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--- group_modelling:goodnessoffit [2009/03/26 15:36]
inpeifgi
+++ group_modelling:goodnessoffit [2009/03/27 07:40]
inpeifgi
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 ====== Tools for Assessment of Multiple Scale Land Change Models ======
-Authors: Kristina Helle, Pedro Andrade, Edzer Pebesma
+Authors: Kristina Helle, Pedro Andrade, and Edzer Pebesma
 =====Introduction====
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 \\
+Pontius (2002) realized that we only need to take into account the cells that have changed, instead of comparing the whole maps. His more flexible approach allows to explicitly separate errors of quantity and of location and to use fuzzy classification.
+Li (2000) investigated the fractal properties which are typical to many land use (change) patterns. Another approach by Jantz and Goetz (2005) compared different goodness-of-fit measures on several resolutions for an urban growth model as land use changes may show varying behaviour on different scales. They do not only address global error rate and exact allocation but also geometric properties of the land use pattern like number and shape of clusters and length of edges. Some of these metrices are already implemented in TerraME but have not been used for testing.
-Li (2000) investigated the fractal properties which are typical to many land use (change) patterns. Land use changes may show varying behaviour on different scales. Therefore Jantz and Goetz (2005) compared different goodness-of-fit measures on several resolutions for an urban growth model. They do not only address global error rate and exact allocation but also geometric properties of the land use pattern like number and shape of clusters and length of edges. Some of these metrices are already implemented in TerraME.
-Pontius (2002) realized that we only need to take into account the cells that have changed, instead of comparing the whole maps. His more flexible approach allows to explicitly separate errors of quantity and of location and to use fuzzy classification.
 Calibration of cellular automata or agent-based models is not a trivial task as parameters influence is in most cases non-linear and often the number of parameters is high, making comprehensive evaluation of all combinations unfeasible. Simple approaches like by Clarke et al. (1998) generate lots of simulations to be evaluated by the user, they consider interactive visualization as an important tool. Still users may not find the most influential parameter combinations. This task was addressed by Miller (1998) who used several robust optimization algorithms to investigate the parameter space.
+The diversity of LUCC models may require different calibration and validation methods. An overview over current multi-agent models is given by Parker et al. (2003).
-=====Research Agenda=====
+=====Topics of the proposed Thesis and Questions to be answered in each work package=====
 The following open questions can be investigated by a PhD and a Master theses (Supervisors: Prof. Dr. Edzer Pebesma, Prof. Dr.Gilberto Câmara - not confirmed).
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 =====Mobility Measures=====
 The topic is at the overlap of the research at INPE (agent-based and cellular automata models of LUCC) and IFGI (statistics, calibration / validation of models). Therefore the theses should take place as sandwich (exchange: PhD 6-12 months, MSc 2-3 months), starting either at INPE or IFGI.
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 JANTZ, C. A.; GOETZ, S. J. {{group_modelling:analysis_of_scale_dependencies_in_an_urban_land-use-change_model.pdf|Analysis of scale dependencies in an urban land-use-change model}}. International Journal of Geographical Information Science. Vol. 19, No. 2, February 2005, 217–241
-LI, B.-L. 2000. {{group_modelling:fractal_geometry_applications_in_description_and_analysis_of_patch_patterns_and_patch_dynamics.pdf|Fractal geometry applications in description and analysis of patch patterns and patch dynamics}}. Ecological
+LI, B.-L. 2000. {{group_modelling:fractal_geometry_applications_in_description_and_analysis_of_patch_patterns_and_patch_dynamics.pdf|Fractal geometry applications in description and analysis of patch patterns and patch dynamics. }}. Ecological Modelling 132 (1/2): 33–50.
-Modelling 132 (1/2): 33–50.
 MANSON, S. M. {{encontros_e_eventos:inpeifgi2009:agent-based_dynamic_spatial_simulation_of_land-use_cover_change.pdf|Agent-based dynamic spatial simulation of land-use/cover change in the Yucatán peninsula, Mexico}}. 4th International Conference on Integrating GIS and Environmental Modeling (GIS/EM4):
@@ Line 116: / Line 115: @@
 E. MOREIRA, S. COSTA, A. P. AGUIAR, G. CAMARA, T. CARNEIRO Dynamic coupling of multiscale land change models: interactions and feedbacks across regional and local deforestation models in the Brazilian Amazonia, Ecological Modelling (//submitted//). 2009
+PARKER, D. C.; Manson, S. M.; JANSSEN, M. A.; HOFFMANN, M. J. & DEADMAN, P. 2003 {{group_modelling:multi-agent_systems_for_the_simulation_of_land-use_and_land-cover_change_a_review.pdf|Multi-Agent Systems for the Simulation of Land-Use
+and Land-Cover Change: A Review}}. Annals of the Association of American Geographers 93 (2): 314–337.
 PONTIUS, R. G. {{encontros_e_eventos:inpeifgi2009:pontius_2002_pers.pdf|Statistical Methods to Partition Effects of Quantity and Location During Comparison of Categorical Maps at Multiple Resolutions}}. Photogrammetric Engineering & Remote Sensing
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-==not relevant==
+==not directly relevant==
-GILES, R. H., Jr. & TRANI, M. K..1999. {{group_modelling:key_elements_of_landscape_pattern_measures.pdf|Key elements of landscape pattern measures}}. Environmental Management 23 (4):477–81.)
+GILES, R. H., Jr. & TRANI, M. K..1999. {{http://www.springerlink.com/content/je6g2v0khpl93gpc/fulltext.pdf|Key elements of landscape pattern measures}}. Environmental Management 23 (4):477–81.)

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