https://www.geog.uni-heidelberg.de/md/chemgeo/geog/lehrstuehle/gis/jokar_simulate_urban_expansion.pdf

Integration of logistic regression, Markov chain and cellular automata models to simulate urban expansion

Developing reliable methods for representing and managing information uncertainty remains a persistent and relevant challenge to GIScience. Information uncertainty is an intricate idea, and recent examinations of this concept have generated many perspectives on its representation and visualization, with perspectives emerging from a wide range of disciplines and application contexts. In this paper, we review and assess progress toward visual tools and methods to help analysts manage and understand information uncertainty. Specifically, we report on efforts to conceptualize uncertainty, decision making with uncertainty, frameworks for representing uncertainty, visual representation and user control of displays of information uncertainty, and evaluative efforts to assess the use and usability of visual displays of uncertainty. We conclude by identifying seven key research challenges in visualizing information uncertainty, particularly as it applies to decision making and analysis.

/pdf/visualizing-geospatial-information-uncertainty-what-we-know-2p6o3omyap.pdf

Visualizing Geospatial Information Uncertainty: What We Know and What We Need to Know

Large-scale patterns of Amazonian biodiversity have until now been obscured by a sparse and scattered inventory record. Here we present the first comprehensive spatial model of tree α-diversity and tree density in Amazonian rainforests, based on the largest-yet compilation of forest inventories and bolstered by a spatial interpolation technique that allows us to estimate diversity and density in areas that have never been inventoried. These data were then compared to continent-wide patterns of rainfall seasonality. We find that dry season length, while only weakly correlated with average tree α-diversity, is a strong predictor of tree density and of maximum tree α-diversity. The most diverse forests for any given DSL are concentrated in a narrow latitudinal band just south of the equator, while the least diverse forests for any given DSL are found in the Guayana Shield and Amazonian Bolivia. Denser forests are more diverse than sparser forests, even when we used a measure of diversity that corrects for sample size. We propose that rainfall seasonality regulates tree α-diversity and tree density by affecting shade tolerance and subsequently the number of different functional types of trees that can persist in an area.

A spatial model of tree α-diversity and tree density for the Amazon

. Digital elevation models (DEMs) represent the topography that drives surface flow and are arguably one of the more important data sources for deriving variables used by numerous hydrologic models. A considerable amount of research has been conducted to address uncertainty associated with error in digital elevation models (DEMs) and the propagation of error to derived terrain parameters. This review brings together a discussion of research in fundamental topical areas related to DEM uncertainty that affect the use of DEMs for hydrologic applications. These areas include: (a) DEM error; (b) topographic parameters frequently derived from DEMs and the associated algorithms used to derive these parameters; (c) the influence of DEM scale as imposed by grid cell resolution; (d) DEM interpolation; and (e) terrain surface modification used to generate hydrologically-viable DEM surfaces. Each of these topical areas contributes to DEM uncertainty and may potentially influence results of distributed parameter hydrologic models that rely on DEMs for the derivation of input parameters. The current state of research on methods developed to quantify DEM uncertainty is reviewed. Based on this review, implications of DEM uncertainty and suggestions for the GIS research and user communities are offered.

/pdf/uncertainties-associated-with-digital-elevation-models-for-48iu7vegut.pdf

Uncertainties associated with digital elevation models for hydrologic applications: a review

https://www.uni-heidelberg.de/md/chemgeo/geog/lehrstuehle/gis/shafizadeh_helbich_2013.pdf

Spatiotemporal urbanization processes in the megacity of Mumbai, India: A Markov chains-cellular automata urban growth model

Monitoring patterns of urban heat islands of the fast-growing Shanghai metropolis, China: Using time-series of Landsat TM/ETM+ data

Principles of geographic information systems : an introductory textbook

The main objective of this research is to, first, monitor urban sprawl in the metropolis of Tehran and, second, to assess the CA–Markov model in the simulation of land-use change. Land-use changes generally occur in developing countries through new building construction. The rapid pace of this development has brought forward a number of research activities involving new applications for modelling this phenomenon. In this research, urban sprawl is examined in the urban fringe of Tehran and, subsequently, the CA–Markov model is implemented in order to evaluate the model. The CA–Markov model is a spatially explicit model for land-change modelling, which has not been implemented very frequently to track urban expansion. This model, however, which is an integrated module of both cellular automata and Markov Chain models, predicts forthcoming changes over time, based on the past use of land in the research area. Urban expansion between 1986 and 2006 was simulated through employing the model in the metropolis of...

Tracking dynamic land-use change using spatially explicit Markov Chain based on cellular automata: the case of Tehran

Formal methods for the description of spatial relations can be based on mathematical theories of order. Subdivisions of land are represented as partially ordered sets (posets), a model that is general enough to answer spatial queries about inclusion and containment of spatial areas. After a brief introduction to the basic concepts of posets and lattices, their applications to modelling spatial relations and operations for spatial regions in terms of containment and overlay are presented. An interpretation is given for new geographical elements that are created by the completion from a poset to a lattice. It is shown that a novel approach to characterize certain topological relations based on a lattice of a simplicial complex is a model for spatial regions that combines both topological and order relations and allows spatial queries to be answered in a unified way.

Wolfgang Kainz

Papers

Integration of logistic regression, Markov chain and cellular automata models to simulate urban expansion

Monitoring patterns of urban heat islands of the fast-growing Shanghai metropolis, China: Using time-series of Landsat TM/ETM+ data

Principles of geographic information systems : an introductory textbook

Tracking dynamic land-use change using spatially explicit Markov Chain based on cellular automata: the case of Tehran

Modelling spatial relations and operations with partially ordered sets