modelling Individual Consumer BehaviourModelling Individual Consumer Behaviour
Modelling Individual Consumer BehaviourGIScRG
 
Agent-based simulation of the spatial evolution of the historical population ...
Agent-based simulation of the spatial evolution of the historical population ...Agent-based simulation of the spatial evolution of the historical population ...
Agent-based simulation of the spatial evolution of the historical population ...GIScRG
 
MEME – An Integrated Tool For Advanced Computational Experiments
MEME – An Integrated Tool For Advanced Computational ExperimentsMEME – An Integrated Tool For Advanced Computational Experiments
MEME – An Integrated Tool For Advanced Computational ExperimentsGIScRG
 

More from GIScRG (8)

Validation of an agent-based model of shifting agriculture
Validation of an agent-based model of shifting agricultureValidation of an agent-based model of shifting agriculture
Validation of an agent-based model of shifting agriculture
 
Modelling the role of neighbourhood support in regional climate change adapta...
Modelling the role of neighbourhood support in regional climate change adapta...Modelling the role of neighbourhood support in regional climate change adapta...
Modelling the role of neighbourhood support in regional climate change adapta...
 
Modelling the Nicobar Islands in the aftermath of the 2004 Sumatra tsunami
Modelling the Nicobar Islands in the aftermath of the 2004 Sumatra tsunamiModelling the Nicobar Islands in the aftermath of the 2004 Sumatra tsunami
Modelling the Nicobar Islands in the aftermath of the 2004 Sumatra tsunami
 
Impacts of Network Topology on Tax Evasion in a Complex Artificial Social System
Impacts of Network Topology on Tax Evasion in a Complex Artificial Social SystemImpacts of Network Topology on Tax Evasion in a Complex Artificial Social System
Impacts of Network Topology on Tax Evasion in a Complex Artificial Social System
 
An agent-based framework for modelling social activities and travel
An agent-based framework for modelling social activities and travelAn agent-based framework for modelling social activities and travel
An agent-based framework for modelling social activities and travel
 
Modelling Individual Consumer Behaviour
Modelling Individual Consumer BehaviourModelling Individual Consumer Behaviour
Modelling Individual Consumer Behaviour
 
Agent-based simulation of the spatial evolution of the historical population ...
Agent-based simulation of the spatial evolution of the historical population ...Agent-based simulation of the spatial evolution of the historical population ...
Agent-based simulation of the spatial evolution of the historical population ...
 
MEME – An Integrated Tool For Advanced Computational Experiments
MEME – An Integrated Tool For Advanced Computational ExperimentsMEME – An Integrated Tool For Advanced Computational Experiments
MEME – An Integrated Tool For Advanced Computational Experiments
 

Recently uploaded

Science 7 - LAND and SEA BREEZE and its Characteristics
Science 7 - LAND and SEA BREEZE and its CharacteristicsScience 7 - LAND and SEA BREEZE and its Characteristics
Science 7 - LAND and SEA BREEZE and its CharacteristicsKarinaGenton
 
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...Krashi Coaching
 
Concept of Vouching. B.Com(Hons) /B.Compdf
Concept of Vouching. B.Com(Hons) /B.CompdfConcept of Vouching. B.Com(Hons) /B.Compdf
Concept of Vouching. B.Com(Hons) /B.CompdfUmakantAnnand
 
call girls in Kamla Market (DELHI) 🔝 >༒9953330565🔝 genuine Escort Service 🔝✔️✔️
call girls in Kamla Market (DELHI) 🔝 >༒9953330565🔝 genuine Escort Service 🔝✔️✔️call girls in Kamla Market (DELHI) 🔝 >༒9953330565🔝 genuine Escort Service 🔝✔️✔️
call girls in Kamla Market (DELHI) 🔝 >༒9953330565🔝 genuine Escort Service 🔝✔️✔️9953056974 Low Rate Call Girls In Saket, Delhi NCR
 
MENTAL STATUS EXAMINATION format.docx
MENTAL     STATUS EXAMINATION format.docxMENTAL     STATUS EXAMINATION format.docx
MENTAL STATUS EXAMINATION format.docxPoojaSen20
 
ECONOMIC CONTEXT - LONG FORM TV DRAMA - PPT
ECONOMIC CONTEXT - LONG FORM TV DRAMA - PPTECONOMIC CONTEXT - LONG FORM TV DRAMA - PPT
ECONOMIC CONTEXT - LONG FORM TV DRAMA - PPTiammrhaywood
 
Paris 2024 Olympic Geographies - an activity
Paris 2024 Olympic Geographies - an activityParis 2024 Olympic Geographies - an activity
Paris 2024 Olympic Geographies - an activityGeoBlogs
 
Mastering the Unannounced Regulatory Inspection
Mastering the Unannounced Regulatory InspectionMastering the Unannounced Regulatory Inspection
Mastering the Unannounced Regulatory InspectionSafetyChain Software
 
“Oh GOSH! Reflecting on Hackteria's Collaborative Practices in a Global Do-It...
“Oh GOSH! Reflecting on Hackteria's Collaborative Practices in a Global Do-It...“Oh GOSH! Reflecting on Hackteria's Collaborative Practices in a Global Do-It...
“Oh GOSH! Reflecting on Hackteria's Collaborative Practices in a Global Do-It...Marc Dusseiller Dusjagr
 
microwave assisted reaction. General introduction
microwave assisted reaction. General introductionmicrowave assisted reaction. General introduction
microwave assisted reaction. General introductionMaksud Ahmed
 
SOCIAL AND HISTORICAL CONTEXT - LFTVD.pptx
SOCIAL AND HISTORICAL CONTEXT - LFTVD.pptxSOCIAL AND HISTORICAL CONTEXT - LFTVD.pptx
SOCIAL AND HISTORICAL CONTEXT - LFTVD.pptxiammrhaywood
 
Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...
Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...
Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...EduSkills OECD
 
mini mental status format.docx
mini    mental       status     format.docxmini    mental       status     format.docx
mini mental status format.docxPoojaSen20
 
A Critique of the Proposed National Education Policy Reform
A Critique of the Proposed National Education Policy ReformA Critique of the Proposed National Education Policy Reform
A Critique of the Proposed National Education Policy ReformChameera Dedduwage
 
_Math 4-Q4 Week 5.pptx Steps in Collecting Data
_Math 4-Q4 Week 5.pptx Steps in Collecting Data_Math 4-Q4 Week 5.pptx Steps in Collecting Data
_Math 4-Q4 Week 5.pptx Steps in Collecting DataJhengPantaleon
 
CARE OF CHILD IN INCUBATOR..........pptx
CARE OF CHILD IN INCUBATOR..........pptxCARE OF CHILD IN INCUBATOR..........pptx
CARE OF CHILD IN INCUBATOR..........pptxGaneshChakor2
 
Contemporary philippine arts from the regions_PPT_Module_12 [Autosaved] (1).pptx
Contemporary philippine arts from the regions_PPT_Module_12 [Autosaved] (1).pptxContemporary philippine arts from the regions_PPT_Module_12 [Autosaved] (1).pptx
Contemporary philippine arts from the regions_PPT_Module_12 [Autosaved] (1).pptxRoyAbrique
 
Sanyam Choudhary Chemistry practical.pdf
Sanyam Choudhary Chemistry practical.pdfSanyam Choudhary Chemistry practical.pdf
Sanyam Choudhary Chemistry practical.pdfsanyamsingh5019
 
Interactive Powerpoint_How to Master effective communication
Interactive Powerpoint_How to Master effective communicationInteractive Powerpoint_How to Master effective communication
Interactive Powerpoint_How to Master effective communicationnomboosow
 

Recently uploaded (20)

Science 7 - LAND and SEA BREEZE and its Characteristics
Science 7 - LAND and SEA BREEZE and its CharacteristicsScience 7 - LAND and SEA BREEZE and its Characteristics
Science 7 - LAND and SEA BREEZE and its Characteristics
 
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...
 
Concept of Vouching. B.Com(Hons) /B.Compdf
Concept of Vouching. B.Com(Hons) /B.CompdfConcept of Vouching. B.Com(Hons) /B.Compdf
Concept of Vouching. B.Com(Hons) /B.Compdf
 
TataKelola dan KamSiber Kecerdasan Buatan v022.pdf
TataKelola dan KamSiber Kecerdasan Buatan v022.pdfTataKelola dan KamSiber Kecerdasan Buatan v022.pdf
TataKelola dan KamSiber Kecerdasan Buatan v022.pdf
 
call girls in Kamla Market (DELHI) 🔝 >༒9953330565🔝 genuine Escort Service 🔝✔️✔️
call girls in Kamla Market (DELHI) 🔝 >༒9953330565🔝 genuine Escort Service 🔝✔️✔️call girls in Kamla Market (DELHI) 🔝 >༒9953330565🔝 genuine Escort Service 🔝✔️✔️
call girls in Kamla Market (DELHI) 🔝 >༒9953330565🔝 genuine Escort Service 🔝✔️✔️
 
MENTAL STATUS EXAMINATION format.docx
MENTAL     STATUS EXAMINATION format.docxMENTAL     STATUS EXAMINATION format.docx
MENTAL STATUS EXAMINATION format.docx
 
ECONOMIC CONTEXT - LONG FORM TV DRAMA - PPT
ECONOMIC CONTEXT - LONG FORM TV DRAMA - PPTECONOMIC CONTEXT - LONG FORM TV DRAMA - PPT
ECONOMIC CONTEXT - LONG FORM TV DRAMA - PPT
 
Paris 2024 Olympic Geographies - an activity
Paris 2024 Olympic Geographies - an activityParis 2024 Olympic Geographies - an activity
Paris 2024 Olympic Geographies - an activity
 
Mastering the Unannounced Regulatory Inspection
Mastering the Unannounced Regulatory InspectionMastering the Unannounced Regulatory Inspection
Mastering the Unannounced Regulatory Inspection
 
“Oh GOSH! Reflecting on Hackteria's Collaborative Practices in a Global Do-It...
“Oh GOSH! Reflecting on Hackteria's Collaborative Practices in a Global Do-It...“Oh GOSH! Reflecting on Hackteria's Collaborative Practices in a Global Do-It...
“Oh GOSH! Reflecting on Hackteria's Collaborative Practices in a Global Do-It...
 
microwave assisted reaction. General introduction
microwave assisted reaction. General introductionmicrowave assisted reaction. General introduction
microwave assisted reaction. General introduction
 
SOCIAL AND HISTORICAL CONTEXT - LFTVD.pptx
SOCIAL AND HISTORICAL CONTEXT - LFTVD.pptxSOCIAL AND HISTORICAL CONTEXT - LFTVD.pptx
SOCIAL AND HISTORICAL CONTEXT - LFTVD.pptx
 
Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...
Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...
Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...
 
mini mental status format.docx
mini    mental       status     format.docxmini    mental       status     format.docx
mini mental status format.docx
 
A Critique of the Proposed National Education Policy Reform
A Critique of the Proposed National Education Policy ReformA Critique of the Proposed National Education Policy Reform
A Critique of the Proposed National Education Policy Reform
 
_Math 4-Q4 Week 5.pptx Steps in Collecting Data
_Math 4-Q4 Week 5.pptx Steps in Collecting Data_Math 4-Q4 Week 5.pptx Steps in Collecting Data
_Math 4-Q4 Week 5.pptx Steps in Collecting Data
 
CARE OF CHILD IN INCUBATOR..........pptx
CARE OF CHILD IN INCUBATOR..........pptxCARE OF CHILD IN INCUBATOR..........pptx
CARE OF CHILD IN INCUBATOR..........pptx
 
Contemporary philippine arts from the regions_PPT_Module_12 [Autosaved] (1).pptx
Contemporary philippine arts from the regions_PPT_Module_12 [Autosaved] (1).pptxContemporary philippine arts from the regions_PPT_Module_12 [Autosaved] (1).pptx
Contemporary philippine arts from the regions_PPT_Module_12 [Autosaved] (1).pptx
 
Sanyam Choudhary Chemistry practical.pdf
Sanyam Choudhary Chemistry practical.pdfSanyam Choudhary Chemistry practical.pdf
Sanyam Choudhary Chemistry practical.pdf
 
Interactive Powerpoint_How to Master effective communication
Interactive Powerpoint_How to Master effective communicationInteractive Powerpoint_How to Master effective communication
Interactive Powerpoint_How to Master effective communication
 

Cellular automata with non-linear transitio rules for simulating land cover change

  • 1. Cellular automata with non-linear transitio rules for simulating land cover change Katarzyna OSTAPOWICZ [email_address] T he 2009 Annual International Conference of the Royal Geographical Society , 2 6-28 August 2009 , Manchester Department of GIS, Cartography and Remote Sensing Institute of Geography and Spatial Management Jagiellonian University
  • 2.
  • 3.
  • 4.
  • 5.
  • 6.
  • 9.
  • 10.
  • 11. Workflow Input data Change probabilities Transition rates Natural and antropogenical variable CALIBRATION PART SIMULATION PART ANN/SVM Land cover maps Management plans cross-tabulation Land cover change simulation
  • 12. Input data Forest/non-forest: 1987, 2000, 2006 ( source: Landsat images, supervised, hierarchcal approach combining image segmentation, knowledge-based rules and likelihood decision rule ) Elevation and slope ( source: STRM DEM, spatial resolution 90 m ) Distance to artificial areas (source: land cover map 2006; distance operation) Migration, NUTS type (urban/rural), distace to urban NUTS (source: GUS) Ownership: state/private forest (source: state forest)
  • 13. Training plots (800, 200 per class) forest aforestation and natural succession non-forest deforestation
  • 14. Transition rules f(P ij , N i , R ij ) CHANGE PROBABILITIES (P ij ) NEIGHBOURHOOD (N i ) Σ n i > 6 (i – land cover type) forest f (elevation, slope, migration, NUTS type, ownership, distance to artificial areas) TRANSITION RATES (R ij ) e.g. for forest 0.25% per year TRAINING: forest change between 1987-2000-2006 SCENARIOS: 2006-2056
  • 15. Maximum accuracy for transsition rules ANN: 75% SVM: 79% 57,06 2050 53,27 2020 55,79 2040 52,16 2010 54,54 2030 50,98 2000 forest cover [%] year forest cover [%] year
  • 16.